When a shopper in Charlotte wants coffee, they don’t open ten tabs and compare. They ask Google or ChatGPT for the best spot nearby, get three names with a line about each, and walk to the winner. No blue links. No website visit. The decision happened inside the answer.

That’s playing out millions of times a day, across every category: restaurants, dentists, auto shops, banks, hotels. If the results page matters less, what happens to the local program you’ve spent years building?

This shift is well underway. In the first four months of 2026, 68% of US Google searches ended without a click, up from 60% two years earlier (SparkToro and Similarweb). People are finding their answers and making their choices without ever leaving the results.

But AI didn’t invent its coffee response out of the ether. It read the brand’s listings, reviews, and local data — the same signals that earn local listings a spot in Google Search. Generative engine optimization, or GEO, runs on the foundation local SEO already builds, and it rewards the brands already doing local well.

So how can you build on the strength of your brand’s local search foundation to become the business AI recommends?

What is GEO (generative engine optimization)?

Start with the term. For two decades, search engine optimization (SEO) has meant earning a place in the list of links: better rankings, more clicks, the long game of keyword research, site structure, and authority.

GEO shifts the target. Sometimes called Answer Engine Optimization (AEO), it’s the work of becoming the business generative engines name when someone asks for a recommendation.

Modern AI doesn’t optimize around keywords alone. It recognizes entities: businesses, locations, brands, products and services. GEO is largely about making your locations recognizable as trustworthy entities.

Those engines, whether ChatGPT, Microsoft Copilot, or Google’s AI Overviews, don’t hand back ten blue links. They return AI-generated answers: a short, synthesized pick drawn from sources the model trusts.

That’s the mechanism behind zero-click search, where a searcher gets what they need without loading a page. The answer engines assemble that pick by reading your listings, your reviews, and your business information, which is the same material a search engine reads to rank you.

GEO isn’t:

• Stuffing AI keywords
• Writing for ChatGPT
• Replacing SEO
• Gaming prompts

GEO is:

• Trusted data
• Entities
• Reputation
• Structured information
• Authority

GEO doesn’t replace local SEO

Many marketers assume GEO requires an entirely new strategy. But Large Language Models (LLMs) don’t conjure local recommendations out of nothing. They assemble them from what’s already published: your listings, your location pages, the reviews and directories that mention you.

Feed them accurate, consistent, structured data and the model has something solid to repeat. Feed it three different sets of hours for the same store and it has a problem.

That problem has teeth. Picture a model fielding “best pediatric dentist near me.” It finds your hours one way on a directory, another way on your site, and a dead phone number on a third. Unsure which version is right, it hedges or picks the competitor whose information lines up.

AI leans on the same families of signals local marketers have always managed. Four of them do most of the work:

• Accurate location data: business name, address, phone number, hours, and services. The basics, and the ones a model trips over first when they disagree across sources.
• Reviews and reputation: ratings, review volume, recency, and response activity. Freshness and whether you reply weigh as much here as the star average.
• Local authority signals: citations, listings consistency, website authority, and brand prominence. The web’s way of confirming you’re real and established.
• Structured content: location pages, FAQs, schema markup, and service information. The machine-readable detail that lets a model quote you without guessing.

None of this is new to a local team. It tracks real user intent rather than keyword tricks, and a brand that keeps these in order is most of the way to being legible to a machine. The flip side is just as blunt: fragmented location data drags you down in both SEO and GEO, because the same gaps that bury a listing also confuse a model.

How AI is reshaping local discovery

AI is taking over the job people used to hand to a friend who knew the neighborhood. The search queries make it plain: “where should I get my oil changed nearby?” or “what’s the best dentist in Denver?”

Instead of a directory of choices to sift through, the searcher gets a verdict, because the model has already done the sifting. What it hands back is a curated recommendation, a short explanation of why, and reasoning pulled straight from reviews.

LLMs don’t crawl the web the way Google Search does. They synthesize information from trusted public sources including Google Business Profiles, Apple Business Connect, Bing Places, review platforms, directories, brand websites, and structured location data.

Our most recent local search behavior study shows a third of consumers (33%) already turn to AI tools often or always for local business information. For a fast-growing share of searches, this is the working default. Generative AI has become the front door, whether people ask ChatGPT, Google Gemini, or Google’s AI Overviews.

What consumers see

Look at what those answers actually say and you’ll find your own marketing reflected back:

• “This location is highly rated for…,”
• “Customers frequently mention…,”
• “Known for….”

The model isn’t inventing those lines. It’s paraphrasing your reviews, listings, and descriptions for a shopper who never opened them, which is a real shift in search behavior.

The pull toward the listing hasn’t disappeared, though: even after AI tools serve an answer, 87% of the people using them still open the original listing at least sometimes, our study found, many heading to Google Search to confirm hours and read the latest reviews before they act.

Why reputation becomes even more important

Reviews used to influence the click. Now they’re the source material the AI-generated recommendation is built from. When the review profile is thin or stale, the model has nothing current to quote, so you lose the mention before you ever lose the conversion. AI summaries are only ever as trustworthy as the reviews underneath them.

So reputation stops being a clean-up task and becomes a discovery function, and staying named in AI answers runs on the same habits that have always built local standing: review generation, response management, and keeping the profile current. That’s what online reputation management handles at scale.

How to earn citations in AI-generated answers

One of the newest questions in local search is also one of the most important: How do you get your business cited by ChatGPT, Google AI Overviews, Gemini, or Microsoft Copilot?

There isn’t a switch you can flip or a new ranking factor to optimize. Instead, AI models are more likely to reference businesses they can verify across multiple trusted sources. Before recommending a local business, they look for signals that reinforce one another: an authoritative website, accurate business listings, trusted directories, and a strong, current reputation.

That means the fundamentals of local SEO matter more than ever. Consistent business information (name, address, phone number, hours, and services) across Google Business Profile, Apple Business Connect, Bing Places, Yelp, Facebook, and industry-specific directories helps establish confidence that your information is accurate. When those sources align, AI has less uncertainty about which details to surface.

Reputation is equally important. AI-generated summaries frequently draw from review content to explain why a business is recommended, highlighting recurring themes like exceptional service, knowledgeable staff, or convenient locations. A steady stream of recent, authentic reviews gives AI richer, more relevant information to reference than an outdated profile with only a handful of comments.

Authoritative content on your own website strengthens those external signals. Comprehensive location pages, structured data, FAQs, and detailed service descriptions help AI understand your business as a well-defined entity rather than just another listing. The clearer your digital footprint, the more confidently AI can incorporate your business into its responses.

Ultimately, earning citations in AI-generated answers is about becoming one of the most trustworthy, consistent, and well-documented businesses across the entire local search ecosystem. The brands that invest in accurate data, strong reputations, and authoritative local content are increasing their chances of becoming the business AI recommends first.

The new ranking factors: what AI appears to prioritize

You already manage these signals for local SEO. What changes with AI is the weighting.

The signals that decide whether a model names you aren’t a mystery, and they aren’t far from what local search has always rewarded. Five appear to carry most of the weight.

Entity authority

AI has to understand what your business is before it can suggest you. That means a clear, consistent picture across the web of who you are, what you do, and where you operate — and location information that says the same thing everywhere it appears. When a model can resolve your brand to a well-defined entity instead of a fuzzy cluster of half-matching listings, you become a safe answer to surface. When it can’t, you’re a risk it routes around.

Reputation signals

Reviews feed the recommendation, but not as a single average. Models read star ratings for the baseline, review velocity for whether you’re still active and relevant, and review sentiment for the specifics they can quote back (“highly rated for short waits”). A four-star profile that stopped growing two years ago reads very differently to a model than a four-star profile collecting fresh reviews every week.

Content depth

A model can only describe what it can find. Detailed location pages, complete service information, and a real set of frequently asked questions give it the raw material to answer with confidence instead of guessing or skipping you. Thin pages leave gaps, and gaps are where a competitor with a fuller profile gets named instead.

Data consistency

Inconsistent data is the fastest way to lose the recommendation. Listings accuracy across every platform and third-party directory alignment tell a model your information is trustworthy enough to repeat. The moment your hours, address, or phone number disagree across sources, your credibility with the model drops, and at enterprise scale those small disagreements multiply across every location.

Local relevance

Local discovery is still local. Proximity matters, but so does location-specific information that proves each site genuinely serves its area, plus the community presence that signals you’re an established part of it rather than a pin dropped on a map. A model weighing “best dentist in Denver” is looking for the business that reads as authentically of Denver, not just near it.

Why multi-location brands face a unique challenge

Everything above is manageable for a single café with one listing and one set of reviews. It stops being manageable fast. An enterprise brand may run hundreds of locations, thousands of listings, and millions of customer interactions, and every one of those is a place where the data can drift out of sync. What’s a quick fix at one address becomes an operations problem at five hundred.

The drift shows up in familiar ways:

• Inconsistent listings across platforms,
• Duplicate locations that should have been merged,
• Outdated hours nobody caught,
• Sparse local content on pages that never got built out, and
• Unmanaged reviews piling up without a response.

Any one of these is a nuisance on its own. Spread across a footprint, they become the rule rather than the exception, and they rarely announce themselves — you find out when a customer does.

Here’s why that matters more now than it did a year ago. AI models aggregate information from multiple sources to build a single recommendation, which means your worst data and your best data get reconciled into one answer, whether you like the result or not.

Inconsistent information creates confusion, and a confused model plays it safe by naming the competitor whose details line up cleanly. The result is the part that should worry any enterprise marketer: brands lose control over the result. The story AI tells about your locations gets written by whatever fragments it can find, not by you.

That’s brand visibility bleeding out one location at a time, and it’s exactly the problem local listing management exists to solve with accurate data, kept consistent, across every location and every platform at once.

The GEO readiness framework

The work breaks into five moves. None of them is new to a local team; what’s changed is that a machine is now reading the output.

1. Audit location data. Go listing by listing and confirm the basics hold everywhere: every listing is accurate, every set of hours current, every service listed. This is the quickest fix and the most common reason a brand goes missing from AI recommendations.
2. Strengthen reputation signals. Generate more reviews, respond consistently, and keep recency up — a steady stream of fresh, answered reviews gives a model current material to quote and a reason to trust it.
3. Invest in location pages. Build pages with unique local content, real FAQs, complete service information, and genuine local relevance, so a model has something specific to pull rather than a thin template it skips.
4. Optimize for entity understanding. Make it unmistakable who you are, what you offer, where you operate, and why customers choose you — the clearer the entity, the more confidently AI can name you.
5. Measure visibility beyond rankings. Track AI mentions, local impressions, review trends, and conversion signals, because share of voice inside AI answers is now as telling as where you rank.

These aren’t a second program bolted onto local SEO; they’re what local SEO becomes when part of the audience is a machine.

The behavior has already shifted; the open question is who’s ready for it.

Enterprise brands need an AI-ready local strategy

Enterprise brands don’t struggle because they lack listings. They struggle because they manage thousands of locations across hundreds of publishers, making consistency nearly impossible without automation.

The future of local discovery belongs to the brands that run SEO and GEO as a single effort. The same foundation feeds both: strong local search signals are what earn the ranking and what earn the AI recommendation, so the work compounds instead of splitting in two.

As AI takes a bigger role in how consumers find and judge local businesses, the mandate for enterprise brands is straightforward: keep your location data, reputation signals, and local presence accurate, consistent, and readable by both search engines and AI.

The brands that win treat local discovery as brand experience — visible, verified, recent, legible to AI — across every location at once, and Rio SEO’s platform is built to run it at enterprise scale.

Want to know how prepared your locations are for AI-driven discovery? Start with a listings audit, fix what’s drifting, and you put your locations in front of the customers choosing inside the answer. The brands cleaning up now are the ones AI will recommend later.

Each quarter, we analyze Google Business Profile performance data across enterprise brand locations in six industries to show how local search behavior is shifting. This quarter’s local consumer search benahvior trends data covers 205,188 locations.

The clearest shift this quarter was the widening gap between visibility and action. Maps gained ground on Search year over year, while clicks grew faster than views overall.  And phone clicks, for decades the way customers made first contact with a local business, moved slower than anything else we measure.

These shifts have been building for some time, but they became more evident than ever before this quarter.  Google has spent years answering routine questions right on the results page, and AI Mode now handles a wider range of queries without requiring someone to visit a brand’s listing.  Changes like these may be contributing pressure on traditional Search visibility, while Maps continues to play a crucial role in local discovery. 

It wasn’t the same story across the board, though. Some industries saw clicks rise sharply while others lost ground, and conversion actions varied by category. Here’s where local search behavior shifted this quarter, industry by industry, and what to do about it.

The story behind the numbers

Between June 24 and July 17, 2025, a confirmed Google reporting glitch suppressed search impressions across Google Business Profile performance data. Engagement held steady throughout, and impressions recovered from mid-July. 

About six days of that window fall inside Q2 2025, the year-over-year (YoY) comparison base this quarter is measured against. A lower base makes growth look bigger, so the YoY view figures overstate the gain slightly. Click figures are unaffected.

Two Google core updates also landed in the quarter. The March update finished rolling out on April 8, and the May update ran from May 21 to June 2. Ranking volatility sits beneath every visibility metric here and should be kept in mind when reviewing the following results. 

Year-over-year local search trends

• Total Views: +9.6%

• Total Clicks: +10.7%

By type:

• Maps Views: +16.4%
• Search Views: +4.5%
• Clicks – Phone: +0.6%
• Clicks – Website: +10.8%
• Clicks – Driving Directions: +8.8%

From April through June, Maps views grew 16.4% YoY against 4.5% for Search views, a pattern that repeated in four of the six industries we track. Clicks outpaced views against Q2 2025, up 10.7% to 9.6%. Phone was the slowest-moving action with 0.6% growth.

Quarter-over-quarter local search trends

• Total Views: +3.1%

• Total Clicks: +11.7%

By type:

• Maps Views: +0.7%
• Search Views: +5.2%
• Clicks – Phone: +5.1%
• Clicks – Website: +15.8%
• Clicks – Driving Directions: +10.3%

Quarter over quarter, Search views grew 5.2% while Maps was nearly flat at 0.7%. People are doing more once they land on a listing: views grew 3.1% while actions on those listings grew 11.7%, led by website clicks at 15.8%. The same traffic is producing more calls, clicks and directions requests than it did three months ago.

Retail

• Total Q2 2026 views: +7.7% QoQ, +15.7% YoY
• Total Q2 2026 clicks: +13.7% QoQ, +11.9% YoY

Retail was the strongest performer of any established industry this quarter. Maps views grew 23.4% against Q2 2025, more than double Search’s 10.7%. Website clicks rose 20.4% and driving directions 14.2%. Phone clicks were the exception, flat at -0.8%. If your Maps growth outpaced Search by roughly that margin, you’re in line with the industry.

That gap is the thing to plan around. Shoppers who open Maps have usually chosen where they’re going, and what they do next depends entirely on what your listing tells them. The store with the local page that loads, a pin that’s right, and listing hours that match the ones on the door wins the foot traffic.

Where to focus next

• Point Maps actions at accurate store data. Driving directions grew 14.2%, and every one of those is someone heading to a physical door. A wrong pin, stale hours or a missed holiday closure turns into a wasted trip.
• Land the website click locally. Website clicks were the fastest-growing action at 20.4%. If that click lands on a homepage instead of the store’s own page, the highest-growth action in the industry ends on a search box.

Financial services

• Total Q2 2026 views: -0.8% QoQ, -5.9% YoY
• Total Q2 2026 clicks: +4.3% QoQ, +3.8% YoY

Every conversion action rose while views fell. Against Q2 2025, Maps views were down 9.7% and Search views down 3.7%. Website clicks led at +15.7%, with phone up 4.8% and driving directions up 2.0%. Fewer people reached these listings, and more of the ones who did took action. Falling views alongside rising clicks is the industry pattern this quarter, not necessarily a brand-level problem.

Which queries still reach a listing at all seems to be changing. Branch hours, locations and phone numbers are exactly the questions AI surfaces now answer outright, and AI Mode passed one billion monthly users this year. When Google answers the question on the results page, customers may have less reason to visit the listing at all.

Where to focus next

• Watch what happens after someone arrives. A dashboard tracking impressions alone reads this quarter as a decline. The growth only shows up when you measure the actions people took on the listing.
• Keep branch, office, and ATM details current everywhere. Hours, services and contact details now feed answers that appear before anyone reaches the listing, so a stale record surfaces as a wrong answer with no click for a customer to correct.

Service businesses

• Total Q2 2026 views: +12.9% QoQ, +15.0% YoY
• Total Q2 2026 clicks: +27.4% QoQ, +29.7% YoY

Website clicks led every action we tracked, up 37.6% year over year. Driving directions followed at +27.5%. Maps views (+15.7%) and search views (+14.6%) grew at roughly half that rate, so the people finding these listings acted on them more often than they did a year ago. Phone clicks moved the least, up 5.5%. 

That order tracks an interface change. Google has been swapping call buttons for images in several industries, and its new AI local packs carry no call button at all. Sterling Sky’s 2026 local search analysis found clicks-to-call declining across two years of Google Business Profile data while website clicks held steady. So a call number that grew this slowly likely reflects the layout rather than demand.

Where to focus next

• Audit the actions Google still surfaces. Website clicks and directions resolve straight from listing data, so a location pointed at a homepage, or a pin on the wrong side of the street, costs more than it did a year ago.
• Shorten the path to a booked job. Google is expanding agentic booking to local services, including calling businesses on a searcher’s behalf for home repair, beauty and pet care in the US this summer.

Healthcare

• Total Q2 2026 views: -2.4% QoQ, +1.4% YoY
• Total Q2 2026 clicks: +0.2% QoQ, -1.7% YoY

Across the healthcare locations in this report, phone clicks fell 7.1% YoY and website clicks 9.0%, while driving directions grew 7.9% and Maps views 7.2%. Search views were essentially flat at -0.1%. If your own call volume is down by roughly that much, the market moved with you. A steeper drop is worth looking into.

Healthcare was the only industry here where views grew, but clicks didn’t follow. More people reached these listings than a year ago, and fewer of them did anything from there. That doesn’t necessarily mean patients aren’t converting. Scheduling actions may be playing a larger role in how patients engage with healthcare listings, potentially reducing their reliance on traditional actions like call clicks.

Where to focus next

• Make it easy to book from the listing. Phone and website clicks fell 7.1% and 9.0%, and those are the two ways a patient books an appointment without leaving Google. Appointment links, accepted insurance, services offered and current hours all come straight from your listing data.
• Get the arrival details right. Driving directions grew 7.9%, the only action moving up. Suite number, which entrance to use, and department hours decide whether that trip ends at the right desk.

Hospitality

• Total Q2 2026 views: +2.0% QoQ, -14.2% YoY
• Total Q2 2026 clicks: +4.3% QoQ, -5.6% YoY

Hospitality brand locations saw Search views fall 26.7% YoY on average, the steepest annual drop anywhere in this quarter’s data. Maps views held nearly flat at -0.5%. Phone clicks fell 12.9%, and website clicks fell 8.2% while driving directions grew 6.5%. If your Search visibility fell sharply while Maps held, you’re seeing the same thing the rest of the industry is.

Hospitality searches are unusually easy for Google to answer without a click. Rates, availability, amenities and check-in times all appear in the result itself, and hotel search has carried booking modules and price comparison longer than any other local category. Maps and directions hold up because people who have already chosen where they’re staying still need to get there.

Where to focus next

• Feed the answer Google builds. Search views fell 26.7%, so what Google shows before the click matters more than it did a year ago. Amenities, policies, photos and current rates are what get a property into that answer.
• Own the details people check on the way. Directions grew 6.5% while every action that doesn’t involve leaving home fell. Entrance, parking and check-in information all sit in your hotel listings, and a guest who can’t find them arrives frustrated or calls the front desk instead.

Restaurants

• Total Q2 2026 views: -10.0% QoQ, +18.0% YoY
• Total Q2 2026 clicks: +5.9% QoQ, +4.8% YoY
• Food menu clicks per location: +7.3% QoQ, +5.7% YoY

Across the restaurant locations in this report, Search views grew 25.9% YoY against 10.7% for Maps views, the only industry where Search views grew faster than Maps views. Phone clicks fell 14.2% while driving directions grew 9.3%, and menu clicks and website clicks each rose 5.7%. Quarterly views fell 10.0%, giving back part of an unusually strong Q1.

Your menu used to be something people checked after they’d decided where to eat. Now it’s what they use to decide, and a missing price or a dish you stopped serving months ago costs you the visit.

Where to focus next

• Keep the menu current. Menu clicks grew 5.7% while calls fell 14.2%, so more diners are choosing straight from the menu on your listing. Prices, photos, seasonal changes and dietary tags all need to match what you’re actually serving today.
• Check where your order button sends people. Google routes ordering clicks to whichever provider is set as preferred on your profile. If nobody has set one, a diner who meant to order from you can end up on a marketplace instead, paying commission you never agreed to.

What Q2 tells us about local search

Directions grew in every industry we looked at. Calls fell in four of six. The clearest takeaway from Q2 is that the actions people take after finding a business are changing.

None of that is new. What this quarter shows is how much further it’s gone: the phone was the fallback when your listing didn’t answer the question, and diners, patients and shoppers are using it less. 

Wrong hours, a practitioner that moved locations, or a discontinued amenity may seem like small things at the location level. Across a thousand locations, they’re a revenue line that compounds, because nobody files a complaint about the location they decided not to visit.

Want to know where you stand? Request your free local audit to uncover hidden gaps, growth opportunities, and tips tailored to your brand.

Q1 marked another step toward AI-driven local discovery. As Google expands Gemini-powered experiences across Search and Maps, consumers are getting answers faster and often acting without ever clicking through.

That shift is changing the shape of local performance. In many industries this quarter, views declined while clicks held steady or increased. Search visibility softened. Maps often proved more resilient. And when consumers did engage, they showed stronger intent — researching services, requesting directions, or moving closer to purchase.

AI is part of that story. Richer listings, AI-generated summaries, and zero-click experiences are compressing the path from discovery to action. In some cases, brands may be losing measurable traffic while still influencing decisions. In others, incomplete listings may mean they’re not being surfaced at all.

The impact isn’t playing out evenly. Some industries saw demand surge; others saw visibility drop. Many saw the path to conversion change. Here’s where the quarter shifted, and what the data says to do next.

The story behind the numbers

We analyzed performance across 315,340 enterprise brand locations during a quarter shaped by overlapping Google updates and shifting search behavior.

Google confirmed three major updates in Q1:

• February 2026 Discover update (Feb. 5)
• March 2026 spam update (Mar. 24)
• March 2026 core update (Mar. 27)

We also saw outside signals of disruption. In February, Sterling Sky reported a rise in review posting blocks, with legitimate businesses seeing the message: “Posting reviews is turned off for this place.” If review volume slowed this quarter, that may be part of the reason.

At the same time, AI-driven discovery kept gaining ground. With Gemini now shaping more answers across Google Search and Maps, users are finding businesses differently, often acting without clicking.

Year-over-year local search trends

Local visibility and engagement both improved in Q1. Across Search and Maps, total views increased 8.3% year over year, while total clicks rose 7.4%.

The biggest driver was Maps, where views jumped 26.2% YoY, suggesting more consumers are discovering businesses closer to the point of decision. At the same time, Search views dipped 3.7%, which may reflect continued shifts in how Google surfaces local results and how consumers search.

Clicks were more mixed. Website clicks were essentially flat, while driving direction requests saw strong growth. That points to high-intent users moving from discovery to in-person action. Phone calls, meanwhile, declined year over year, which aligns with reports that Google has been removing the Call button from Map Pack listings.

By click type:

• Phone calls: -6.7%
• Website clicks: +0.3%
• Driving direction requests: +14.9%

The takeaway: consumers are still engaging with local listings, but the actions they take are changing.

Quarter-over-quarter local search trends

Local visibility softened in Q1. Across Search and Maps, total views declined 11.1% quarter over quarter, while total clicks dropped just 2.0%.

Even with fewer impressions, engagement held relatively steady, suggesting that the users who did find listings were still taking action.

The drop was steeper in Search. Search views fell -14.0% QoQ, while Maps views declined -7.7%, pointing to continued volatility in traditional search visibility and a more stable performance in Maps.

Clicks were more resilient. By click type, we observed:

• Phone calls: -0.4%
• Website clicks: +2.4%
• Driving direction requests: +4.6%

Consumers may be seeing fewer listings, but those who do are still engaging with intent. Let’s explore what brands are seeing in their Q1 data across industry segments.

Retail

• Total Q1 2026 views: -20.2% QoQ, +16.2% YoY
• Total Q1 2026 clicks: -8.8% QoQ, +6.3% YoY

Retail visibility cooled in Q1 after the holiday surge but remained well ahead of last year with Total Views up 16.2%. This was driven by Map Views surging 45.5% YoY, while Search Views fell slightly (-2.2%), signaling that retail demand is still healthy.

That aligns with the broader industry picture. According to the U.S. Census Bureau, total U.S. retail and food services sales were up 3.7% in Q1 compared to the same period in 2025. After a slight contraction in January, retail activity accelerated through February and March, with March up 1.7% — the strongest monthly gain in more than a year.

This increased online interest translated to in-store action, as Total Clicks rose 6.3% compared to Q1 2025. While Website Clicks remained flat (+0.1%) and Phone Clicks fell -8.9%, requests for driving directions grew by 19.8%. 

Consumers appear to be moving faster from discovery to decision. As search engines and AI-generated summaries surface richer information upfront, shoppers may be skipping traditional research behaviors like website visits and phone calls, and heading straight in-store.

That creates a clear opportunity for enterprise brands to win the decision before the click. If shoppers are making up their minds in search and maps, brands need to treat local listings as conversion channels, not just digital storefronts.

Where to focus next

• Protect local visibility as search demand normalizes. Accurate, complete listings and fresh content matter more as competition for attention tightens.
• Use inventory, promotions, and local offers to create urgency. Timely messaging can help convert shoppers as momentum builds.
• Turn Maps into a revenue driver. With direction requests climbing, optimize for the “near me” moment with local pages, reviews, and complete profiles that push people to visit.
• Prioritize review generation and response. Fresh reviews and active responses can help reinforce trust and improve conversion when shoppers are ready to act.

Financial services

• Total Q1 2026 views: -2.6% QoQ, -9.4% YoY
• Total Q1 2026 clicks: -0.3% QoQ, +5.4% YoY

Q1 financial services visibility lagged behind the same period last year, with a -9.4% drop in Total Views driven by -13.6% fewer Maps Views and -6.8% less in Search. Local visibility is becoming more difficult to earn in an increasingly competitive and AI-influenced search environment.

Even so, customer satisfaction in the banking industry held steady in Q1, with the American Customer Satisfaction Index reporting a score of 80 out of 100. The biggest gains came in the speed of in-branch transactions and the accessibility of branch and ATM locations, pointing to convenience and ease still having great influence on consumer decision-making.

Clicks told a more resilient story, growing 5.4% over Q1 2025.

Despite that YoY drop in views, consumers are engaging local listings in financial services at a higher rate. This conversion activity is being driven by increased Website Clicks (11.1%) and Clicks for Directions (7.2%), while clicks to call a location fell slightly (-2.6%). 

The rise in website clicks may reflect a broader industry trend: personalized digital experiences continue to be a major driver of retention in financial services, as customers increasingly expect seamless online tools and self-service options.

Consumers may also be spending less time browsing and more time evaluating. As trust, transparency, and convenience become more important in financial services, listings that quickly surface the right information may be more likely to convert.

Where to focus next

• Strengthen digital conversion paths. With website clicks rising sharply, ensure local pages and branch-level landing pages make it easy for consumers to research services and take the next step.
• Audit branch-level listing accuracy. In a trust-sensitive category like financial services, inaccurate hours, outdated services, or inconsistent data can quickly cost conversions.
• Highlight key services and specialties in Google Business Profiles. Consumers evaluating providers in search need immediate clarity on offerings like mortgages, wealth management, business banking, or lending.
• Monitor shifts between Maps and Search. Search held steadier this quarter, which may signal changing discovery behavior and the need to prioritize visibility across both surfaces.

• Prioritize reviews and reputation management. Trust is critical in financial services, and fresh reviews with active responses can reinforce credibility at the moment of decision.

Service businesses

• Total Q1 2026 views: -11.2% QoQ, +1.0% YoY
• Total Q1 2026 clicks: +2.2% QoQ, +10% YoY

Service businesses saw location visibility online stagnate in Q1. Map (-9.2%) and Search (-12.3%) views both declined quarter-over-quarter, reflecting softer discovery activity after the holiday season. Compared to the year prior, a 2.3% gain in year-over-year Search Views offset by a -1.2% drop in Maps Views left the segment ended up just a single percentage point ahead of Total Views in Q1 2025.

Clicks came out stronger.

Total clicks rose 2.2% QoQ and climbed 10.0% YoY, indicating that consumers who did view those listings online were more intent-driven.

Annual conversion growth was driven by Clicks for Directions (+16.3%) and Website Clicks (+10.6%); only Clicks to Call fell, by -6.2%.  

Consumers may be searching less often, but with greater intent when they do. Rising Website Clicks and Direction Requests suggest service-based brands are successfully capturing both online consideration and in-person action, while declining Calls point to a growing preference for self-service and richer in-search experiences.

For service businesses — from gyms and salons to post offices, pet care, and auto shops — complete listings and clear calls to action can still convert fewer impressions into stronger engagement.

Where to focus next

• Keep listings accurate and complete across every location. For service businesses, details like hours, services offered, booking availability, and contact information directly influence conversions.
• Strengthen digital conversion paths. With website clicks rising, make it easy for customers to book appointments, check availability, or learn more without friction.
• Optimize for high-intent actions. Phone calls and website visits increased this quarter, so ensure “Call now,” “Book now,” and service-specific CTAs are easy to find.
• Refresh photos and business descriptions regularly. In competitive service categories, visual trust signals and clear service information can improve conversion.
• Monitor location-level engagement trends. Service demand can vary widely by market, making local reporting critical for spotting opportunities and declines early.

Healthcare

• Total Q1 2026 views: +2.5% QoQ, +2.9% YoY
• Total Q1 2026 clicks: +5.9% QoQ, +3.0% YoY

Healthcare visibility and engagement both improved in Q1. Map (+11.1%) and Search (+0.2%) views rose over Q4, with Maps driving nearly all of the growth. That suggests more patients are turning to map-based discovery when searching for nearby care, urgent services, or in-person appointments.

Year-over-year figures show greater Views (+2.9%) and Clicks (+3%) when compared to Q1 2025, though digging deeper into types of clicks reveals an interesting trend. 

Both Phone and Website Clicks dropped YoY, by -4.5% and -5.4%, respectively. Conversion gains are being driven by the +15.1% increase in requests for driving directions.

Healthcare searches are often immediate and practical. People may care less about browsing and more about finding the closest available option, and yet trust signals are essential in healthcare. When local consumers don’t need to visit the website or call a location, it suggests that reviews, provider details, photos, accessibility info, and accurate categories may now be enough to drive a decision without requiring extra validation.

That aligns with broader industry trends. A 2026 practice-focused analysis of patient expectations found that online self-service channels (including portals, websites, and mobile apps) ranked as the #1 preferred booking method at 42%, ahead of telephone booking at 33%. Within that, 60% of patients listed the patient portal among their top three preferred ways to book, even though many still default to phone because they can’t easily find the digital option.

Patients are still actively searching for care, but increasingly expect immediate access to information and frictionless booking options. Listings that make the next step easy are more likely to convert.

Where to focus next

• Build trust signals with a solid reputation management strategy. It’s not enough to hope patients leave good reviews. Soliciting patient feedback and responding to all reviews helps show searchers the organization is trustworthy, caring, and involved.
• Prioritize online booking. With website clicks rising sharply, make appointment scheduling fast, mobile-friendly, and easy to access from local listings and local pages.
• Keep provider and service information accurate. Patients rely on listings for hours, specialties, accepted insurance, and urgent care availability.
• Optimize for map-based discovery. With Maps driving most of the visibility gains this quarter, complete and accurate Google Business Profiles are critical.
• Highlight high-demand services and specialties. Use local pages and listings to surface urgent care, primary care, diagnostics, and specialty services clearly.
• Monitor patient engagement by location. Local reporting can help identify markets where appointment demand is rising or where friction may be limiting conversions.

Hospitality

• Total Q1 2026 views: +7.2% QoQ, -10% YoY
• Total Q1 2026 clicks: -0.6% QoQ, +4.7% YoY

Hospitality visibility improved over Q4 2025, though performance lagged behind last year, as we see Total Views are down -10% YoY. Search Views fell noticeably (-22.9%), and a modest +5.9% gain in Maps Views couldn’t make up the difference.

Despite this loss in visibility, the hospitality brands we track saw Total Clicks increase 4.7% over Q1 2025. The greatest gain came from Clicks for Directions, which rose 13.4% YoY. This indicates those consumers still searching did so with greater intent and found what they needed — maybe in local listings, or perhaps via an AI assistant — to make the decision to head to a location. Clicks to Website rose 10.7%, while Clicks to Call remained flat.

That aligns with broader industry trends. National RevPAR (revenue per available room) rose roughly 3.6% YoY in Q1 2026, driven by slightly higher occupancy and stronger room rates. At the same time, Marcus & Millichap projects hotel supply growth will accelerate to about 2.6% in 2026, especially in the upscale and mid-scale segments, which could put upward pressure on vacancy rates as competition intensifies.

Rich listings, compelling photos, and seamless booking experiences remain critical for conversion.

Where to focus next

• Prioritize booking-ready local listings. With website clicks rising, make pricing, amenities, and “Book now” calls to action easy to find.
• Refresh visual content frequently. Photos and updated property details help travelers compare quickly and build trust faster.
• Strengthen Google and Apple Maps visibility. This means beefing up on-page content, review content, and responses, all of which feed the AI system Maps uses to recommend hotels in response to AI queries. 
• Monitor market-level competition closely. As supply grows in upscale and mid-scale segments, local reporting can help identify markets where visibility or engagement is slipping.

Prioritize reputation management. Reviews remain one of the strongest decision-making signals in hospitality, especially as travelers compare options more carefully.

Restaurants

• Total Q1 2026 views: +51.9% QoQ, +25% YoY
• Total Q1 2026 clicks: +49.6% QoQ, +3.7% YoY

People are hungry, and they’re going online to explore their options. Search visibility rose dramatically for the Restaurants segment this quarter, with a 51.9% increase in QoQ landing Total Views 25% higher than in Q1 2025. Restaurant brands are gaining visibility across both key local discovery channels — Maps for high-intent, in-the-moment dining decisions  (+27.7%), and Search for broader discovery like cuisine, menu, or branded queries (+21.3%).
Big picture, U.S. quick-service restaurants (QSR) saw net sales rise 2.1% YoY, rebounding from Q4 declines as brands stabilized pricing and menu mix. Full-service restaurants (FSR), meanwhile, faced more pressure, with visits down roughly 1.4% YoY, including a nearly 2% decline on weekends—traditionally a peak period.

Restaurant demand is rising, but the path to conversion may be shifting. Diners are comparing menus, checking pricing, and making faster decisions across both on-site and off-site channels. Total clicks jumped 49.6% QoQ and rose 3.7% YoY, indicating that stronger visibility translated into action, though to a lesser extent.

Where to focus next

• Use local campaigns and promotions to drive higher average checks and smooth demand during weekdays or off-peak periods.
• Optimize on-page, local listing, and reviews content for specific services and amenities. AI assistants and their underlying LLM systems are processing longer, more conversational queries from customers who are not only looking for a type of cuisine, but “Which restaurant along this route has high chairs?” or “Where can we stop for lunch that has accessible parking and washrooms?”
• Keep menus accurate and up to date. With menu clicks rising sharply, outdated pricing or missing items can create friction and cost conversions.

• Strengthen local reputation management. Reviews, photos, and timely responses help diners choose quickly when comparing multiple nearby options.

Multi-family residential

• Total Q1 2026 views: -9.3% QoQ, -28.5% YoY
• Total Q1 2026 clicks: +7.6% QoQ, +10.8% YoY

The U.S. apartment market is stabilizing, but still soft. Occupancy reached 94.9% in Q1 2026, up slightly from Q4, though still below year-ago levels. Demand has improved, with roughly 93,300 units absorbed in Q1 — one of the strongest first quarters in the past decade but annual demand remains slightly below the long-term average.

But while demand may be improving, digital discovery is still lagging.
Map (-7.7%) and Search (-10.8%) views both declined QoQ, continuing the downward trend in local discovery for multi-family residential brands. Total search views landed -28.5% lower than the same period one year prior.

Clicks told a more encouraging story. Total clicks rose 7.6% quarterly and 10.8% YoY, indicating that while fewer renters are discovering listings, the ones who do are further down the funnel.

While Clicks to Call and Website Clicks dropped — -14.3% and -12.8% respectively — Clicks for Directions grew 26.6%, indicating that a growing proportion of searchers are finding what they need and are ready to take action. In a softer market, renters may also be pre-qualifying properties through third-party sites, social, or aggregator platforms before engaging directly.

This could also indicate an increase in self-guided tours, in-person leasing visits, and drive-by evaluations of neighborhoods and curb appeal.

Where to focus next

• Protect search visibility where demand is softening. With Search views down more than 10% this quarter and nearly 30% year over year, complete, optimized listings are critical to staying discoverable.
• Turn website visits into leases. Website clicks surged 24.7%, so property pages should surface pricing, availability, floor plans, and tour scheduling immediately.
• Prioritize occupancy-driving content. In a market focused on retention and occupancy over rent growth, spotlight move-in specials, concessions, and high-value amenities in listings and local pages.
• Track high-intent properties and markets. Rising clicks alongside falling views suggests some locations are outperforming. Use location-level reporting to identify where demand is strongest and where intervention is needed.
• Reduce friction in the tour-to-lease journey. Driving direction requests rose modestly, signaling continued in-person interest. Make scheduling tours and contacting leasing teams as seamless as possible.

Conclusion

The Q1 data tells a clear story: local search is changing fast. AI is shrinking the path from discovery to decision, even as search is getting less predictable. And visibility alone means less than it used to. Brands that win will keep their local presence accurate, complete, and ready to convert across every location.
Want to know where you stand? Request a local audit to uncover hidden gaps, growth opportunities, and tips tailored to your brand.

Local search is changing faster than most enterprise teams can adapt and the data now shows exactly where performance is breaking down. 

Most notably, local listing visibility dropped 13.2% across search in 2025. Phone clicks fell 12.9%. Website clicks fell 7.7%. And yet — direction clicks rose 6.4%, the only major action to grow year-over-year. By Q4, total views were down 6.6% but total clicks finished 0.4% higher. Fewer people were seeing listings. The ones who did were closer to acting.

That’s the story defining the current state of local search: shrinking visibility, sharper intent.

Rio SEO’s 2026 local search report pulled performance data from more than 239,000 U.S. enterprise locations across seven industries from January through December 2025. The findings line up with what local marketers have felt for months: AI hasn’t killed demand. It compresses the journey and rewrites what gets a brand chosen.

In this blog (and report), “AI” refers primarily to Google’s AI Overviews, evolving Local Pack behavior, and the broader shift toward answer-first search experiences. 

Here’s what the data says, and what enterprise marketers should do about it heading into 2026.

A shorter journey, with trust as the deciding factor

The old local search path looked like this: search for a business, check its website, compare, call to confirm, then visit. Five steps. Plenty of room to rank your way into the consideration set.

The new path looks like this: search, decide, visit.

When AI Overviews and the Local Pack answer the question on the results page, the in-between steps disappear. Phone numbers, hours, services — surfaced up front. Reviews, ratings, sentiment — summarized in the snippet. The shopper, diner, patient, or renter doesn’t need to dial in or land on the homepage to feel confident moving forward. They’ve already decided.

That’s why direction clicks were the only metric that grew. They’re the action that survives when everything before the visit gets compressed out.

For enterprise marketers, this changes what visibility is worth. A view that doesn’t lead anywhere isn’t a win. A view that leads straight to the door is. And the deciding factor — the thing that turns surfaced information into a chosen brand — is trust.

What AI is actually rewarding

Google Business Profile isn’t just a listing anymore. It’s the source data feeding AI Overviews, Maps results, and the answers consumers see without ever clicking through. Even when a profile isn’t viewed by a local consumer, it’s still being read — by the systems deciding what to surface, summarize, and recommend.

The signals AI weighs aren’t new, but they’ve been re-weighted:

• Listing accuracy across hours, services, attributes, and photos
• Review velocity, recency, sentiment, and the actual language of the review
• Structured location pages with FAQs, schema, and service-level detail
• Consistency across Google, Apple, Bing, Yelp, and the long tail of directories — including sources that have come back into play under AI, like Reddit and MapQuest

Brand authority alone won’t carry you here. The biggest restaurant name in a market still has to feed AI the structured detail it needs — menu items, photos, dine-in options, real customer language — to be picked up as the answer to “best burger near me on a Tuesday.”

What the data reveals across industries

The top-line numbers hide some sharp contrasts. Retail, healthcare, and restaurants tell the cleanest version of the story.

Retail: Stable visibility, stronger intent

Retail visibility declined modestly, with total views dropping 5.3%, but Maps views barely moved (+0.5%) and direction clicks rose 9.5%, double the prior year’s growth. Phone clicks fell 9.6% and website clicks dropped 5.9%. 

Shoppers are skipping the discovery and the follow-up. They see enough in the listing to commit. For retail brands, that means the listing has to be conversion-ready, not just present. Hours, in-stock services, location-specific offers, photos that match what’s on the floor.

Healthcare: Growth driven by trust

Healthcare was the only vertical to see meaningful growth across key metrics. Total views climbed 7.7%, direction clicks 10.2%, website clicks 6.9%. Q4 clicks per location finished 15.2% higher year over year, a level of resilience no other vertical matched. 

Healthcare consumers are searching with intent, vetting providers before they call, and arriving ready to walk in. The trust signals matter more here than anywhere — board certifications, accepted insurance, specialty detail, patient testimonials surfaced in AI summaries. 

When the underlying data is rich and the trust signals are strong, AI surfaces you and consumers act.

Restaurants: Discovery is shifting elsewhere

Restaurants saw the sharpest declines across the board. Total views fell 31.7%. Maps views fell 40.1%. Food orders dropped 25.7% after growing 31.8% the year before. View declines have now spanned five straight quarters. Direction clicks held nearly flat at -1.0%, so dine-in intent isn’t gone — it’s just that fewer people are starting the journey on Google. 

Third-party platforms, AI recommendations, and changing consumer habits are absorbing the discovery layer. Restaurants that win from here are the ones feeding AI structured menu data, dine-in differentiators, and current photos — and not relying on brand recognition to do the work.

Other verticals: Same pattern, different pace

Financial services, service businesses, hospitality, and multi-family residential follow the same pattern. 

• Visibility tightened
• Calls dropped 
• High-intent actions held up better than anything else

Hospitality saw direct bookings fall 53.5% as travelers shifted to third-party platforms and AI-driven recommendations. Multi-family residential search views actually grew 8.6%, but phone clicks fell nearly 50% — interest rising, action delayed.

5 key takeaways from the data

Pulling back to the cross-industry picture, five clear patterns emerge:

• Visibility is shrinking, but high-intent actions — especially direction clicks — remain resilient.
• AI-driven discovery raises the stakes for accurate, structured, location-level data.
• Calls and website clicks are declining, signaling fewer touchpoints and faster decisions.
• The local journey is shorter but more decisive, rewarding brands that remove friction early and craft strong local experiences across the customer journey.
• Local performance varies sharply by industry. Brand averages hide what location-level benchmarking reveals.

What this means for 2026 planning

Audit listings for AI readiness, not just accuracy. 

Hours and addresses are table stakes. The data AI surfaces — services, attributes, photos, structured menus, accepted payments, appointment types — is what gets you picked up in the answer. Walk through a sample of your locations and ask whether an AI summary built from your GBP would actually represent the brand.

Treat reviews as a trust signal, not a scorecard. 

Velocity, recency, sentiment, and keyword match all factor into how AI evaluates you. A 4.6-star average from 2022 carries less weight than a 4.4 with fresh, specific reviews. Build the review program around continuous generation and substantive responses, not threshold-chasing.

Turn location pages from brochure to answer. 

The ones that perform have FAQs that mirror long-tail queries, schema that makes services machine-readable, and hyper-local content that proves the location is real and current. If a page reads like a template, AI will treat it like one.

Use verified customer feedback as content. 

Survey data, NPS comments, loyalty program feedback — owned content the brand can surface on local pages. It’s one of the cleanest ways to feed AI authoritative material that competitors can’t replicate, and it brings CX and digital teams into the same conversation.

Benchmark at the location level. 

A brand average hides everything that matters. The best-performing locations in your portfolio are doing something the others aren’t, and the worst-performing ones are bleeding visibility you can recover. Get the data location by location and act on the spread.

What this means for the future of local search 

Local search didn’t stop working in 2025. It got more selective. Brands that compete on clarity, consistency, and trust at the location level are the ones AI surfaces and consumers choose. Brands that treat GBP as a static listing are watching their visibility erode while their competitors get picked.

Local search isn’t just about being found anymore. It’s about being chosen.

The on-demand webinar walks through every vertical in the report, including the seasonal patterns, the Q4 rebounds, and the Q&A on call tracking attribution under AI, review management at scale, and how to use customer surveys as local-page content. If you’re planning the year and want the full picture, that’s the place to start.

The full 2026 Local search report breaks down performance across every major vertical, including seasonal trends, Q4 reversals, and what’s driving high-intent actions at the location level.

Watch the 2026 local search report webinar today

Watch the on-demand webinar to see the full dataset and how top-performing brands are adapting.

Google Maps just stopped showing options and started making decisions.

It’s 6:30 p.m. You’re meeting a client and need a place to host dinner — fast.

You ask: “Find a quiet restaurant with great service near me, and a table for two tonight.”

Not long ago, you would’ve handed you a list with ten options, ratings, distances, and a bit of comparison shopping to do.

Now, you get an answer. With its recent “Ask Maps” Gemini integration, Google has moved from search to selection.

This isn’t a tweak to search algorithms or even local search algorithms. Consider this a rewrite. Artificial intelligence now sits between your customer and your locations, listening, interpreting, and choosing for them.

Instead of typing keywords, users ask real questions. Rather than scanning results, they get recommendations. And instead of comparing options, they follow a path already mapped out for them.

Here’s what fuels those answers:

• Your Google Business Profile data
• Your reviews (what people say, how often, and how recently)
• Your photos, attributes, menus, and content
• The patterns in how people search, move, and decide

AI pulls it all together, fills in the gaps, and serves up a shortlist, or just one choice.

No scrolling. No second page. No safety net. That changes the stakes significantly for multi-location brands. When Google stops showing options, visibility isn’t about being present. It’s about being picked.

From results to recommendations: local search just changed shape

Local search used to reward visibility. Now it rewards certainty.

Traditional search engines relied on local search algorithms to rank options. Your job was to climb into the local pack, stand out in a list, and win the click.

AI changes the job: You’re no longer competing to be seen. You’re competing to be selected.

Then vs now

Then:

• Keyword → list of results → user decides
• Search behavior: scan, compare, choose
• Ranking in the local pack = visibility
• Optimization problems: improve position, drive clicks
• Goal state: be one of the top options

Now:

• Intent → AI synthesis → Google decides
• Search behavior: ask, refine, act
• Artificial intelligence and machine learning evaluate context, not just keywords
• Google Business Profiles feed the system, not just the ranking
• Goal state: be the answer

Follow-up questions seal it. A user doesn’t stop at “find a restaurant.”
They ask:

• “Quiet enough for a meeting?”
• “Do they have vegetarian options?”
• “Can I get a table at 7?”

Each question filters the field and reshapes the recommendation.

And each time, AI rewrites the shortlist based on what it knows (or doesn’t) about your locations.

Ranking still matters, but only to get considered by intelligent algorithms.

What happens next is different; AI takes over. It connects signals across your Google Business Profiles, reviews, attributes, and content. It weighs them against intent. Then it decides what’s worth showing.

That’s the shift, as local search evolves from being ranked to being chosen.

What feeds AI Answers

These are the signals Ask Maps relies on to generate answers.

• Google Business Profiles: Core facts: hours, categories, services, attributes
• Reviews: Language, detail, recency, and how you respond
• Photos and videos: What your location looks like—inside and out
• Attributes and amenities: “Quiet,” “outdoor seating,” “wheelchair accessible,” “same-day appointments”
• Menus, services, and products: Structured, up-to-date, and specific
• Website and local pages: FAQs, service details, and location-level content
• Third-party signals: Listings, social profiles, and external reviews

Google removed Q&A and replaced it with AI answers

Google didn’t just retire Q&A; it replaced it. The old model was simple: customers asked questions, and businesses answered them directly on their listings.

As Miriam Ellis at Whitespark points out, the new Ask Maps feature replaces business-written responses with AI-generated ones built from whatever information Google can find.

That includes customer reviews, menus and services, website and local content, and aggregated content from around the web, among other sources.

Not all of it is controlled. Not all of it is accurate, either.

Before, you could step in, clarify, and correct. Now, AI assembles the answer on your behalf, whether you like it or not.

Your brand’s voice is no longer the source. Your data is.

That means influence works differently. You don’t manage a Q&A feed anymore; you have to make sure every surface, from reviews and listings to local content and third-party signals, tells the same, complete story.

If it doesn’t, AI will fill in the blanks. You won’t see it happening, but your prospects will, in every market you serve.

If your data can’t answer the question, you won’t be the answer

AI doesn’t deal in “maybe.” Inside Google’s search engine, predictive local search is built to return confident answers, not a spread of options.

If your data is thin, missing, or inconsistent, you don’t rank lower. You disappear.

• Missing attributes? You’re not considered.
• Weak customer reviews? You’re not trusted.
• Gaps in local content? You’re not relevant.

That’s the visibility gap, and it widens fast across enterprise brands.

One location with rich, complete local map listings can match user intent and surface. Another with the same brand name but weaker data won’t even enter the conversation.

Voice search makes this sharper. There’s no list to scroll; just one answer tied to hyperlocal relevance.

One optimized location doesn’t fix the network.

AI evaluates every location on its own merits, so when some locations show up and others don’t, it’s not random.

It’s the data.

What enterprise brands need to fix, and fast

For enterprise brands, the challenge isn’t knowing what to do. It’s doing it everywhere, all at once, without creating new optimization problems or stretching resource allocation past the limit.

Because Google’s local search algorithms no longer smooth over gaps; they expose them.

Start with your data.

Every location. Every field. Every detail inside your Google Business Profiles. Categories, hours, services, attributes—if it’s missing or inconsistent, it breaks the chain. AI can’t confidently match user intent if the basics aren’t locked in.

Then move to reviews.

Not volume. Depth.

A five-star rating without detail doesn’t help AI understand what makes a location right for a moment. You need language—specifics like “quiet,” “fast,” “friendly”—the words real people use in voice search and real-world decisions. That’s what turns customer feedback into something usable.

Next, close the gaps.

Photos, menus, FAQs, attributes, local content—these aren’t enhancements anymore. They’re requirements. If your locations don’t clearly answer common questions, AI will either guess or skip you.

And your local content has to carry its weight.

Not duplicated pages. Not light variations. Each location needs structured, relevant information that reflects its reality—its services, its neighborhood, its role in that market. That’s how you build the context AI looks for.

Finally, start paying attention to the output.

Not just rankings. Representation.

What is Google actually saying about your locations? How are they being described, recommended, or excluded? That’s the feedback loop now.

Because this isn’t a one-time fix.

It’s an ongoing population of solutions—feeding, refining, and aligning your data so every location can compete on its own merits.

The brands that win won’t be the ones with the best rankings.

They’ll be the ones with the most complete, consistent, and usable data—at scale.

Why scale breaks without a platform at the enterprise level

Everything up to this point sounds manageable. Fix your data. Improve reviews. Build better local content.

Then reality hits: you’re not managing one location. You’re managing hundreds, or even thousands, across regions, teams, and systems that don’t always talk to each other.

That’s where it breaks.

Local SEO done manually or with point tools doesn’t scale across AI local search, voice search, and visual search environments. The more locations you have, the more chances for inconsistency. And in systems driven by artificial intelligence and natural language processing, inconsistency isn’t a small issue. It compounds.

One location with incomplete Google Business Profile data creates a gap. Fifty locations with inconsistent data create noise. Hundreds create confusion within the very systems that try to interpret your brand, and search engines don’t resolve that confusion in your favor.

They route around it. That’s the problem.

Local search algorithms, and the AI now increasingly embedded within them, don’t see your brand as a single entity. They see a collection of locations, each with its own signals, gaps, and brand mentions.

Which means scale introduces a new kind of risk:

The bigger your footprint, the harder it is to stay consistent.
The harder it is to stay consistent, the less likely you are to be chosen.

Fixing that isn’t about working harder, but working differently.

You need centralized control over your data, so every location meets the same standard. You need local flexibility, so each location reflects what actually happens on the ground. And those two things have to work together.

That’s where infrastructure comes in.

How Rio SEO can help

Listings, reviews, local pages, and reporting can’t live in silos. They have to connect, update, and reinforce each other in real time, not as one-off fixes but as a system that continuously feeds accurate, consistent data into the ecosystem.

That’s exactly the problem Rio SEO’s Local Experience (LX) platform is built to solve.

It’s not just to “optimize listings.” LX gives enterprise brands a way to manage the full surface area of local presence, from data and content to reputation and through performance, all in one place, at scale.

The question isn’t “do you rank?” It’s “does AI choose you?”

Traditional local search algorithms still sort, and the local pack still exists. But that’s no longer where decisions are made.

It’s where candidates are pulled from. The decision happens after.

Inside AI local search, inside the layer where search engines interpret intent, connect signals, and choose what to recommend: That’s the new front door.

And what gets you through it is simple:

• Your listings
• Your reviews
• The story your data tells, across every location

Feed the system with complete, consistent, specific information, and it can choose you with confidence.

Leave gaps, and it moves on.

In this model, visibility isn’t a given. It’s earned, one answer at a time. As Ask Maps continues to evolve, the brands that surface will be those with the most complete and consistent data.

See how your locations show up in today’s AI-driven Maps experience and where gaps may be costing you visibility. 

Google Maps is no longer just a directory layered onto navigation. With Ask Maps, Google is turning Maps into a conversational discovery engine that can interpret nuanced questions, display options visually, and guide users from exploration to action in a single experience.  

This added functionality symbolizes more than a quick feature release. It reflects a meaningful shift in how local search intent is understood. Google Maps is no longer waiting for a keyword. It is beginning to understand context, preferences, and real-world constraints in real time. 

Why conversational search changes local visibility 

This shift changes what local visibility actually means.  

In a traditional search environment, brands competed to match a query. In a conversational environment, brands compete to satisfy intent. That distinction matters. Search is no longer returning a simple list of options based on proximity and relevance. It is constructing answers. The businesses that appear are those with the most complete, consistent, and machine-readable signals across location data, attributes, and reputation. 

For consumers, this simplifies the decision journey. Instead of piecing together information across multiple listings, users can ask Maps more complex questions and get clear, useful recommendations.  

Whether it’s finding a location that’s open late, meets a specific need, or aligns with personal preferences, Google is increasingly doing that work upfront. Discovery, evaluation, and decision-making are coming together in one place, which raises the importance of every detail tied to a location across the digital landscape. 

In many ways, AI is now acting as a filter rather than a retrieval system. Historically, a business could appear in search results even if it only matched part of the searcher’s query. In a conversational experience, partial relevance is often not enough to appear in AI Overviews or in the top search results. If a location cannot fully support the intent behind a question, it may be excluded entirely from the answer. 

That shift raises the stakes for local visibility. Inclusion is about being confidently selected. 

What does Ask Maps mean for enterprise brands? 

For enterprise brands, this means local search optimization is becoming less about rankings and more about answer readiness. The fundamentals have not changed, but expectations are higher. If a location’s data is incomplete, inconsistent or outdated, it becomes much harder for Google to confidently include it in a conversational response. Accuracy is no longer just about user experience. It directly impacts visibility. 

Local data is a competitive advantage 

The first priority for all enterprise brands is to treat Google Business Profile management as infrastructure, not a checklist. Every location should have standardized, complete and consistently updated data across: 

• Name 

• Address 

• Phone 

• Hours 

• Categories 

• Attributes.  

Additionally, details like amenities, services, and accessibility are becoming more important because they help Google match locations to specific needs. At scale, this requires strong governance, automation, and regular validation across every location. 

Reviews now provide both feedback and context 

The second priority is to view reviews as both a trust signal and a source of insight. Reviews still influence visibility, but they also help Google understand what a business is known for.  

As AI systems take on a larger role in filtering and recommending businesses, reputation signals are becoming a key differentiator. Review velocity, the specificity of review content, and the quality of brand responses all contribute to how confidently a location can be surfaced in a conversational result. 

In a conversational Maps experience, that context becomes even more valuable. Enterprise brands should focus on generating authentic reviews, responding thoughtfully, and identifying common themes that can inform both operations and content. At the same time, it is important to stay within Google’s guidelines and avoid practices that could create risk. 

Connected systems matter more than ever 

Finally, enterprise brands should think in terms of connected signals rather than isolated tactics. Local performance is shaped by how well-structured data, customer feedback, and operational accuracy work together.  

Agencies supporting multi-location brands can play a key role here by building scalable systems that ensure consistency while allowing for local relevance. The goal is not to optimize for a single feature like Ask Maps, but to create a strong, reliable local presence that performs across any Google experience. 

Conversational Maps is not a distant concept. It is a natural next step in how local search is evolving. Brands that invest in accurate, complete and reputation-rich location data will be in a much stronger position as Google continues to reshape how consumers discover and choose local businesses. 

Prepare for the future of conversational search

Conversational search is raising the bar for local visibility. Rio SEO helps enterprise brands build the data accuracy, reputation strategy and scalable systems needed to stay competitive in an evolving Maps experience. Connect with our team to see how your locations can become truly answer-ready. 

Helpful content doesn’t win local search. Local SEO infrastructure does.

Case in point: you were told to create helpful content, so you did. You covered the angles. You improved clarity. You made it genuinely useful.

And your multi-location brand still didn’t rank in half the markets you operate in.

That’s where the framing breaks.

“Helpful” is a human standard. Search ranking is a machine decision.

Ranking isn’t a judgment about effort or intent. It’s a decision a search engine makes based on structure and signals — whether it can interpret, classify, and confidently position your page against thousands of others.

The real question isn’t “Is this helpful?” It’s “Is this machine-legible and rankable?” And for enterprise brands managing 500, 2,000, or 10,000 locations, that distinction isn’t philosophical — it’s financial.

Search doesn’t evaluate effort. It evaluates structure.

Search engines don’t reward intent. They reward interpretability.

How intent is inferred algorithmically — not empathically — is the defining constraint.

Modern search engines use machine learning to evaluate patterns, structures, relationships, and historical signals at scale. They predict, they don’t feel.

When a location page enters the index, it’s deeply evaluated.

• Headings are parsed
• Entities are extracted
• Geographic modifiers are weighed
• Internal links are mapped
• Structured data is validated
• Profile completeness is assessed
• Competitive proximity signals are compared

Your page becomes a pattern inside a competitive system.

And that gap between human expectation and mechanical evaluation is where most SEO advice goes wrong. For enterprise local brands, ranking is about sending clearer signals across every market you compete in.

A brief history of mechanical judgment

Search didn’t grow up reading essays. It grew up sorting files.

Early systems made decisions the simple way: set the rules, feed in the input, and get the output. Clean boxes. Clear lines. In or out.

That DNA is still there.

When your page enters the index, it’s dismantled and its structure is checked. Relationships are mapped. Signals are weighed against thousands of near-identical contenders.

Your carefully crafted article becomes something else entirely: Headings. Entities. Links. Patterns. Through natural language processing, Google Search converts that content into structured signals comparable across millions of documents.

Machine learning made Google Search more adaptive, but it didn’t give the system taste. Ranking still hinges on alignment. Does your page match the structural patterns the system has learned to trust?

When the answer is yes, visibility follows.

What SEO testing measures

Guidelines say:

• Use descriptive titles.
• Add local language.
• Complete your profiles.
• Improve content depth.

But guidelines don’t tell you what happens when you deploy a change across 1,200 locations with different competitive density, proximity bias, and category saturation. Testing does.

Enterprise SEO testing measures what actually moves visibility when you change something at scale:

• Standardizing title formats across 900 location pages
• Reducing GBP category sprawl across 1,100 listings
• Adding explicit neighborhood modifiers in dense metros
• Aligning schema markup across an entire location network

Then measuring:

• Local pack presence by city
• Ranking distribution across competitive tiers
• Visibility radius shifts
• CTR movement by market density
• Threshold signals required to compete in specific metros

Why controlled SEO testing matters more than guidelines

Enterprise brands can’t afford guesswork.

Guidelines tell you what platforms say they value. Testing shows what actually moves rankings across markets with different competition, density, and intent.

What works in Chicago may not work in Phoenix. What lifts automotive may stall in healthcare. What works in suburban markets may collapse in dense urban grids.

Controlled testing isolates change. It separates platform narrative from measurable impact. At scale, that difference matters because one misguided rollout doesn’t affect a single page. It affects your entire footprint and it’s expensive.

Testing turns optimization from opinion into an operational discipline.

The difference between correlation, causation, and reproducibility

When you analyze thousands of search engine results pages (SERPs) across markets, patterns emerge.

• Explicit geo-modified titles align with stronger visibility.
• Complete GBP profiles correlate with higher pack presence.
• Consistent internal linking supports ranking stability.

That’s correlation. It points the direction.

Causation is harder. It requires isolating a variable across comparable location groups and measuring lift against a holdout.

Reproducibility matters most. If the pattern holds across regions, verticals, and competitive tiers, it’s not a fluke. It’s operationally reliable.

At scale, reliability beats novelty.

What large-scale experiments reveal about local search

Large-scale SEO experiments do more than identify tactics. They surface what the system consistently rewards.

• If explicit geographic modifiers outperform generic proximity language across markets, proximity is structurally prioritized.
• If under-optimized profiles fail to compete regardless of brand strength, minimum completeness is enforced.
• If neighborhood-level specificity lifts only in dense metros, the system’s geographic model becomes visible.

Testing doesn’t just guide what to change. It reveals how visibility is allocated across your entire location network. And for enterprise brands, that insight is leverage.

Case study: When meaning was optional

Consider a competitive local SERP across hundreds of location pages, where two content approaches go live across comparable domains.

One set is structurally disciplined: clear geo-modified titles, consistent internal linking, explicit entity alignment, clean schema. The copy is technically accurate but thin.

The other invests in richer language and stronger brand voice, but with looser structural signals.

Then, rankings are measured across markets.

Controlled experiments have repeatedly shown that structurally optimized pages can rank even when semantic depth is minimal. Not because they’re more persuasive, but because they’re easier for the system to classify.

In multi-domain environments, search rewards clarity of signals before depth of meaning. Explicit location markers, clean hierarchy, and entity alignment reduce ambiguity and increase ranking confidence.

This creates a visibility vs. trust paradox. A thinner page can rank above a stronger one if it better mirrors the system’s structural expectations. Trust, authority, and brand perception may follow, but visibility often comes first.

For enterprise brands, the lesson is practical: Structure earns entry. Meaning earns conversion.

Search requires the first before it ever evaluates the second.

What AI didn’t change in search

The headlines keep declaring a reset. Artificial intelligence (AI) will change everything. Machine learning rewrites the rules. In fact, Gartner predicted that by 2026, traditional search engine volume will decline by approximately 25% as users increasingly rely on AI chatbots and virtual agents for answers.

And yet, across decades of Google Search updates, the fundamentals that drive visibility on SERPs haven’t disappeared.

Google Search still relies on:

• Clear page structure
• Logical internal linking
• Consistent topical focus
• Strong entity relationships
• Structured data and Schema Markup
• Mobile optimization and page load speed
• Protection against spam and low-quality content

Search behavior evolves. Interfaces shift. Voice search grows. AI features appear. But every search engine still depends on interpretable signals to evaluate content relevance and user experience.

AI adjusts how signals are weighted. It doesn’t eliminate the need to send them.

For enterprise brands, that continuity matters. Large-scale content creation, content optimization, and content strategy still succeed when they reinforce structure, entity optimization, and search intent clarity across every location.

The mechanics matured. They didn’t vanish.

AI content is not the disruption people think it is

What AI changed, then, is production speed — not the evaluation model. AI has accelerated content creation, but it hasn’t changed how a search engine evaluates that content once it enters the index.

AI-generated content aligns easily with existing ranking systems because it’s built from the same patterns search engines already reward: predictable hierarchy, clean topical grouping, structured phrasing, entity clarity.

From the perspective of Google Search and its AI algorithms, that content is legible.

AI algorithms still rely on structured data, entity clarity, and reinforced relevance to power AI Overviews, knowledge panels, and Search Generative Experience. Even AI search environments depend on the same structural signals that have historically driven search traffic.

What changes is scale.

AI lowers the barrier to producing structurally compliant content. More brands can generate pages that satisfy baseline content relevance. More competitors can enter the SERP with technically sound formatting.

That raises the competitive floor.

Automation succeeds when it mirrors machine expectations. Answer Engine Optimization isn’t a departure from SEO practices; it’s structured discipline applied to AI-driven environments.

The risk for enterprise brands isn’t that AI content will replace them. It’s that AI will make structural competence common.

When every competitor can generate passable, machine-legible pages, advantage shifts to precision:

• Sharper entity alignment
• Stronger internal architecture
• Cleaner geographic signaling
• More disciplined content changes across markets

AI didn’t rewrite the rules of search. It amplified the consequences of following — or ignoring — them.

Precision is the strategy

The case for precision over volume is simple: algorithms reward clarity, not completeness. Stripping content often improves performance because it sharpens signals. Every excess word dilutes intent. Every unnecessary flourish introduces ambiguity.

In algorithmic environments, precision is greater than completeness.

The false assumption in content creation is that “better writing” equals “better rankings.” It doesn’t. Better writing improves user experience. Better structure improves search engine interpretation.

Search was never designed to think like a human

It was designed to parse, classify, and rank patterns.

Disappointment happens when we expect interpretation instead of evaluation. When we anthropomorphize algorithms, we assume they’ll infer nuance, reward voice, or appreciate depth. They won’t. They score signals.

Winning, then, isn’t about sounding smarter. It’s about being more interpretable.

The brands that outperform aren’t the ones that say the most. They’re the ones that remove friction between intent and signal. They write with the algorithm in mind, not by dumbing content down, but by engineering it for clarity.

In machine-mediated environments, precision is performance. But precision at scale isn’t accidental.

For enterprise brands managing hundreds or thousands of locations, clarity has to be engineered. Titles standardized. Entities aligned. Schema structured. Internal logic enforced across every market.

That’s not a copywriting exercise. It’s an operational one.

How Rio SEO can help

Rio SEO’s Local Experience platform was built for that reality. It gives enterprise teams the controls to:

• Align location data across directories and search engines
• Enforce structural consistency across local pages
• Strengthen entity relationships market by market
• Measure ranking movement across your entire footprint

Because winning in search isn’t about saying more. It’s about sending clearer signals, everywhere you compete. If precision is the strategy, infrastructure is the advantage.

Explore how Rio SEO helps enterprise brands turn structural clarity into scalable visibility.

For years, brand discovery followed a familiar path. A consumer searched. Results appeared. The best-ranked brands earned the click.

That path is disappearing.

Today, brand discovery increasingly starts with an AI-generated summary. Not a website. Not a blog. Not even a traditional search result.

Generative search tools are rapidly becoming the first touchpoint. They name one or a few brands, tell a quick story, and move the customer one step closer to a decision. And they do it all without ever sending the customer to visit your site.

If your brand is not a part of that answer, the journey ends before it begins. Visibility now depends on whether AI systems recognize, understand, and trust your brand well enough to recommend it.

Discoverability no longer starts with a search result

Once upon a time, search engine visibility came down to position. Climb the rankings, win the click, earn the visit. Simple enough.

Not anymore.

Generative AI is rewriting the rules. Where traditional SEO used to be about being found, generative search is about being introduced. It’s not a list of blue links anymore, it’s a conversation. And in that conversation, AI acts less like a librarian and more like a trusted guide.

In fact, research shows around 15 million adults say generative AI is their primary tool for online research, with that number projected to rise to over 36 million online users in the next few years.

The rise of discovery layers

Search engines are evolving into what we can now call “discovery engines.” Generative AI tools like Google’s Search Generative Experience (SGE), Microsoft’s Copilot, and ChatGPT with web browsing aren’t just returning results; they’re also generating them.

They’ve become answer engines that offer opinions, summarize choices, and shape preferences before a user ever lands on a page.

Users are no longer typing in keywords and scanning ten blue links. They’re asking,

• “What’s the best children’s healthcare provider near me?”
• “Which restaurant brands are known for consistency across locations?”
• “Who leads in sustainable retail practices?”

AI responds with a shortlist and a narrative.

So, while traditional search rewards optimization, generative search rewards understanding.

If you’ve heard of Generative Engine Optimization or seen the acronym GEO showing up alongside SEO, this is what it’s all about.

Why visibility now starts upstream

This goes far beyond tweaking title tags or sharpening your metadata. It’s about something deeper — visibility that begins before SEO kicks in. Brand visibility is now shaped upstream of tactics, in the terrain of narrative, trust, and authority.

And if you’re only focused on where you rank, you’re missing where you matter.

In the generative search experience, your brand might never even be part of the conversation if the AI doesn’t recognize you as a credible source, regardless of how well your pages rank.

That’s because generative AI is pulling data from signals, stories, and sentiment across the web to paint a full picture.

For enterprise brands, this means visibility is shaped upstream across:

• Brand narratives
• Local business data
• Reviews and reputation
• Third-party validation
• Structured and unstructured content signals

If those signals are fragmented or inconsistent, the AI can’t confidently recommend your brand. This is where topical authority and entity clarity separate the recommended from the forgotten because when AI isn’t confident, it defaults elsewhere.

From search engine to sense-maker

Think of it this way: A traditional search engine was a map. Generative AI is more like a concierge. It doesn’t tell you where everything is; it tells you where you should go.

AI systems need to clearly grasp:

• Who your brand is
• What you offer
• Where you operate
• Why customers choose you

This requires more than keyword alignment. It requires entity clarity: a consistent, well-defined brand presence across every location, listing, and citation.

You can’t just shout louder. You need to be understood clearly, described consistently, and recognized widely.

From intent capture to intent creation: How generative search changes demand

For years, brands have built strategies around capturing intent. Someone searches “best waterproof running shoes,” and the goal is to show up high, earn the click, and win the sale.

That’s search marketing 101: reactive, tactical, and tightly tied to existing demand.

But generative AI flips the script. Now, the engine is making suggestions before users even know what they’re looking for. It’s sparking interest, seeding options, and shaping decision-making earlier in the discovery journey.

That shift from intent capture to intent creation changes the role of content, the purpose of visibility, and the brand’s definition of success.

Why brand discoverability is now probabilistic, not positional

Rankings assume stability, whereas AI answers are fluid, contextual, and variable. One day your brand is mentioned, the next it’s not. That’s the nature of the model, and in that environment, discoverability isn’t guaranteed anymore. It’s probabilistic.

Think about the questions being asked now. “What’s the best option for sustainable shipping?” “Which brands lead in skin barrier repair?” These aren’t product searches so much as they’re open-ended invitations for input.

AI responds with recommendations that carry weight. It forms a mental shortlist, a frame of reference. And if your brand isn’t part of that initial story, it might not matter how well you rank later.

So when we talk about AI visibility, we’re not just talking about showing up. We’re talking about showing up first, in the right context, with the right framing, at the moment of influence.

The implication here brands need to understand is that inclusion matters more than position.

That shift changes how we think about AI Overviews, content architecture, and even how we measure impact. Search volume and organic click-through rates still tell part of the story, but they can’t capture brand presence in this new environment.

You need to know how often you’re included. How you’re framed. And whether the AI gets your story right.

The new brand signals AI uses to decide who belongs in the answer

Generative search isn’t a black box. Generative engines aren’t guessing; they’re scanning, and drawing from a complex mesh of structured data, retrieval sources, semantic cues, and signals that point to authority, clarity, and trust.

The brands most likely to be included share a few common traits:

Consistent brand narratives

Your positioning must be clear and aligned across corporate pages, local landing pages, location listings, and external citations. Mixed messages create uncertainty and uncertain brands are rarely recommended.

Third-party validation

Third-party validation means reputation management, reviews, media coverage, and how other platforms describe you. These external signals carry weight because they’re perceived as unbiased. And for an AI engine trying to build a balanced response, third-party proof often beats first-party claims.

Experienced proof

Case studies, outcomes, and documented customer experiences reinforce topical authority. AI systems prioritize brands with evidence of real-world performance. Your brand isn’t credible because you said it is, but because the local ecosystem agrees.

Entity and location clarity

Structured data, accurate listings, and complete business attributes help AI systems categorize and contextualize your brand. If your locations aren’t clearly defined, they’re less likely to be surfaced in local and high-intent queries. That’s where structured data, knowledge bases, and voice assistants all come into play to help the engine see your brand in sharp focus.

None of this is about ranking tricks. It’s about recognition. Generative AI doesn’t need to be impressed; it needs to be sure. That certainty comes from the signals your brand sends, whether intentionally or not.

Generative search as the new top of the funnel

AI summaries now sit where early discovery used to happen, before a user even hits your site.

That means blog posts, comparison pages, and product explainers don’t get the same chance to do their job. That means fewer clicks but higher stakes. When it excludes you, there’s no second page of results to fall back on.

In generative search, brand discoverability means three things:

• Being named
• Being described accurately
• Being recommended confidently over others

Those are the new benchmarks for search visibility.

What generative search gets wrong and why brands must correct the record

AI pulls from the signals it sees. Unfortunately, when it sees gaps, it fills them with guesses. That’s how brand stories get lost, flattened, or rewritten entirely.

Here’s the risk:

• AI oversimplifies your unique value
• Defaults to louder or more established competitors
• Misses key differences in highly specialized or regulated industries
• Gets local details wrong, or skips them altogether
• Flattened brand positioning

You can’t afford to wait for these errors to show up in the search engine results. You need to prevent them.

You need brand guardrails for AI interpretation.

Guardrails mean structuring your brand data so AI sees a complete, consistent picture. That starts with your local listings, pages, and directories. Every location needs accurate, optimized content and business data that are widely distributed and kept up to date. That includes schema markup, business attributes, reviews, hours, services, and any data point AI uses to evaluate relevance and credibility.

Fixing inaccuracies is reactive. Guardrails that guide how AI interprets your brand are proactive, and that matters. Generative AI won’t ask if it’s right. It will just answer.

How marketing leaders should rethink AI search strategy in 2026

Now that we understand how AI search has collapsed the gap between brand, content, CX, and SEO — and that search engines now answer questions using LLM-generated responses, not just web rankings — we can see that visibility depends less on keyword performance and more on semantic understanding. This means how well AI tools grasp what your brand offers and why it matters.

Search optimization is no longer the whole game, so stop measuring success only by traffic. That metric is blind to what generative search actually influences.

Start measuring what matters:

• Inclusion frequency: How often are you named in AI-generated answers?
• Brand framing in AI responses: When you’re mentioned, are you positioned accurately and competitively?
• Consistency across AI platforms: Do different AI tools describe you the same way?

These are the new indicators of visibility and trust in AI search environments.

LLMs don’t see team boundaries. They pull from everywhere at once, across your brand voice, your CX data, your structured content, and your reviews.

If those signals aren’t aligned, you confuse the engine.

Key takeaways

• Align brand, content, and CX narratives across all touchpoints
• Audit how AI tools describe your brand today, running real queries
• Identify gaps between brand intent and AI interpretation
• Strengthen schema markup and structured content to support semantic clarity
• Invest where third-party credibility compounds: reviews, PR, partnerships, citations

These tactics are essential in building the trust AI engines need to include and recommend your brand.

And that means search, brand, CX, and content teams can no longer operate in isolation. It’s time to bring these teams together with one goal: make the brand unmistakable and unmissable, no matter where or how the question is asked.

That’s how you evolve from CX to HX, creating connected, human experiences across every touchpoint, for AI and for the people your brand serves.

The fourth quarter of 2025 confirmed a pattern we’ve seen building all year. Local visibility is harder to earn, but consumer intent remains strong. Brands that win are those with accurate, action-ready listings and experiences designed for AI-driven, often zero-click discovery.

If it felt harder to stay visible in Q4, you weren’t imagining it. Holiday demand was high, but so was disruption, with multiple major Google updates, shifting search layouts, and the growing influence of AI all changing how customers found and engaged with local businesses.

When discovery habits shift, so do expectations. And when it comes to local experience (LX), what worked last quarter might not work now.

The good news is that you’re not navigating it alone. Each quarter, we analyze performance across more than 228,000 enterprise brand locations across eight industries to surface what’s changing, what’s working, and where to focus next. 

This Q4 2025 report distills those insights to help you meet customers where they are, protect performance through volatility, and stay competitive as 2026 begins.

The story behind the numbers

Q4 brought its usual seasonal surge of holiday shoppers, and this year, brands had to contend with a confirmed Google core update in December and smaller updates in October and November. Each introduced noticeable volatility, especially in local visibility, peaking just ahead of the holidays and reshaping how (and where) businesses showed up in search.

At the same time, search behavior has continued to shift. Our most recent consumer behavior survey found that 84% of consumers are searching online daily for local businesses, and 60% say they click on AI-generated overviews in Google Search. Discovery is still happening, but not always where or how it used to.

Let’s take a look at the overarching trends from Q4, then dig into the industry-specific insights to help contextualize your local performance.

Year-over-year local search trends

On average, brands saw a clear drop in local search visibility in Q4 2025, with aggregate total views down 13.2% year-over-year across both Maps and Search, though there were variations by industry. The decline was evenly split — Maps views fell 13.0%, and Search views dropped 13.4% — reflecting both increased competition for attention and changes in how Google surfaces results.

Despite fewer impressions, engagement held relatively steady. Total clicks dipped only 1.8% YoY, a sign that users who do find you are more likely to act. Breakdown by click type shows the same shift:

• Phone calls: –12.9%
• Website clicks: –7.7%
• Driving direction requests: +6.4%

That rise in direction clicks suggests shoppers are moving with intent, especially around high-traffic holidays. Conversion opportunities remain strong for brands that show up with accurate, action-ready listings.

Quarter-over-quarter local search trends

Local visibility rebounded in Q4, with total views up 12.5% across both Maps and Search. Maps views rose 11.2%, while Search views climbed 13.5%, likely driven by increased consumer activity around the holidays and recovery from Q3’s reporting disruptions.

Clicks dropped 4.8% quarter-over-quarter, suggesting that while more users saw listings, many found what they needed without taking additional action.

• Phone calls: –2.6%
• Website clicks: –6.8%
• Driving directions: –1.4%

This aligns with the broader shift toward zero-click experiences, where AI-generated overviews, rich snippets, and enhanced local listings surface answers directly in the search interface. As listings become more complete and search becomes more predictive, users may not need to click through to convert.

Visibility is still critical. But clarity, completeness, and confidence-building content are what move users from intent to action, even if that action happens off page.

Retail

• Total Q4 2025 views: +36% QoQ, +7.8% YoY
• Total Q4 2025 clicks: +0.8% QoQ, -1.4% YoY

Map (+37.7%) and Search (+34.7%) views surged, pointing to renewed discovery activity heading into the holidays. That aligns with early reports from Visa and Mastercard showing ~4% U.S. holiday retail sales growth—a sign that consumers were shopping actively, both online and in-store.

Clicks told a more tempered story. Total clicks rose just 0.8% quarter-over-quarter and remained slightly behind last year (–1.4% YoY), indicating that even as listings gained exposure, engagement didn’t climb at the same pace. Most of the growth came from phone calls (+2.8%), likely tied to high-intent scenarios such as store hours, inventory checks, or pickup logistics. Website clicks were essentially flat (+0.6%), and driving direction requests grew by only 0.1%.

This suggests a few trends: shoppers are browsing more locally, turning to listings for quick answers, and making decisions faster — often without clicking through. With AI-powered summaries and action-rich listings doing more of the heavy lifting, the path to purchase is shortening.

Where to focus next

• Keep listings accurate across all locations, especially for hours, inventory, and holiday updates — the basics still drive foot traffic.
• Use real-time inventory feeds to surface available products in local search results and reduce friction.
• Optimize GBP for high-intent actions like “Get directions” and “Call now” — they’re still your best signals of conversion readiness.
• Prioritize mobile experience, since most local retail searches start and end on phones.
• Leverage AI-driven personalization to tailor promotions, product suggestions, and follow-ups — especially during peak seasonal moments. Want to see what a fully personalized local journey looks like? Explore this guide.

Financial services

• Total Q4 2025 views: +1.7% QoQ, -12.9% YoY 
• Total Q4 2025 clicks: -3.2% QoQ, +1.8% YoY

After a visibility slump earlier in the year, financial services listings stabilized in Q4. Views rose slightly quarter-over-quarter, driven entirely by Search views (+11.2%), while Map views declined (–12.0%). It’s a signal that more users are evaluating providers via search results rather than map-based discovery and it’s the first we’ve seen Search and Maps views trend this way in a while.

Clicks dipped overall quarterly and were down dramatically from 2024. Phone inquiries rose (+2.8%) from Q3, but website (-4.3%) and driving direction clicks (-4.5%) fell — suggesting that while some consumers reached out directly, fewer advanced to in-person visits or deeper digital engagement. 

The macro context offers some explanation: U.S. banks reported strong Q4 profits, fueled by resilient consumer borrowing. But that strength doesn’t automatically translate to local action. Financial brands still need to meet rising expectations around transparency, digital experience, and trust.

Compared to last year, total views per location fell -20.6%, compounding the decline from the -17.3% drop YoY from 2023 to 2024. Financial services consumers are clicking less, too, as we see that metric -6.4% from 2024.

Where to focus next

• Audit listings regularly for hours, services, and appointment options; 53% of consumers say they’re unlikely to visit a business with inaccurate listings, and even small discrepancies can cost visits.
• Highlight local advisors, specialties, and GBP services to give consumers clear reasons to choose your brand over national alternatives.
• Track branch-level direction requests to identify growth hotspots and optimize in-person service.
• Ensure CTAs like “Schedule an appointment” are visible on mobile — that’s where most customers are making decisions.

Service businesses

• Total Q4 2025 views: +12.3% QoQ, -10.8%
• Total Q4 2025 clicks: -3.3% QoQ, -5.3% YoY

Service businesses — from gyms and salons to post offices, pet care, and auto shops — saw a healthy rebound in visibility this quarter. Search views were up 15.4%, and map views climbed 7.7%, signaling that consumers are still actively looking for local services.

But engagement tells a more complex story. Clicks fell across all categories, including phone calls (–1.1%), website visits (–1.9%), and driving directions (–5.5%). That decline doesn’t mean interest is down—it suggests that more users are finding what they need directly in search, without clicking through.

Service business views per location fell -17.4% YoY, surpassed only by Restaurants (-31.7%) and Financial Services (-21.1%) in terms of reduced views. However, as we’ve pointed out, that doesn’t mean brands aren’t being found in AI answers.

In a world of AI-powered search and zero-click answers, listings need to work harder. Consumers are making decisions inside the results page, not after clicking through to check things out. That makes full, structured, and accurate listings non-negotiable. If your services aren’t clearly listed, your photos are outdated, or your information is inconsistent across platforms, you risk being skipped by both people and algorithms serving them instant answers.

Where to focus next

• Monitor and update your listings regularly to ensure service details, hours, and location data stay accurate across platforms like Google and Apple Maps.
• Add structured data to highlight services and availability (like classes, bookings, or appointments), so answer engines can surface your offerings correctly.
• Refresh photos and business descriptions to stand out in visual results and map packs, where trust is earned at a glance.
• Invest in brand experience, including consistency across reviews, listings, and on-site service, to build trust at scale.

Healthcare

• Total Q4 2025 views: -8.8% QoQ, +3.2% YoY
• Total Q4 2025 clicks: -5.2% QoQ, +8.3% YoY

Q4 introduced some turbulence in healthcare visibility. Views dropped 8.8% from Q3, driven largely by a steep -22.5% decline in Map views, while Search views fell a more moderate -4.2%. But the bigger story is in the engagement: despite the visibility dip, clicks still rose +8.3% YoY. It’s proof that high-intent patients are still finding and acting on relevant listings.

Driving direction clicks fell 4.2%, and website clicks dropped 9.1%, pointing to increased selectivity. Patients aren’t browsing. They’re scanning, judging, and acting fast once trust is established. That tracks with industry data showing a long-term rise in patient visits per provider — even through seasonal lulls and softening primary care interest online.

With fewer paths to discovery and a growing focus on patient experience, healthcare brands must prioritize clarity, accessibility, and relevance across every local entry point.

Where to focus next

• Use Specialty Pages to surface high-demand services like diagnostics, urgent care, and specialty clinics. Get the Local Pages Playbook
• Emphasize trust signals like verified hours, accepted insurance, and provider bios on listings and local pages.
• Ensure accuracy in Map listings, especially for multi-location systems, as patients rely on these details to navigate care.
• Streamline booking experiences by linking directly to online scheduling or virtual visit options.

Hospitality

• Total Q4 2025 views: -17.8% QoQ, -15.8% YoY
• Total Q4 2025 clicks: -1.6% QoQ, +11.9% YoY

Hospitality visibility dropped sharply in Q4, with Search views down –21.7% and Map views falling –13.9%. That volatility reflects broader shifts in Google’s UI and user behavior, but the story doesn’t end there: despite fewer impressions, engagement remained strong. Total clicks rose +11.9% year-over-year, and driving directions increased +3.3% quarter-over-quarter—proof that travelers are still booking, just with more intent and less browsing.

Industry trends back that up. While RevPAR softened slightly, overall occupancy held steady. Luxury and upper-upscale segments outperformed, posting RevPAR gains of +2.9% and +0.4% YTD, according to Cushman & Wakefield. Discerning guests are still spending, just more selectively.

For hospitality brands, the mission is clear: earn trust fast, convert in fewer steps, and make every listing ready to capture last-minute decisions.

Where to focus next

• Prioritize reputation management. 75% of consumers read at least four reviews before making a decision.
• Optimize local listings with clear, mobile-friendly CTAs like “Book Now” or “Check Availability.”
• Refresh photos and amenities to appeal to high-intent travelers comparing options quickly.
• Highlight premium experiences. With upper-tier properties outperforming, showcasing upgrades, packages, and differentiators pays off.

Restaurants

• Total Q4 2025 views: +17.8% QoQ, -13.2% YoY
• Total Q4 2025 clicks: -11.5% QoQ, -14.6% YoY
• Food orders per location: -74.5% QoQ, -82.5% YoY
• Food menu clicks per location: -15.0% QoQ, -21.5% YoY

Restaurant visibility rebounded from Q3, with views rising nearly 18% QoQ. Both Search (+19.9%) and Maps (+15.5%) saw healthy growth, but that didn’t translate to clicks, which fell  by 11.5%. The restaurant sector saw the largest drop in views per location (-31.7%), marking the second year of decline after a -18.1% drop from 2023 to 2024. The YoY losses this past quarter spanned both Maps (-40.1%) and Search (-22.5%) views.   

The broader industry context mirrors this tension. According to Revenue Management Solutions, restaurant traffic slowed in Q4 as consumers grew more cautious with discretionary spending. Quick service and fast casual brands leaned heavily on value-driven promotions, while giants like McDonald’s focused on restoring perceived value. 

Casual dining was a relative bright spot, with chains like Darden exceeding revenue expectations (+7.3% YoY), especially in stronghold regions like Florida and the Southwest.

What it all means: diners are still searching, but price sensitivity is high and expectations are sharper. AI plays a role now, as in other sectors where diners are searching for information such as hours or menus and getting an AI response that answers the question, there’s no need for further action. Restaurants are competing not just on visibility, but on clarity, trust, and value — especially in that crucial moment between search and sale — and success may not show up as a click.

Where to focus next

• Surface your strongest value cues — portions, pricing, quality, and limited-time offers — early in local listings, and often in Google Posts, social media, and on landing and specialty pages.
• Keep menus fresh and accurate to encourage conversions when visibility spikes.
• Monitor food order CTAs and platforms, testing new messaging and offers to revive performance.
• Respond to reviews quickly to build trust and edge out nearby competitors.
• Expand your understanding of the path to local visibility and discovery in AI-driven search.

Multi-family residential

• Total Q4 2025 views: -15.3% QoQ, +8.5% YoY
• Total Q4 2025 clicks: -16.2% QoQ, -17.6% YoY

After a strong Q3, visibility for multi-family listings softened in Q4, down more than 15% quarter-over-quarter. Clicks declined even further (–16.2% QoQ), with sharper drops in website clicks (–24.4%) and phone calls (–20.4%). Search views fell –16.1%, and even driving direction clicks—often a sign of strong intent—slipped nearly 10%.

The broader market followed a similar arc. Multifamily demand eased in Q4, as expected, but 2025 still closed strong with 355,000 units absorbed nationally — the third-highest total in 25 years. 

Vacancy rates held stable near 6.5%, though advertised rents flattened, dipping 0.9% in Q4. Notably, construction starts hit decade lows, signaling less new inventory coming online in 2026 and potentially tighter competition for qualified renters.

For multi-family marketers, the message is clear: visibility alone won’t drive leases. Search behavior is active, but renters are comparing more, acting slower, and seeking clear value — especially when price and supply remain steady.

Where to focus next

• Refresh listings frequently with updated pricing, availability, amenities, and photos to stay competitive.
• Highlight value differentiators like move-in incentives, pet policies, or flexible lease terms early in the listing.
• Track direction and website clicks by property to spot high-interest communities and optimize digital ad spend.
• Support each property with a well-optimized local page, especially in regions with slower lease-up activity.
• Look beyond Google; make sure you’re optimizing for the Apple ecosystem.

Rethinking local visibility in 2025 and beyond

Q4 2025 reinforced a fundamental shift in local discovery. Visibility is no longer a guarantee of engagement, and clicks are no longer the sole measure of success. As Google’s UI shifts and AI-driven results reshape the search journey, brands that rely on outdated metrics or incomplete listings are getting left behind.

But the opportunity is still huge. Consumers are searching daily. They’re still showing up, still clicking — just more selectively, and with higher expectations.

The brands winning today are doing more with less: optimizing every listing, testing every CTA, and delivering consistent, credible experiences across every touchpoint. 

AI and answer engines are raising the bar. For marketers willing to adapt, they’re also expanding the path to conversion. Now’s the time to rethink your local presence from the ground up.

Want to know where you stand? A local audit can uncover hidden gaps, growth opportunities, and the opportunities that matter most in an AI-driven search landscape.

The 2025 top local search trends tell a clear story: search has changed. Not slowly, not subtly, but it’s no exaggeration to say this past year has transformed the way people search for and find information at the local level. In just one year, the way people find local information has completely shifted. AI Overviews and machine-generated summaries now drive local discovery, with platforms deciding which businesses appear for users.

And with 84% of consumers searching for local businesses daily, as well as 73% searching multiple times a day, that shift carries massive stakes for every brand with a physical footprint.

The old mindset of optimizing to rank won’t carry multi-location brands into 2026. Ranking still matters. But what matters more now is showing up in the answer, not just the results.

What 2025 taught us about local search

The signals that drive local visibility didn’t vanish; they just changed rank. In 2025, the spotlight shifted toward trust, intent, and AI-readable signals. The data proves it.

Here’s what surfaced in the 2026 Whitespark Local Search Ranking Factors report:

• Citations are making a comeback. Three of the top five AI search visibility factors are citation-based. These include mentions on expert-curated “best of” lists, unstructured mentions in news or blogs, and overall volume of mentions across the web. LLMs are now digging deep into third-tier directories for information, as well. That makes citation accuracy critical not just for major listings like Yelp and Google, but also for second- and third-tier aggregators (e.g. Hot Frog).
• Review signals are more influential than ever. High Google ratings ranked sixth for local pack visibility and first for conversion impact. Review recency, sentiment, and overall volume matter, as well. Reviews are now the second-most-important ranking factor for Local Services Ads.
• Dedicated pages for each service are essential. They ranked first for local organic rankings and second for AI visibility. This proves that content structure still matters across every search surface. Having dedicated pages for each service helps both search engines and LLMs understand the depth of products and services a local brand offers, improving visibility in both local search results and AI chatbots.
• Keywords in Google Business Profile services carry real weight. This detail emerged as a top-ranking factor for local visibility, confirming what many brands have long suspected.
• Behavioral signals are gaining ground. User engagement matters. Metrics such as mobile clicks, dwell time, and click-through rates are on the rise. One expert noted that locations experiencing higher-than-usual activity often see a boost in rankings in real time.
• Google Business Profile optimization still underpins visibility. Primary category, proximity, and keywords in the business name were the top local pack ranking factors. A new factor, “business is open at time of search,” ranked fifth and joined the top tier this year.

AI models now prioritize confidence, not clicks

More than tweaking the algorithm, these shifts are redefining how visibility works. AI isn’t scanning for keywords. It’s scanning for confidence: accurate data, timely updates, and content that makes sense in context. Consumers feel that shift, too; 60% click AI-generated overviews at least sometimes, even when the summary gives them most of what they need without leaving the results page.

Local discovery is now shaped by how machines read trust. That trust shows up in more places; in review text pulled into AI Overviews, Business Profile features like “What’s Happening,” and schema-rich pages that confirm your relevance without a click.

If 2025 taught us anything, it’s that visibility lives in the answer layer. And inclusion, not just position, is what moves people to act.

Local search engines follow your customer reviews and citations

And yet, inclusion doesn’t happen in a vacuum. Behind every AI-generated summary, map pin, or booking button is a trail of data in reviews, structured markup, categories, content, and visuals. It’s all working in sync to tell a clear story. Customer behavior reinforces this: 75% of consumers read at least four reviews before making a decision, and 21% now say that how brands respond to those reviews influences confidence.

In 2025, we saw Google lean harder on review text and schema markup, AI systems start pulling answers straight from Reddit threads and forums, and social platforms step up as local search engines in their own right.

What brands need next to win local search visibility

Winning visibility in 2026 won’t come from chasing the algorithm. It’ll come from creating clarity across every local touchpoint and reinforcing it with signals AI can trust. Each element of your digital presence, from listings to landing pages, plays a role in earning inclusion.

Listings: Structure your data for full-text search and AI tools

Google Maps, Apple Maps, and local search engines rely on accurate, consistent signals to fuel their results. AI tools (especially custom Assistants and autonomous agents) can’t afford to guess. They need verified data at the source. And with 68% of consumers trusting Google most for accurate business information, your listings are the first proof point.

Your Google Business Profile isn’t just a listing, though; it’s a structured data node. Fill in every detail, from hours and categories to services and service areas. Align those signals with trusted local citations, industry niche directories, and full-text search data from your business websites. And don’t stop at accuracy… stay active. Respond to Q&A, publish updates, and treat your listing like a live storefront.

Reviews: Help language models read what makes you trustworthy

Today’s AI models don’t just count customer reviews, they interpret them. AI search systems parse review text to extract sentiment, context, and recurring themes. That language feeds directly into AI Overviews and chat assistant responses.

That means volume matters, but voice matters more. Encourage reviews across platforms, respond with natural language, and highlight keywords that reinforce your core services. A steady stream of authentic customer feedback tells AI that your business is active, trustworthy, and worth recommending, whether in search or inside an assistant.

Pages: Align your local pages with machine learning expectations

Machine learning models can now evaluate your business websites the way a human would, but faster and with stricter rules. They expect clear structure, accurate markup, and seamless alignment between on-page content and your Google Business Profile.

Each location page should act as a confidence checkpoint: relevant keywords, local context, and schema that reinforces the who, what, and where of your business.

Use FAQ markup, embed customer reviews, and connect the dots between your structured data and your social media channels. AI-powered queries are looking for clarity, not keyword tricks, and content that’s built to help, not just rank.

Analytics: Understand how AI-powered queries reflect brand performance

Clicks are no longer the full picture. AI search experiences surface results without sending users to your site. Success now shows up in customer actions — tap-to-call, direction requests, profile views, and conversions — across AI interfaces.

Accuracy plays a major role here: 53% of consumers won’t visit a business with incorrect listing information, and 59% expect a response within 24 hours when they reach out. To track this, you need visibility across both traditional analytics and engagement signals from Google Business Profile, Google Maps, and other entry points. Rio’s approach connects location-level data with real-world actions, helping enterprise brands see how presence, perception, and precision work together to drive results.

The path forward: Train your brand for AI search

Machine learning, language models, and AI search aren’t going to slow down, and neither can you. As discovery evolves, your visibility depends on how well your brand speaks the language of both machines and people. That means training your data to be consistent, training your team to stay responsive, and training your content to surface when it matters most.

It also means thinking beyond one platform. Local search engines, social media channels, and autonomous agents are learning from the same data sources: your customer reviews, local citations, business websites, Q&A content, and every structured signal you send out into the world.

For enterprise marketers, the mission is clear: Turn every search result into a source of truth.

Turn every location into a learning loop. Turn every signal into a story your customers and AI models can trust.

This isn’t a set-it-and-forget-it task; it’s a new discipline, where precision, consistency, and experience stack together to make your brand visible, valuable, and chosen.

Get the must-read guide

Want to go deeper? The 2025 Top Local Search Trends and insights featured in the full Local Search Q4 2025: Winning Visibility in an AI-Driven World guide is built to help you take the next step whether you’re rethinking your content, revamping listings, or rebuilding your data model from the ground up.

Get the guide here.

The local search landscape is evolving faster than ever. Algorithm updates cause mass disruption, AI assistants multiply, and consumers expect instant, accurate answers across Google, Gemini, ChatGPT, and Perplexity. Yet one truth remains: when people search nearby, Google’s Local Pack and Business Profiles still drive discovery and dollars.

That’s where data makes the difference. Big data now powers how brands see, shape, and scale their local presence. Behind every ranking boost or map pin is a data story, and these signals reveal what’s working, what’s not, and where to focus next.

This isn’t guesswork or hype. It’s data-driven decision-making rooted in real-world results, and it’s echoed by industry experts who track the ever-changing search terrain.

In this breakdown, we’ll show what’s moving the needle, from the reviews that fuel trust, to the backlinks that build authority, to the structured data that helps AI understand your business.

Why local SEO still matters in an AI-first search world

AI may be rewriting the rules of discovery, but it hasn’t rewritten human behavior. When consumers need a dentist, a coffee shop, or a plumber nearby, they still turn to traditional search platforms most often. Even as voice assistants reshape how people ask questions, Google remains the top engine of trust, 68% of respondents in our latest Local Consumer Behavior Survey said they expect Google to provide the most accurate local information.

It’s still the place where people go for business hours, phone numbers, directions, and reviews they can act on. It’s where the digital path meets the physical doorstep.

The difference now? AI has raised the stakes. Behind every “near me” search is interpreted through layers of artificial intelligence and natural language processing that decode intent in milliseconds. Google’s algorithms don’t just crawl pages anymore; they understand context, tone, and customer interactions.

The brands that connect the dots between search data, consumer patterns, and on-site engagement can see the full story: what’s working, what’s missing, and where to focus next. Data-driven insight reveals not just what’s ranking, but why and how to replicate that success across every location.

The core data signals that shape local visibility

Local SEO may be evolving, but its foundation still rests on a handful of core signals. These are the measurable data points—reviews, links, structure, and accuracy—that tell Google (and now AI assistants) who you are, where you operate, and why you’re relevant. Let’s break down the data signals driving real-world results in 2025 and beyond.

Reviews: The most powerful and accessible local signal

Reviews are the heartbeat of local SEO. This is the public proof that real people have real experiences with your brand, and they carry more weight in Google’s Local Pack than almost any other factor. The data backs it up: more reviews consistently mean better visibility, irrespective of industry.

Volume beats perfection. A steady stream of authentic, genuine feedback tells Google your business is active and trusted. Star ratings still matter, but consistency and credibility matter more.

Smart brands don’t just collect reviews; they connect and activate them. Each review feeds data analytics, uncovering patterns in customer behavior and data quality that help team members refine both service and search strategy.

Tips that drive performance

• Prioritize review volume over star rating. Aim for steady growth, not flawless scores.
• Encourage reviews across platforms including Google, Yelp, Facebook, and niche industry platforms.
• Respond with care and clarity. Use keyword-rich, natural language that reinforces location and services.
• Cross-promote in your responses. Turn a “thank you” into a subtle nudge toward another product or service.
• Add review schema on landing pages to strengthen visibility in AI summaries.
• Keep messaging and visuals aligned across your social channels. Consistency builds trust with both people and algorithms.

Reviews aren’t just feedback, but a valuable form of two-way communication. Each one shapes how your brand is seen, understood, and surfaced in local search.

Backlinks: Still one of the strongest ranking signals

Despite endless predictions of their demise, backlinks are still the backbone of authority. They demonstrate authority, connection, and trust. Even in 2025, and even with AI parsing context and intent, links remain one of the clearest indicators of credibility in local search.

But not all backlinks are created equal. Google’s algorithm has become smarter at distinguishing meaningful relationships from empty exchanges. The best-performing links today come from authentic local connections and community relevance.

What’s working right now

• Local press mentions: Earn coverage from newspapers, radio stations, or digital magazines in your area. These links build both awareness and authority.
• Community sponsorships: Partner with local charities, sports teams, or events—and make sure your link appears on their official site. It signals genuine local engagement.
• Regional guest posts: Contribute to nearby business blogs or Chambers of Commerce. These placements carry local weight and reach potential customers directly.
• Directories and citations: Secure accurate, up-to-date listings in trusted local and niche directories. They may not be glamorous, but they strengthen your digital foundation.
• Link to location landing pages: Don’t funnel everything to the homepage. Each location page deserves backlinks that reflect its specific geography and service focus.

Pro tip: Local SEO success often mirrors overall domain authority. Treat your link-building strategy as a long-term trust exercise, not a checklist. Build real relationships, not just backlinks, and your rankings will follow naturally.

Structured data: Make your content machine-readable

Search engines, and now AI assistants, don’t just read your content, they interpret it. Structured data is how you help them understand exactly what your business offers, where you operate, and why you’re relevant. It’s the connection between your website, your Google Business Profile, and the evolving web of AI-driven discovery.

When your structured data is clean and complete, AI can surface your business confidently in voice, map, and conversational results. Without it, your content becomes harder for machines to categorize, and easier for competitors to outrank.

Schema types that matter most

• LocalBusiness: Anchors your NAP (name, address, phone) and location.
• Service and Product: Describe what you offer in detail, including pricing and availability.
• Review: Connects ratings and feedback directly to your listings and landing pages.
• FAQ: Feeds AI engines ready-made answers for conversational queries.
• ImageObject: Gives context to visuals, helping them appear in AI summaries and rich results.
• Organization: ties your brand identity together across platforms.

Implementation tips that matter

• Match your schema to on-page content and your Google Business Profile. Accuracy builds trust with both searchers and systems.
• Add “sameAs” links for your social accounts, citations, and Wikidata entries to strengthen your brand graph.
• Clarify the essentials—services, pricing, hours, coordinates, and reviews—so every data point aligns.
• Audit regularly. Even small mismatches can break context for AI models and cost you visibility.

Structured data is your translator in an AI-first search world. It turns plain text into something machines can understand, and something humans can find.

Images: A growing influence in local rankings and engagement

Visuals have become a powerful trust signal in local SEO. Businesses with robust, high-quality images tend to appear more often (and higher) in Google’s Local Pack. Why? Because visuals help both people and AI understand what you offer at a glance.

The right image can tell a data story of its own, signal product quality, reflect strong product design, or shows customers what to expect before they ever walk through the door.

Best practices for visual performance

• Upload high-quality, descriptive images to your Google Business Profile and landing pages. Each photo should feel purposeful, showing your people, place, or product clearly.
• Use alt text wisely. Include natural mentions of services, locations, or product types to give search engines and AI more context.
• Keep visuals consistent. Your GBP, website, and social feeds should tell the same visual story. Disjointed imagery confuses both users and algorithms.
• Highlight what matters most. Include team photos, your storefront or office, core products, and real customer experiences.
• Show collaboration. Capture moments that feature your sales team in action, organized displays, or behind-the-scenes shots of inventory management to humanize your brand.

AI relies on visuals to fill in gaps text can’t. Every photo, caption, and alt tag contributes to how your business is represented in summaries, snippets, and search results. In an image-led world, your visuals aren’t just creative assets, they’re your brand’s ambassadors.

GBP categories: Choose wisely for maximum relevance

Your Google Business Profile category is one of the most direct signals you can send to Google about what your business actually does. Get it right, and you’ll show up in the right searches. Get it wrong—or ignore it—and even the best content, reviews, or backlinks can only do so much.

Studies show that profiles with multiple relevant categories tend to rank better across most industries, with few outliers. The key is precision, not volume. Each category you select should reinforce your brand’s expertise, not dilute it.

Tips for stronger category performance

• Pick a single, precise primary category that defines your core service.
• Add all relevant secondary categories. Think of these as context builders—use them to capture your full range of offerings.
• Avoid irrelevant or excessive categories. Extra categories don’t boost reach; they confuse Google and customers alike.
• Spy smart. Use tools like GMBSpy or competitor audits to see which categories top performers are using, then refine accordingly.

Categories tell Google exactly where you belong in the local ecosystem. They’re a shorthand for relevance; a way for AI and algorithms to connect your business to intent. The more accurately you define your space, the more confidently Google can recommend you when it counts.

Q&A: Underused, high-impact Local SEO lever

The Q&A section on your Google Business Profile is one of the most overlooked and yet purely powerful tools in local SEO. When used intentionally, it becomes a mini knowledge base that answers real customer questions right where decisions happen in search.

More Q&A activity correlates with higher visibility and better engagement. It signals to Google that your business is active, responsive, and relevant. And it signals to customers that you’re listening.

Tips to turn Q&A into a ranking advantage

• Seed your own Q&As: Add common questions customers ask on calls, in reviews, or on-site, then answer them directly. It’s proactive SEO in action.
• Keep answers clear, keyword-aligned, and conversational: Write like a human first, but include natural mentions of services, products, and locations.
• Monitor and respond quickly: Timely replies show engagement to both users and search engines. Don’t let questions linger unanswered.
• Repurpose Q&A content: Reuse your best entries as on-page FAQ schema to strengthen your structured data and capture more long-tail queries.

Q&A shouldn’t be treated like filler or an afterthought. It bridges curiosity and confidence, turning common questions into conversion paths and improving your visibility along the way.

The technical data layer: Small errors, big consequences

Even the smallest technical mistakes can quietly chip away at visibility, traffic, and trust. Broken links, inconsistent NAP data, and redirect chains all send mixed signals to Google’s crawlers trying to verify your business.

Common culprits include 404s, 403s, 302s, and 301s hiding in your Google Business Profile links. These errors break the chain of relevance that connects your profile to your landing pages.

Another frequent issue is inconsistent NAP (name, address, phone) data across your website, listings, and citations. To Google, those mismatches look like uncertainty.

The good news is that these are fixable issues with measurable impact.

Fixes that keep your data clean and your rankings strong

• Audit your links regularly. Check every GBP-linked URL for redirects, broken pages, and outdated tracking codes.
• Add UTM parameters to your GBP links for clear attribution in analytics. Profiles with tracking parameters often perform better.
• Ensure consistent NAP data across your site, listings, and third-party directories. One version of the truth—everywhere.
• Use HTTPS and fast-loading, mobile-friendly pages. Technical performance directly influences visibility and user trust.
• Match GBP categories and keywords with the content on your linked pages to reinforce topical relevance.

Technical accuracy is the quiet hero of local SEO. It doesn’t shout for attention but when it’s off, your results suffer. And when it’s right, everything else performs better.

Additional ranking trends to watch

Local SEO in 2025 is more dynamic and data-driven than ever. AI has rewritten how search engines evaluate credibility, context, and intent. But even with all of this evolution and change, the fundamentals haven’t disappeared. Here’s what’s shaping visibility right now.

AI’s new influence on local visibility

Google’s AI Overviews are changing the flow of traffic, delivering fewer clicks, but higher-quality ones. Searchers who reach your site through these summaries are more informed, more intentional, and closer to conversion.

AI rewards websites that are structured, contextual, and trustworthy. The stronger your data foundation of clear schema, consistent NAP, authentic reviews, the more confidently AI systems will surface your business in results.

Search success now hinges on experience. Pages that earn clicks, keep users engaged through useful content, and lead to real actions such as calls, directions, and bookings, signal genuine value.

Reddit and social signals are feeding the algorithm

Google is pulling structured answers directly from Reddit threads, forums, and Q&A platforms. These sources help AI models learn what real customers ask and how they describe experiences.

Social media activity is also gaining weight. Coupons, local events, trending products, and authentic interactions send live relevance signals. Your brand’s social pulse now influences how—and how often—you appear in search.

The rank radius reality check

No matter how optimized your profile, geography still governs visibility. Most businesses don’t rank far outside their physical footprint. Instead of chasing unrealistic distances, use GBP insights and local rank tracking tools to measure where you truly compete. Then, build density (more reviews, backlinks, and engagement) inside that core radius.

AI is elevating what matters most: context, clarity, and credibility. The brands that thrive aren’t chasing every trend, they’re maintaining precision, consistency, and a human touch in a machine-led world.

Local SEO in 2025 is a blend of fundamentals and AI-readiness

The rules of local search may keep shifting, but the winning formula hasn’t changed. It’s grown up a little, but the foundations still matter most: strong reviews, credible backlinks, accurate structured data, and active Q&A. These are the cornerstones that help your business get found, understood, and trusted.

What’s new is how those signals interact with AI. Search engines are now storytellers, pulling from every digital cue, from your visuals and social activity to your tone of voice and reviews volume, to decide how your brand appears in answers and summaries. Clean data and technical precision aren’t nice-to-haves anymore; they’re the ticket to entry.

Marketers who lead in 2025 will be the ones who treat local SEO as both art and architecture. Build trust layer by layer and strengthen context at every touchpoint. Make your content readable and understandable not just by people, but by the machines that help people find you.

For years, local search success meant one thing: rank high in search results and earn the coveted click.

Today, search has evolved—and so have the opportunities. AI-driven engines are changing what visibility looks like, creating new ways for customers to discover and connect with brands. Between AI summaries, map packs, design tweaks, and ongoing core updates, Google continues to raise the bar on what it takes to stand out.

In short: visibility isn’t vanishing. It’s transforming, as evidenced in local search behavior trends in Q3 2025 analysis.

The story behind the numbers

In mid-2025, a 23-day Google reporting glitch disrupted visibility data across nearly every industry. From June 24 to July 17, impressions appeared to plummet—temporarily skewing June and July year-over-year (YoY) and month-over-month (MoM) metrics.

Beyond the anomaly, however, a more meaningful trend emerged: brands are adapting faster to an increasingly volatile, AI-driven search landscape.

As Google experiments with new layouts and call-to-action (CTA) formats, user engagement patterns are shifting. Some listings now show fewer—or entirely different—buttons, altering how users take action. Despite these interface changes, direction requests have remained steady, signaling continued high-intent engagement in moments that matter most.

Customers haven’t disappeared. They’re just finding you differently.

Each quarter, Rio SEO analyzes Google Business Profile (GBP) performance across eight industries and over 180,000 business locations to help brands benchmark performance, identify shifts, and prioritize next steps. Because showing up isn’t the goal anymore; showing up ready to convert is.

Use our analysis to benchmark your results, spot emerging patterns, and guide smarter optimization in the months ahead.

Year-over-year local search trends

Q3 2025 visibility took a dive, and not just because of market shifts. Between June 24 and July 17, that Google reporting issue impacted search views across all clients. Search-heavy industries like retail and staffing saw the biggest drops. And that’s just one layer of disruption.

Since July, Google has also rolled out multiple algorithm updates and UI tests, including mobile button changes that impact how easily users can call or click through from listings. Some users now see only a single action button — or none at all — unless they tap into the full profile.

All of that shows up in the numbers:

• Retail views dropped –12.2% YoY, despite a +4.3% gain in clicks
• Restaurants saw –36.3% fewer views and –6.7% fewer clicks
• Financial services dropped –24.9% in views and -5.2% in clicks
• Business services also took a big hit in visibility (–23%)

The message is clear: impressions are unreliable. Actions tell the real story. Clicks, calls, and direction requests remain strong across most verticals. The data points to one trend with teeth: as listings get less visible, the ones that convert rise to the top.

Healthcare continues to grow YoY in both visibility (+0.6%) and engagement (+6.6%). And multi-family residential saw a lift in views (+14.5%) but a decline in clicks (–9.2%), suggesting more exposure but weaker follow-through. 

If you’re tracking visibility alone, you’re missing the bigger picture: intent-driven actions are what define local success now.

Quarter-over-quarter local search trends

Zooming in on Q3 performance, most verticals weathered the reporting disruption with steady or improved engagement, despite lower visibility.

• Retail: Views down –3.8%, but clicks up +3.0%
• Hospitality: Views fell slightly by -3.4%, while clicks rose +1.1%
• Restaurants: Views fell by –10.1% and clicks fell by -3.7% 
• Multi-family: Views were up +4.1%%, clicks were down slightly -5.9%
• Service businesses: Small drop in views (–1.4%), big jump in clicks +7.2%
• Healthcare: Flat nearly across the board, a signal of stability, while clicks grew by 6.6%
• Financial services: Views dropped –5.1%, clicks rose +2.1%

The reporting issue complicates visibility comparisons, but the broader pattern is clear: industries leaning into conversion-focused listings and high-intent CTAs are outperforming.

In 2025, your local listing has to do more with less: less real estate, fewer buttons, and fewer chances to make an impression. The payoff for optimizing for action is clearer than ever.

Retail

• Total Q3 2025 views: –3.8% QoQ, –12.2% YoY
• Total Q3 2025 clicks: +3.0% QoQ, +4.3% YoY

Retail faced another quarter of declining visibility, but engagement stayed resilient. Views fell modestly, yet clicks climbed across both timeframes—proof that intent is sharper, even as exposure narrows.

That mirrors what we’re seeing in the broader U.S. retail landscape: total consumer demand remains steady, but it’s more selective. Shoppers are price-sensitive, store format matters. and when they search, they search with purpose.

Map views rose slightly (+1.2%) while Search views dropped (–7.2%), mirroring the broader trend of AI summaries and interactive modules replacing traditional listings. Website clicks and phone calls dipped slightly (–3.9% and –3.0%, respectively), suggesting shoppers are relying more on listings themselves to decide.

Consumers are shopping with purpose, not impulse. Direction requests rose +9.2% QoQ and +18.5% YoY—evidence that people are still showing up, just through fewer, higher-intent entry points.
Collier projects 3.5–4.0% holiday sales growth and $1.7T in total spending, with 91% of consumers planning to shop both in-store and online. Retailers that emphasize clarity, convenience, and conversion-ready listings will be best positioned to capture this hybrid demand.

Total actions on listings climbed +11.3% from Q1 and beat last year’s volume by over 4%. Driving direction clicks saw the biggest gain, up +21.6% quarter-over-quarter and +14.4% year-over-year, a strong signal of in-person shopping intent.

Website clicks also rose (+6.1% QoQ), while phone calls dipped slightly (-1.4% QoQ), suggesting that shoppers may be relying more on self-service information available on the listing or website.

Engagement is back, even if views haven’t fully recovered. Not all impressions are created equal. Retailers saw fewer views overall compared to last year, but more meaningful engagement from the customers who did see them.

Where to focus next

• Watch the balance between Search and Maps views to guide content strategy.
• Activate local product feeds and inventory listings to surface real-time availability—especially critical for retail brands looking to capture “near me” and “in stock” searches.
• Identify top-performing stores and replicate what’s working.
• Keep listings fresh, including hours, categories, images, and fulfillment options.
• Maintain a strong reputation management program across all verticals; positive reviews and timely responses remain key ranking and engagement drivers within AI Overviews (AIOs).
• Drive fresh reviews and respond consistently to build trust.
• Support GBP with optimized local pages for key offerings.

Financial services

• Total Q3 2025 views: –4.9% QoQ, –24.9% YoY
• Total Q3 2025 clicks: +2.2% QoQ, -5.2% YoY

In Q3, financial services brands took a visibility hit but more than made up for it with a surge in engagement, mirroring the sector’s strong market performance.

Views dropped –24.9% YoY and –4.9% from Q2, making financial services one of the most visibility-impacted verticals this quarter. That YoY drop reflects both real shifts in Google’s SERPs and the June-July reporting gap, which skewed Search views heavily downward. Search views fell –9.2%, while Map views were up 2.4%. This doesn’t come as too much of a surprise as this industry tends to outperform in Q2 due to tax season.

But engagement told a different story: Clicks rose slightly +2.2% QoQ, a clear sign that users are acting fast when they find what they need. Direction requests were up +4.5%, and website clicks rose +2.0% — both modest but meaningful gains in a quarter where many industries saw flat or declining web traffic.

Phone calls dipped –4.1% QoQ but remain relatively stable compared to the steep YoY drop in views (–21%). That’s likely tied to Google’s recent mobile UI experiments, where users sometimes see only one CTA button (often directions) unless they tap into the listing.

Despite shrinking visibility, financial services listings are converting better. That speaks to stronger intent, clearer CTAs, and more users moving quickly once they find the right location.

This engagement lift mirrors renewed market confidence: JPMorgan Chase reported $8.9B in trading revenue, Bank of America’s investment banking revenue jumped 43%, and Morgan Stanley’s equities trading grew 35%. That momentum likely translated into higher local intent and branch interactions.

Where to focus next

• Audit branch and office listings for hours, services, and appointment links—every detail matters.
• Track direction and website clicks by location to spot demand and optimize staffing.
• Test CTA visibility on mobile; if “Call” and “Website” buttons aren’t showing, adjust layout or content.
• Use GBP attributes like “online appointments” or “ATM available” to boost relevance.
• Focus less on volume, and more on conversion: what users do > how many see you.
• Create professional listings for key staff (like loan officers, agents, or advisors) if your brand doesn’t already have them.

Service businesses

• Total Q3 2025 views: –3.5% QoQ, –28.8% YoY
• Total Q3 2025 clicks: –3.3% QoQ, –6.5% YoY

Service businesses took another hit in Q3 — especially in visibility — but engagement held better than expected.

Views dropped –3.5% from last quarter and nearly –28.8% year-over-year. That’s one of the steepest visibility losses across any vertical this quarter, driven by falling search views (–6.8% QoQ, –23.0% YoY) and mobile layout changes that continue to squeeze local listings.

Clicks were down –3.3% QoQ and –6.5% YoY. It’s not a collapse, but a clear slowdown after a strong Q2 rebound. Phone clicks dropped sharply (–12.6% QoQ, –29.9% YoY), echoing the broader trend in which mobile users no longer see call buttons by default. Website clicks fell more modestly (–4.4% QoQ, –5.2% YoY), while direction requests rose slightly (+2.0% QoQ, +4.1% YoY).

The takeaway: With shrinking visibility and fewer interaction points, clarity and credibility are now differentiators.

Where to focus next

• Prioritize review quality and response time to reinforce trust.
• Keep listings fresh with current services, hours, and contact info.
• Highlight high-converting branches and align campaigns accordingly.
• Use website and direction click trends to track engagement hotspots.
• Monitor Map vs. Search view shifts and adapt visibility strategy.
• Add clear CTAs or chat features (like “Book Now,” “Call,” or “Chat with an Expert”) to create a seamless experience for high-intent customers ready to take action.

Healthcare

• Total Q3 2025 views: +0.1% QoQ, +0.6% YoY
• Total Q3 2025 clicks: +0.8% QoQ, +6.6% YoY

Healthcare brands stayed steady again in Q3, and that’s saying something. While most verticals wrestled with visibility drops and UI disruption, healthcare saw near-flat performance in views (+0.1% QoQ, +0.6% YoY) and a healthy rise in engagement (+0.8% QoQ, +6.6% YoY). That stability stands out in a quarter full of shakeups.

Search views slipped slightly (–0.6% QoQ), but Map views rose (+2.2%), helping offset the difference. Driving direction clicks jumped +7.7% QoQ and +19.4% YoY, a strong indicator that patients are still showing up, even if they’re starting their journey from fewer visible paths.

Phone and website clicks dropped modestly (–3.9% and –4.1% QoQ), but direction requests and total engagement made up the difference. It points to a shift in how patients are acting: fewer distractions, faster decisions.

That tracks with broader healthcare market dynamics. In Q3, the sector faced continued workforce constraints, rising outpatient demand, and growing reliance on temporary replacements to fill care gaps. Outpatient visits are projected to exceed 6 billion annually by 2035. It’s part of a sweeping shift away from inpatient care.

But access remains uneven. Roughly one-third of rural hospitals face financial risk, and more than 300 are at immediate risk of closure. That disparity affects how — and if — consumers find care.

Layer on top of that a persistent trust gap. Post-COVID skepticism runs deep, with patients wary of insurers, pharma brands, and even providers. That means accuracy in your listings isn’t just helpful, it’s foundational. If patients can’t trust what they see, they’ll go somewhere else.

Where to focus next

• Prioritize trust-building by making your listings complete, consistent, and up to date.
• Lean into both Google and Apple Maps, as strong Map visibility correlates with high-intent action.
• Highlight access points such as outpatient locations, hours, and scheduling links.
• Optimize for the moment with fewer clicks, more clarity, and faster action.
• Watch rural performance closely if you operate in mixed geographies.

Hospitality

• Total Q3 2025 views: –3.4% QoQ, –13.2% YoY
• Total Q3 2025 clicks: +1.1% QoQ, +4.2% YoY

Hospitality brands The hospitality sector entered Q3 2025 in recalibration mode. After a year of post-pandemic travel recovery and elevated leisure demand, the market showed signs of softening. Lower international travel, rising operational costs, and mixed economic signals cooled earlier momentum. RevPAR growth slowed as forecasted, while occupancy hovered in the 62–63% range, just as PwC predicted earlier in the year.

That tempered demand showed up in local search, where total views dropped –3.4% from Q2 and –13.2% YoY. Organic visibility remained in flux, with Search views down –9.4% QoQ and –18.6% YoY,  among the sharpest declines in any vertical. Map views, however, rose +3.5% QoQ, suggesting users are still navigating to listings but are doing so with more intent and less browsing.

Total engagement tells a different story. Clicks climbed +1.1% QoQ and +4.2% YoY, driven by stronger performance across direction clicks (+4.1% QoQ, +12.7% YoY). That lines up with steady domestic leisure travel and the continued shift toward last-minute, mobile-led decision-making.

Website clicks dropped –5.7% QoQ, and phone calls dipped slightly (–0.4%), reflecting the mobile UI tests seen across Google and a growing preference for in-platform decision-making over outbound clicks.

Notably, direction clicks reached their highest levels since Q3 2024, signaling real-world foot traffic remains active, even as traditional visibility metrics decline.

Where to focus next

• Prioritize Maps visibility and accuracy, including Google and Apple Maps, for last-minute travelers.
• Ensure listings support direct bookings and highlight real-time availability.
• Track Search vs. Map performance, and shift your strategy accordingly.
• Audit mobile SERP appearance to ensure CTA buttons are visible and functional.
• Build in flexibility: travelers are still booking, just closer to arrival.

Restaurants

• Total Q3 2025 views: –10.1% QoQ, –36.3% YoY
• Total Q3 2025 clicks: –3.7% QoQ, –6.7% YoY
• Food orders per location: –10.4% QoQ, –46.5% YoY
• Food menu clicks per location: -11.2% QoQ, –16.8% YoY

Google introduced expanded GBP (Google Business Profile) layouts in Q3 2025, particularly for restaurant queries, which occupied more screen space and altered user interaction patterns.

Q3 was a quarter of hard tradeoffs for restaurant brands, and that’s reflected in our location data.

Local search visibility for restaurants dropped steeply (–10.1% QoQ and –36.3% YoY), the sharpest YoY decline of any vertical this quarter. But even with fewer views, user engagement held its ground: total clicks declined only –3.7% QoQ and –6.7% YoY, pointing to a consumer base that’s smaller, but still actively searching and converting — when the value is right.

That gap between visibility and action highlights a key market truth: perceived value is driving restaurant traffic right now.

According to Black Box Intelligence, guests aren’t just looking for low prices; they’re looking for a good deal. That means generous portions, quality taste, and a consistent experience that justifies the cost. Restaurants delivering on that equation are earning repeat visits and outperforming the pack.

The numbers reinforce that pattern:

• Food orders per location dropped sharply (–10.4% QoQ, –46.5% YoY), showing pressure on digital conversions and third-party platforms.
• Driving direction clicks rose +2.6% QoQ and +4.3% YoY, showing that even with visibility down, customers are still showing up in person when the perceived value is high.
• Meanwhile, phone calls and website clicks continued to decline (–15.4% and –9.3% QoQ, respectively), likely tied to changing UI layouts and more selective consumer behavior.

Restaurant visits are no longer automatic. Consumers are doing the math. Whether it’s casual dining’s recent outperformance, fast casual’s consistency, or quick service’s softness, one message cuts across the board: you win by making the choice easy, and worth it.

Where to focus next

• Highlight perceived value in listings, menus, and local ads, emphasizing portion size, food quality, speed, and atmosphere, not just price.
• Prioritize review generation by actively asking for reviews, especially from satisfied in-store guests.
• Keep menus and photos fresh. Rising menu click activity signals that more customers are checking listings before visiting, so make sure they like what they see.
• Watch direction clicks, as they continue to be a strong signal of real-world traffic, especially as phone calls and website clicks decline.
• Ask better questions in post-visit surveys, emails, or SMS, such as “Was the portion size worth the price?” or “How would you rate the quality of your meal for the cost?” These prompt value-based responses that help you refine messaging and operations.
• Test and track order CTAs: Food orders are down, so experiment with new language, delivery promos, and clearer paths to action.

Multi-family residential

• Total Q3 2025 views: +4.1% QoQ, +14.5% YoY
• Total Q3 2025 clicks: –5.9% QoQ, –9.2% YoY

Multi-family listings gained visibility in Q3, with views rising both quarter-over-quarter (+4.1%) and year-over-year (+14.5%). This continued a modest recovery in local exposure as renter demand held steady in most markets and stabilized vacancy levels signaled stronger competition for qualified tenants.

But despite more eyes on listings, clicks declined –5.9% QoQ and –9.2% YoY, a sign that interest isn’t always translating to action. Website clicks fell –15.5%, and phone inquiries dropped –9.2%, suggesting that some listings may be drawing casual browsers, not serious prospects. The one exception? Driving direction clicks, which climbed +3.5% — a potential indicator of localized, high-intent interest.

On the market side, vacancy rates held steady around 9% nationally, but stabilized vacancy (excluding new builds) rose slightly as concessions became more common to attract tenants. Rental rates continued their gradual upward trend, with Q3 showing modest growth (e.g., +1.3% YoY in Virginia). However, delivery slowdowns may begin to tighten inventory and drive stronger rent growth into 2026.

Together, the performance and market data point to a shift: interest is still there, but conversion hinges on relevance, clarity, and competitive differentiation. Simply being seen isn’t enough. Listings need to earn the next step.

Where to focus next

• Audit listings for clarity, making sure key information such as rent ranges, availability, lease terms, and pet policies is immediately visible and accurate.
• Refresh visual content with high-quality, up-to-date photos and virtual tours increase the odds of turning a view into a visit.
• Capture local intent by prioritizing local SEO, Google Business Profile (GBP) accuracy, and geo-targeted ads.
• Track and test CTA performance, and if web clicks are soft, revisit your calls to action and landing page experience.
• Lean into leasing incentives. If offering concessions, make them visible early in the search journey to stand out from competing properties.

Rethinking local visibility in 2025 and beyond

From shifting algorithms to changing consumer expectations, Q3 2025 made one thing clear: local visibility isn’t guaranteed, but action still is. The brands seeing growth aren’t just showing up… they’re showing up ready. That means listings built for conversion, content built for trust, and strategies built to adapt.

Want to know where you stand? Request your free local audit to uncover hidden gaps, growth opportunities, and tips tailored to your brand.

Your next customer might meet your brand in an AI summary, without ever visiting Google’s traditional results page.

Generative AI and natural language processing are reshaping how information moves from query to answer. Natural language models like Google AI Overviews, ChatGPT, and Perplexity don’t hand over a list of links. Instead, they deliver immediate answers, and those answers come from sources they trust, not just pages that rank.

The job of search engine optimization (SEO) has fundamentally changed. Now, artificial intelligence is the audience you need to persuade. And in local SEO, those decisions happen instantly, in the flow of a conversation or a voice query.

Winning visibility means covering three bases:

• Structured data that machines can interpret without guesswork
• Visuals that enrich AI summaries and build human trust
• Social proof that signals credibility from every angle

This is the SEO trifecta for the AI search era. It’s your ticket to showing up in search results that are no longer pages, but answers.

Why AI search is different from traditional SEO

AI search isn’t just a new interface, but an entirely new decision-maker. Instead of pointing people toward a list of pages, it decides which facts, quotes, and images to lift into the spotlight. That shift means the game isn’t “rank and hope.” It’s “be the source worth quoting.”

AI is answer-first, not link-first

In AI-driven search, visibility starts with the summary. Google’s Search Generative Experience, AI Overviews, ChatGPT, and other large language models don’t just show search results. They generate AI-generated summaries built from multiple trusted sources.

If your content isn’t structured, high-quality, and clear, it won’t make the cut. Structured data is now the foundation for getting surfaced in this answer-first world.

Search is now happening across more surfaces

Search engines aren’t just in browsers. Voice assistants in smart home devices, in-car systems, and mobile voice search are handling conversational queries every second. From “Where’s the closest auto repair?” to “Which bakery delivers today?”

AI agents need clean, consistent data to retrieve and present accurate answers in any context. That’s Local SEO with a generative AI twist: always on, always connected.

AI tools think like researchers

Large Language Models (LLMs) work more like investigative journalists than traditional crawlers. They scan Google Search results, niche sites, and public forums, looking for consensus, clarity, and confidence signals.

They identify and connect entities—people, products, places—through explicit, consistent information. This is where entity optimization and keyword research intersect.

Trust, context, and structure matter more than ever

In this new environment, it’s not enough to rank; your brand and its content must be the source AI trusts to quote.

That means unifying your structured data, sharpening your context, and making your trust signals impossible to overlook. In local SEO, the difference between being cited in an AI-generated summary and being left out is the difference between being discovered and being invisible.

The 3 pillars of AI search optimization

To earn that trust and surface in AI-driven search, you need to give machines exactly what they’re looking for, starting with structured data. This is the first pillar of the SEO trifecta, which we’ll dive into below.

Pillar 1: Structured data – Speak AI’s language or be ignored

Structured data is your translator between human language and machine logic. Without it, AI-powered search engines are left guessing what your page is about (and guessing rarely lands you in AI-driven results).

With structured semantic markup, you’re giving Google, large language models, and other AI tools a clear, machine-readable map of your content.

Why it matters: Structured data turns web content into information AI can interpret, categorize, and validate. Google Search, AI Overviews, and other AI-driven platforms use it to confirm context before they pull you into AI-generated summaries or Zero-click answers. If you want your business to be the “official” answer in a local search, your data has to be structured, consistent, and trustworthy.

Types to focus on:

• LocalBusiness – Include @context/@type and consistent NAP (Name, Address, Phone) data
• Product – Help AI identify what you sell and pair it with visuals, reviews, and pricing
• FAQ – Give AI ready-made Q&A for conversational queries
• Review – Surface ratings and testimonials as credibility signals
• Service – Define your offerings in detail
• Organization – Anchor your brand’s identity and attributes

Best practices:

• Match your schema to your Google Business Profile, on-page content, and other listings
• Validate using Google’s Rich Results Test and Schema.org tools
• Keep schema clean—no stuffing, no duplicating irrelevant properties
• Use sameAs to link to verified social profiles, Wikidata, or trusted citations

Pro tip: Think of structured data as your AI handshake. When your markup is accurate, consistent, and complete, you’re telling search engines, “You can quote me.” That’s how you move from just being indexed to being the source.

Pillar 2: Visuals – Let AI “see” your content

Search engines are no longer blind to imagery. Generative AI can now interpret what’s in a photo, connect it to surrounding copy, and decide if it supports the answer it’s building. When visuals are paired with structured data and strong textual context, they can tip the scales in your favor, ultimately boosting trust, improving AI summarization, and helping you own high-intent moments in AI-driven results.

Why it matters: In AI-driven search, image aren’t decorations, they’re data. A well-lit photo of a dish, a product shot with context, or a before-and-after transformation tells the algorithm, “This is real.” Google’s AI Overviews and other platforms often give enhanced treatment to content with relevant visuals. Done right, images deepen your content clusters, strengthen content depth, and add entity-rich phrasing opportunities in captions, alt text, and surrounding copy.

Use cases

• Product images for eCommerce – Multiple angles, contextual shots, lifestyle use cases
• Food images for restaurants and quick-service – Authentic, well-lit photos of menu items
• Service visuals for local businesses – Before-and-after transformations, team portraits, interior spaces
• Infographics – Break down complex topics and showcase thought leadership or industry-specific expertise visually

Best practices

• Use descriptive file names and alt text with relevant keywords
• Add image schema (ImageObject) to connect visuals to structured content
• Place images near related copy; AI pairs text and visual context when evaluating relevance
• Choose high-quality, fast-loading formats (WebP recommended for speed and clarity)

AI-specific tip: Think of every image as an entry point. When a visual is tied to the right entity-rich phrasing and industry-specific expertise, you’re signaling to AI: “This isn’t just pretty, it’s proof.” You get stronger placement in AI-generated summaries and a brand presence that’s hard to overlook.

Pillar 3: Social proof – Build trust signals AI can detect

Trust travels fast online, and AI is listening in. Every review, forum mention, and social post becomes a data point that tells AI engines whether you’re worth recommending. The more positive, consistent, and widespread those signals are, the more likely you are to be featured in AI-generated summaries instead of buried in the background.

Why it matters: AI doesn’t just scan your site, it watches what the internet says about you. LLMs draw from Google Search results, niche sites, and social chatter to measure credibility, popularity, and sentiment. In local SEO and local search, that means customer feedback and brand mentions can make or break whether you’re the business a voice search recommends.

Key types of social proof for AI

• Customer reviews and review responses – Especially on Google Business Profile and trusted third-party sites
• Mentions on Reddit, forums, and social media – Brand mentions in authentic, topic-relevant conversations
• Real-time signals – Coupons, event posts, or timely updates on social platforms that show you’re active and engaged

Best practices

• Respond to reviews with locally relevant keywords, service details, and genuinely helpful information
• Use responses to highlight service breadth: “Thanks! Did you know we also offer X?”
• Stay active on platforms AI engines track—Reddit, YouTube, LinkedIn, Instagram
• Mark up reviews and ratings with structured data so AI can verify and display them

Pro tip: When you answer questions in forums, use detail, clarity, and structure. AI agents like ChatGPT will often cite these posts directly if they read like a trustworthy source. The more you participate where your audience is already talking, the more entry points you create for AI to connect back to your brand.

Checklist to make your content AI-ready

Use this quick hit list to align your site with how search engines, AI chatbots, and voice assistants find, understand, and feature content.

• Add schema markup to all key pages: Prioritize Structured Data for LocalBusiness, Product, FAQ, Review, and Service types
• Mark up images: Use ImageObject plus descriptive alt text to strengthen visual context for AI and zero-click searches
• Keep data consistent: Match your Google Business Profile, website content, and schema down to every local keyword and detail
• Actively manage reviews: Monitor, respond with intent, and weave in relevant services and keywords
• Publish fresh content: Feed search intent with regular updates on social and your site to stay relevant in ranking algorithms
• Track performance: Use UTM codes and Google Search Console to see where Structured Data and schema are paying off
• Engage where questions happen: Reddit, Quora, and niche forums can influence AI chatbots and knowledge panel citations
• Clarify what you offer: Write clear, keyword-rich product and service descriptions that leave no doubt for AI or humans

Bonus: Where AI is pulling data from (and how to show up)

AI chatbots and search engines aren’t working from a single source. They pull from a web of signals including structured content, trusted citations, and active conversations. Knowing where they look helps you position your brand where it counts.

Find your data sources

• Ask AI tools like ChatGPT or Perplexity where they got their information for a search related to your industry
• Compare those sources to your own coverage; are competitors dominating? Are you absent?

Watch the usual suspects

• News and niche blogs: Industry-specific expertise often earns citations
• Forums and social platforms: Reddit, LinkedIn, YouTube, and Instagram are monitored for brand mentions
• Local citations: Yelp, BBB, and industry directories feed local keywords into AI-driven recommendations

Close the gaps

• Fill in missing structured data where competitors are already using schema markup
• Create content clusters around high-intent search intent topics missing from your site
• Participate directly in conversations where AI is already “listening”

AI visibility is earned where real people ask questions, share experiences, and link to trustworthy sources. If you’re not showing up there, you’re giving the ranking algorithm no reason to feature you in zero-click searches or knowledge panels.

Be the source AI trusts

AI isn’t killing SEO, but it’s definitely rewriting the playbook. Structured data, visuals, and social proof aren’t optional extras anymore. They’re the baseline for earning visibility in AI-driven search results, voice assistants, and AI-generated summaries.

The brands that act now will own the answers AI serves up tomorrow. Future-proof your content, feed the signals AI trusts, and make your presence undeniable before these systems become the default way customers discover and decide.

Want help auditing your local search presence? Take advantage of our free local search audit today and see exactly where you stand.

Your Google Business Profile is the backbone of local SEO. It puts your business on Google Maps, pulls you into local search results, and drives real revenue through calls, clicks, and visits.

But even the best-looking profile can miss the mark. Select the wrong category, create duplicate listings, or neglect buried backend details, and you risk losing rankings—and revenue.

And, given the rise of the AI search era, it’s imperative to enhance every aspect of your local marketing strategy to ensure you remain visible.

This post walks through the most common Google Business Profile issues and gives you clear fixes that improve visibility, strengthen your SEO strategy, and keep your brand’s listings front and center on Google Search.

The silent killers of local rankings

Optimizing your Google Business Profile isn’t just about adding local keywords or gathering customer reviews. While content and reputation signals are important, they’re only part of the equation.

With AI-generated results gaining traction in Google Search, your GBP accuracy and landing page clarity matter more than ever. Misinformation, missing data, or misaligned schema can lead to exclusion from key answer boxes or AI summaries.

Technical SEO is often the most overlooked part of local optimization. These backend issues quietly undermine your visibility without warning. They may not be visible to customers, and you won’t get a warning from Google. You’ll just see fewer views, fewer clicks, and a slow slide down the rankings.

A few examples include:

• Broken or misdirected URLs
• Slow or non-mobile-friendly landing pages
• Inconsistent NAP details across business listings
• Tracking issues that block visibility in Google Search Console
• Missing structured data
• Keyword stuffing in business descriptions

These problems hurt user experience and send mixed signals to Google. They can knock you out of the local pack, even if everything else looks fine.

Unlike reviews or photos, you can’t fix these in five minutes. But the effort is worthwhile. Once remedied, they have a measurable impact on local search performance and your bottom line.

Let’s take a deeper look at the most common mistakes and what you can do about them.

Common mistake #1: Broken links (404s, 403s, server errors)

Your Google Business Profile lets you add a website link; however, this simple detail can have a big impact if that link leads to a broken page. It sends the wrong message fast.

We’re talking about 404 errors, 403 permissions issues, or links that lead to dead-end server errors. These aren’t just technical hiccups. They’re red flags for both users and the search engine.

People click expecting answers. Instead, they will hit a wall. That hurts trust and kills momentum. For Google, it signals sloppy site maintenance, and that’s one of the most avoidable SEO mistakes in local SEO.

How to fix it:

• Run regular audits
• Fix broken pages or set up proper 301 redirects
• Make sure the link doesn’t lead to a page behind a login or restricted access (403s)

Clean links improve user experience and help reinforce credibility with search engines. They also protect the value of any local backlinks pointing to your site, ensuring you don’t waste ranking power from hard-earned authority.

A working link might seem basic. But when it’s broken, everything else on your profile starts to look questionable.

Common mistake #2: Improper or excessive redirects (302s, redirect chains)

Your Google Business Profile link should go straight to your landing page. No detours. No redirect loops. Just a direct connection that loads quickly and clearly tells Google and your customers: here’s what you’re looking for.

But too often, that’s not what happens. Redirect chains, especially 302s or URLs with multiple tracking hops, create friction. The more steps between Google and your content, the more likely your local SEO efforts will stall.

Improper redirects confuse the search engine, slow down site crawling, and strip away valuable ranking signals. It’s one of those local SEO mistakes that’s easy to miss but costly over time.

How to fix it:

• Link directly to the final landing page
• Skip unnecessary tracking parameters or affiliate redirects
• Use 301 redirects only when needed, and test for loops or chains that drag down performance

A clean, direct link strengthens your local content, helps protect local rankings, and keeps site traffic flowing efficiently. It also makes your profile more trustworthy both to bots and to people.

Redirects should support your content strategy, not sabotage it. Keep them simple. Keep them clean.

Common mistake #3: Not tracking your Google Business Profile links

If you’re not tagging your GBP URLs, you’re flying blind. The absence of UTM parameters means you can’t see how much traffic your profile is driving, nor how it’s performing in Google Maps and local search.

This kind of visibility isn’t optional. It’s foundational to your SEO strategy.

Without tracking, there’s no way to tell which locations are converting, which updates move the needle, or how users move from your profile to your site. It’s one of the easiest SEO mistakes to fix, and one of the most important.

How to fix it:

• Add UTM codes to your GBP website links
  Example: ?utm_source=google&utm_medium=local&utm_campaign=gbp
• Use consistent naming across all locations
• Set up filtered views in Google Analytics to segment local traffic

When you can see what works, you can double down. You’ll know which pages support your local search presence and where to fine-tune your SEO strategy. That means smarter decisions, stronger performance, and fewer surprises in search engine rankings.

Common mistake #4: Mismatched or inconsistent business info (NAP)

Your business name, address, and phone number (NAP) needs to match everywhere. One wrong digit, a slightly different street name, or outdated info in a directory can confuse both users and search engines.

This mismatch weakens your local trust signals and chips away at your authority in local listings. People rely on accurate details to visit, call, or navigate to your location. So does Google. If the NAP on your GBP doesn’t match what’s on your site, in the Attributes section, or in third-party directories, expect lower visibility near local landmarks and across the map.

How to fix it:

• Run a full audit of your NAP across all locations and major platforms
• Sync GBP data with your site’s schema markup and structured content
• Use a citation management tool to keep info current and consistent

You can also reinforce accuracy with supporting signals, using region-specific blog posts and making Google Posts that reference local landmarks to tie your business to a specific place. Keep an eye on your Q&A section, too. Outdated answers can send the wrong message just as easily as a wrong phone number.

Common mistake #5: Linking to a non-optimized landing page

Your GBPshouldn’t send users on a scavenger hunt. If the link goes to a generic homepage (or worse, a thin, outdated page) you’re wasting the click.

Each of your brand’s local landing pages needs to work hard. It should speak directly to the location, the service area, and the intent behind the search. If it doesn’t, you’ll miss out on both conversions and visibility in local search results.

A well-optimized page reinforces your relevance, improves rankings, and builds trust in seconds. A weak one tells Google and prospective customers you’re not serious, and that’s entirely the wrong message.

How to fix it:

• Link directly to a location-specific landing page
• Use local keywords, customer reviews, images, and clear business information
• Include contact details, service descriptions, and mention the city or neighborhood
• Write a strong, relevant meta description
• Prioritize mobile optimization, fast load speed, and responsive design
• Use structured data markup to help search engines understand the content
• Optimize for voice search; people ask for services the way they speak, not the way we write

This is where content creation meets technical precision. When your landing pages reflect your local presence and deliver a clear message fast, they convert better, and rank better.

Common mistake #6: Wrong or missing GBP categories

Choosing the right business categories in your GBP is one of the strongest signals Google uses to understand local relevance.

If your primary category is too broad, too vague, or just plain wrong, you’re likely missing your target audience altogether. And if your competitors are using more accurate or complete categories, they’ll outrank you no matter how strong your business listings or content may be.

This directly impacts your keyword rankings and visibility in local search. You can have all the right info, but if your categories are off, you’re pointing Google in the wrong direction.

How to fix it:

• Research which business categories your top competitors are using
• Choose a precise, accurate primary category as this one carries the most weight
• Add secondary categories that support your services, unless you’re in a restricted vertical like healthcare

Your categories are the backbone of your profile. Get them right, and you’ll show up for the searches that matter. Get them wrong, and you’ll disappear from view and miss out on category-specific attributes, even if everything else is buttoned up.

Common mistake #7: Ignoring structured data

Structured data helps Google understand what your page is about. Without it, your landing page lacks key signals that support local relevance.

If the page linked from your GBP doesn’t include schema markup—like LocalBusiness or Organization—Google may miss critical details: your NAP, service areas, or business type. That can limit your visibility in local search and rich results.

How to fix it:

• Add LocalBusiness or Organization schema to your GBP-linked landing page
• Include consistent NAP, geo coordinates, business type, and services
• Match the schema to your GBP exactly
• Test implementation using Google’s Rich Results Test

Structured data doesn’t boost rankings directly. But it gives Google clearer context, improves indexing accuracy, and supports stronger performance in local search.

Common mistake #8: Underusing Google Business Profile features

Your GBP isn’t set-and-forget. It’s a living listing, and Google favors the businesses that treat it that way.

Too many brands skip key features that signal activity and relevance:

• Not regularly updating your GBP
• Leaving customer questions unanswered in the Q&A section
• Incomplete business hours, especially during holidays
• Not responding to reviews or worse, answered without relevant keywords

These aren’t just missed opportunities. They’re engagement signals that feed Google’s local ranking algorithm. The more complete and active your profile, the more likely you are to earn trust and visibility.

How to fix it:

• Post updates consistently with new offers, events, or product highlights
• Seed your Q&A with real FAQs customers are asking
• Respond to all reviews using natural, keyword-relevant language
• Keep hours accurate, especially during seasonal changes and holidays

An active profile tells Google you’re paying attention, and that earns better placement. Small, regular updates go a long way in staying visible and building local trust.

How to audit your brand’s GBP technical health

For enterprise brands, the challenge isn’t knowing what to fix but keeping it consistent across hundreds or even thousands of locations. Broken links. Mismatched NAPs. Missed updates. These issues don’t just pop up, they multiply.

A simple, repeatable audit process is essential.

Enterprise-ready GBP technical health checklist:

• Scan for broken links, redirect chains, or blocked URLs across all listings
• Add or validate UTM tracking to accurately segment traffic
• Ensure NAP consistency across websites, directories, and local listings
• Audit linked landing pages for load speed, mobile optimization, and local content
• Review business categories, hours, and active use of profile features
• Validate structured data using Google’s Rich Results Test
• Monitor GBP Insights and connect attribution data in Google Analytics

Managing local SEO at scale means locking down the details, then automating what you can and auditing the rest.

A clean GBP is a high-performing GBP

Managing local SEO across hundreds or thousands of locations means details slip. Pages break. Categories drift. Profiles get stale. This isn’t just about technical SEO. It’s about keeping every listing accurate, active, and aligned, so customers can find you and search engines can trust you.

Most of the fixes we’ve covered here are straightforward. They don’t take long, but they make a real difference when rolled out across your network. The key is getting it done at scale, and staying on top of new opportunities and potential issues as they arise.

Need help wrangling that complexity? Reach out to Rio SEO for a free, enterprise-grade audit of your Google Business Profiles and local SEO performance.

Across thousands of enterprise locations, Google views are dropping. Hard. Since 2022, total search impressions are down nearly 30% and search views have fallen by 40%. 

Website clicks? Shrinking. Yet somehow, the total number of clicks has held steady. So what’s happening?

In short, Google is reshaping how people find businesses (or don’t). Traditional search results are getting squeezed. Now AI summaries, map packs, and richer SERP features are stealing the spotlight. Organic listings are being overshadowed by bots and bundles.

And it shows:

• Retail views have been sliced in half since 2022
• Restaurant visibility crashed 18% in a year
• Website traffic is falling across every vertical

But it’s not all decline. Direction requests are up, phone calls are steady, and map views have quietly become the main stage. That tells us something important: customers still want to visit your locations; they’re just reaching you through fewer entry points.

Still, it’s not universal. In many industries, especially those less reliant on appointments or in-person visits, web and call clicks are slipping. Zero-click searches are eating into engagement, and the impact gets masked in aggregate by stronger performance from sectors like healthcare and services. That’s why it’s more important than ever to zoom in by vertical.

The impact of the June Google core algorithm update

Between June 24 and 25, we observed an abrupt decline in mobile search impressions across nearly every vertical we track, including retail, staffing, and financial services. Yet engagement metrics — clicks, calls, direction requests — held steady. That suggests user behavior didn’t change. What changed was how Google reported visibility.

Here’s what we know:

• Google officially launched its June 2025 Core Algorithm Update on June 30
• Volatility in impressions started as early as June 24, especially on mobile
• The rollout lasted until July 17, with ranking fluctuations continuing throughout
• There were no changes to engagement, suggesting a shift in how impressions are measured or reported

Some in the industry flagged a possible reporting glitch. Others believe this reflects deeper SERP changes or AI Overviews suppressing standard listings. Either way, the pattern is clear, and it’s global.

Impressions are down. Actions are stable. The signal is shifting.

That’s why we’re watching this trend closely. And while impressions have never been a perfect metric, they still shape how brands evaluate visibility. This quarter’s data reflects that shift. So does the response from enterprise marketers: optimize for action, not just appearance.

Our Q2 2025 local consumer search trends analysis breaks down how search behavior is evolving, where it’s holding strong, and what your next move should be.

Year-over-year local search trends

Compared to Q2 2024, most enterprise brands saw a sharp drop in local search visibility. Total impressions fell across five of the seven verticals we track — some by more than 30%. 

Financial services and restaurants were hit hardest, with views down –21.3% and –35.0% YoY, respectively. Business services saw the steepest decline overall at –30.2%, pointing to sustained disruption in how users discover service-based locations.

Retail and hospitality also lost ground, with total views down –8.3% and –5.0% YoY. In both cases, Search visibility fell further than Map impressions, likely due to changes in SERP layout and the growing influence of AI-generated summaries.

Only healthcare and multi-family residential bucked the trend. Healthcare saw a modest +8.3% YoY gain in visibility and a +4.3% increase in total clicks — one of the only categories with consistent growth. Multi-family views also climbed slightly YoY (+4.3%), though click-throughs fell -12.3%, pointing to a growing gap between exposure and engagement.

What’s clear is that brands that rely on visibility alone are losing ground. It’s no longer enough to show up; your listing has to work harder to win the click.

Quarter-over-quarter local search trends

Q2 2025 brought a much-needed rebound in engagement, even as total visibility remained uneven.

Retail led the way with a +7.3% QoQ gain in views and +11.3% jump in total clicks. Restaurants held flat on views but saw clicks climb +11.1%, while hospitality impressions rose +4.1%, backed by a +13.8% lift in actions. Those three verticals alone show a clear trend: even if reported visibility is uneven, real interest hasn’t faded. When listings work, users follow through.

Business services followed a similar pattern, with views down slightly (–2.1%) but clicks up +20.9%. Multi-family brands gained on both fronts, with views up +9.0% and clicks up +9.3% QoQ — a positive shift after a quiet Q1.

Healthcare remained steady, with only small changes in either direction. But financial services continued to struggle, with views down another –10.3%. Still, a +6.8% QoQ rise in clicks shows that users who do find the right listings are acting.

Taken together, the data tells a consistent story: impressions are down, but engagement is up. That points to a shift in what Google is counting, not a drop in audience. It’s a signal to optimize not just for visibility, but for velocity. Cut friction, sharpen content, and focus on high-intent CTAs beyond just direction clicks… think ‘schedule an appointment’ or ‘order now’ links.

Now, let’s take a deeper look at the eight verticals we track.

Retail

• Total Q2 2025 views: +7.3% QoQ, -8.3% YoY
• Total Q2 2025 clicks: +11.3% QoQ, +4.3% YoY

Retail brands saw a solid rebound in Q2, reversing much of the Q1 downturn. Total views rose +7.3% quarter-over-quarter — a meaningful recovery, though not enough to overcome the -8.3% drop from the same time last year.

Search views led the way, jumping nearly 17% from Q1, signaling renewed top-of-funnel activity. But not all impressions rebounded equally. Map views, while slightly up quarter-over-quarter (+1.7%), remain down -12.2% year-over-year compared to Q2 2024 — a likely result of shifting search behavior and AI-powered result formats reducing traditional Map exposure.

Clicks tell a different story — one of growing intent.

Total actions on listings climbed +11.3% from Q1 and beat last year’s volume by over 4%. Driving direction clicks saw the biggest gain, up +21.6% quarter-over-quarter and +14.4% year-over-year, a strong signal of in-person shopping intent.

Website clicks also rose (+6.1% QoQ), while phone calls dipped slightly (-1.4% QoQ), suggesting that shoppers may be relying more on self-service information available on the listing or website.

Engagement is back, even if views haven’t fully recovered. Not all impressions are created equal. Retailers saw fewer views overall compared to last year, but more meaningful engagement from the customers who did see them.

Where to focus next

• Watch the balance between Search and Maps views to guide content strategy
• Identify top-performing stores and replicate what’s working
• Keep listings fresh, including hours, categories, images, and fulfillment options
• Drive fresh reviews and respond consistently to build trust
• Support GBP with optimized local pages for key offerings

Financial services

• Total Q2 2025 views: -10.3% QoQ and -21.3% YoY
• Total Q2 2025 clicks: +6.8% QoQ, -3.5% YoY

Q2 brought a mixed bag for financial services brands. Visibility continued to decline, with total views down -3.4% from Q1 and now -21.6% compared to the same period last year. Search views saw the sharpest drop, falling another -4.6% QoQ, on top of already steep Q1 losses. 

That suggests fewer local discovery moments — especially on mobile — as users increasingly skip the map and scan summaries or AI-generated results instead.

But here’s what stands out: Clicks went up. Total actions on listings rose +6.8% QoQ, with driving direction clicks leading the recovery at +11.0%. That marks the first YoY lift in driving clicks since 2023. It’s a sign that high-intent customers are still navigating their way to branches when they find the right info.

Phone clicks and website visits, on the other hand, remained flat or declined. Phone actions dropped -3.3% QoQ, and website clicks were unchanged from Q1 but still -8.4% below last year. That may point to friction in how listings present next steps, or to customers relying more on listings and reviews to make decisions without ever clicking through.

With fewer total views but more engagement, Q2 confirms what we’ve seen brewing: local search for financial services is shifting from casual discovery to high-consideration decision-making.

Where to focus next

• Respond to every review to build trust where it matters most
• Keep listings accurate, especially services, hours, and phone numbers
• Use branch-level email and SMS to close the gap between search and action
• Watch direction clicks to spot high-intent locations and align staffing

Businesses services

• Total Q2 2025 views: -2.1% QoQ and -30.2% YoY
• Total Q2 2025 clicks: +20.9% QoQ and +3.2% YoY

After a sharp downturn in Q1, business service brands found firmer footing in Q2. Total views were still down year over year, dropping 30.2%, but the rate of decline slowed quarter over quarter. More importantly, total clicks rebounded—up 20.9% QoQ and slightly above last year’s levels.

That signals a shift in intent, with fewer searches overall, but higher engagement when users do look.

Search views rose 2.2% QoQ, while Map views fell 7.5%. That suggests the visibility dip is tied more to SERP shifts and AI changes than user disinterest. And once users did engage, they were more likely to take action—especially via websites and direction requests.

• Website clicks jumped 30% QoQ
• Driving direction clicks rose 21.2%
• Phone calls dipped slightly, down 1.6%

These patterns reinforce what we’re seeing across verticals: discovery is becoming more selective, and customers are skipping low-relevance results in favor of trusted sources.

For business service brands—many of which rely on high-consideration actions like consultations, quote requests, or bookings—accuracy and authority are everything. If your listing isn’t up to date or backed by solid review content, it may never surface in the first place.

Where to focus next

• Prioritize review quality and response time to reinforce trust
• Keep listings fresh with current services, hours, and contact info
• Highlight high-converting branches and align campaigns accordingly
• Use website and direction click trends to track engagement hotspots
• Monitor Map vs. Search view shifts and adapt visibility strategy

Healthcare

• Total Q2 2025 views: –1.6% QoQ, +8.3% YoY
• Total Q2 2025 clicks: +2.1% QoQ, +4.3% YoY

Healthcare brands held steady in Q2, with only minor shifts across metrics and signs of quiet but meaningful growth. Views dipped slightly from Q1 (–1.6%), but year-over-year visibility improved (+8.3%), making Healthcare one of the few verticals with positive annual growth.

Search impressions fell only –0.8% QoQ and remained up +7.5% YoY, suggesting that patient-driven lookups for providers or services continue to hold strong. Map views dipped –4.0%, but still show a +10.9% gain compared to Q2 last year.

Click data paints a more encouraging picture.

Total actions rose +2.1% QoQ and +4.3% YoY — small but consistent gains. Driving direction clicks jumped nearly +9% quarter-over-quarter, reinforcing the continued importance of in-person visits in a post-telehealth plateau. Website clicks dipped slightly (–3.4% QoQ), but phone calls held steady.

One standout stat: location-based actions (like driving directions) now account for a larger share of total engagement. And with direction clicks up +7.9% YoY and conversion-focused impressions trending upward, intent is clearly there — even if volume isn’t spiking.

Where to focus next

• Keep location and service listings up to date, especially hours and provider availability
• Track direction clicks to see where in-person demand is highest
• Use reviews and FAQs to reassure patients during the search moment
• Prioritize mobile clarity; users are still calling, even if clicks dip
• Align local landing pages with health system-wide campaigns for consistency

Hospitality

• Total Q2 2025 views: +4.1% QoQ, –5.0% YoY
• Total Q2 2025 clicks: +13.8% QoQ, +3.1% YoY

Hospitality brands continued their steady rebound in Q2. Views climbed +4.1% from Q1, led by a +9.4% jump in Map impressions, a sign that travel planning and local discovery are back on the rise. Still, total visibility remains –5.0% below Q2 2024 levels, with Search views down –11.2% YoY.

Engagement surged ahead of impressions.

Total clicks rose +13.8% quarter-over-quarter, with direction requests up +18.6% and phone calls up +13.5%. That’s a strong signal of action-oriented intent — especially among users making last-minute decisions or navigating locally.

Website clicks saw a smaller boost (+3.7% QoQ), but the real standout was direction clicks: up +11.1% year-over-year. In a vertical where proximity drives bookings, that’s a sign people are still showing up, and listings are converting.

Where to focus next

• Optimize listings for last-mile actions: directions, hours, and click-to-call
• Add booking links and make CTAs clear and mobile-friendly
• Use direction trends to staff and promote high-performing locations
• Prioritize speed and clarity on local landing pages to reduce drop-off
• Monitor bookings closely to identify friction between click and conversion

Restaurants

• Total Q2 2025 views: –0.4% QoQ, –35.0% YoY
• Total Q2 2025 clicks: +11.1% QoQ, –5.7% YoY
• Food orders per location: –10.4% QoQ, –46.5% YoY
• Food menu clicks per location: +9.2% QoQ, –18.8% YoY

Restaurant brand visibility took another hit in Q2. Total views were essentially flat from Q1 but still down a steep –35% from last year. Maps views fell –4.4% quarter-over-quarter, while Search views climbed +3.3%, pointing to a shift in how and where diners are discovering restaurants.

Clicks were a brighter spot.

Total listing actions jumped +11.1% over Q1, driven by a nearly +19% surge in driving direction clicks. Website visits also rose +5.5%. That bump in discovery-to-decision behavior suggests that even as exposure drops, motivated diners are following through.

But phone calls slipped again, down –2.1% QoQ and –17.4% YoY — a sign that listings need to do more heavy lifting in answering diners’ questions without human help.

Meanwhile, food orders per location plunged –10.4% from Q1 and –46.5% YoY. That’s a sharp signal that interest isn’t converting. At the same time, food menu clicks rose +9.2%, suggesting more users are exploring menus — but not committing.

That growing gap between intent and action points to friction in the ordering experience, or possibly customers defecting to third-party apps. Either way, high funnel interest isn’t enough.

Where to focus next

• Audit listings for accuracy — hours, categories, and amenities matter
• Make menus easy to access and update — especially on mobile
• Use direction click data to identify high-performing locations
• Streamline food ordering paths to reduce drop-off
• Monitor reviews and respond quickly to protect trust and conversion

Multi-family residential

• Total Q2 2025 views: +9.0% QoQ, +4.3% YoY
• Total Q2 2025 clicks: +9.3% QoQ, –12.3% YoY

After a slow start to the year, multi-family listings gained visibility in Q2. Views rose +9.0% over Q1, with Search views up +10.0%. Compared to Q2 2024, visibility is trending slightly ahead — up +4.3% year-over-year overall.

Click activity also picked up slightly, climbing +9.3% quarter-over-quarter. But the YoY picture tells a different story: total clicks remain down –12.3% from this time last year, despite more people seeing listings.

Driving direction clicks rose +15.2% from Q1 — a sign that foot traffic and in-person interest may be rebounding. Phone calls, however, dropped further: –45.1% YoY. 

Website clicks also stayed in the red, down –9.5% YoY.

That split suggests that while interest is returning, conversion remains patchy. Prospects might be turning to third-party platforms or experiencing friction on brand-owned sites.

Still, impressions in Google are improving. And with renters actively comparing options, it’s a crucial moment to close the gap between visibility and follow-through.

Where to focus next

• Refresh listings with current amenities, floor plans, and photos
• Audit phone numbers and contact paths for accuracy and ease
• Track direction clicks to align marketing with on-site activity
• Improve website UX and mobile load times to reduce bounce
• Use review responses to build trust in competitive markets

Local visibility is shifting—are you keeping up?

This quarter confirmed a growing truth: impressions are fading, but intent isn’t. Across verticals, total views are still falling, in some cases by double digits year-over-year. Yet clicks, especially high-intent actions like directions and website visits, are holding steady or rising. Consumers aren’t disappearing. They’re just taking fewer steps to act, and skipping listings that don’t meet their needs.

AI Overviews and changing SERPs are reshaping discovery. Organic links are losing space to summaries, bundles, and richer in-SERP tools. That’s shrinking the top of the funnel, and raising the stakes for every impression that does land. If your listing isn’t accurate, complete, and compelling, it won’t just get overlooked — it might not show up at all.

But when listings work, they really work. From driving direction surges in Retail and Restaurants to rising action rates in Healthcare and Business Services, one thing is clear: customers still want to connect. They’re just skipping the fluff and heading straight for the good stuff. Your listings, local pages, and reviews need to meet them there, in the moment.

The brands winning in this new reality aren’t chasing views. They’re building for action. Strong local visibility now means fewer doors, but better ones. Make sure yours is open.

Want to know where you stand? Request your free local audit to uncover hidden gaps, growth opportunities, and tips tailored to your brand.

Google just flipped the local search script, and it’s already reshaping how brands show up or don’t. Enter Google’s AI Deep Dive mode.

Two recent changes set this all in motion, and these aren’t just technical tweaks. They’re fundamental shifts in how Google decides who earns visibility, trust, and clicks in a world where AI is the front door to discovery.

First came Google’s June 2025 core algorithm update. Then on July 9, it introduced a new mode within AI Overviews. A week later, a blog post confirmed the shift: “More advanced AI capabilities are coming to Search.”

Together, these updates mark the start of a new era: one where sentiment, star ratings, and authority signals outweigh keyword stuffing and map-pack tactics.

For brands relying on local search: If you’re not optimizing your review strategy and reputation management for AI, you’re fading from view.

What changed: Google’s AI Deep Dive Mode & core algorithm update

The first tremors came with Google’s core algorithm update, which began rolling out June 24–25 and continued into early July. The update hit hard, but not how most expected.

Across nearly all industries, impressions dropped. Fast.

In some cases, the drop was as steep as 30–50% compared to previous months. However, while impressions declined, engagement metrics such as clicks, calls, and direction requests remained steady or even increased.

So what happened?

In short, Google is cleaning house. It’s cutting out the noise, dropping impressions that were never meaningful in the first place. For example, if your business used to appear in searches that weren’t truly relevant—like a pet store showing up for “restaurants near me”—those phantom impressions are slowly being removed.

This isn’t a local SEO penalty. It’s a precision upgrade.

And that pruning of noise paved the way for what came next: a deeper, AI-driven view of local results.

Google introduces Gemini 2.5 Pro: What this means for local marketers

On July 9, Google rolled out a new mode within AI Overviews. Then on July 16, it published a blog post titled “More advanced AI capabilities are coming to Search” that confirmed how fast—and far—this shift is moving. 

Here’s what it looks like in action.

When a user searches for something like “best coffee near me” or “affordable dog groomers in Denver,” the top of the results page now includes an AI Overview. This snippet includes a quick description of top-rated places, links directly to their Google Business Profiles, and shows off their average star ratings. In some test environments, the user can even toggle into a deeper view to explore more businesses, sorted by rating and reputation.

There’s also a deeper wrinkle. Some of the “lost” impressions may not be lost at all; they might just be getting rerouted into this new AI experience. Google’s AI Overview and Deep Dive environments may not register in traditional reporting yet, which means engagement could be happening off the radar. In other words, this isn’t just a drop… it’s a shift.

This is not a test. It’s the new normal.

What the AI prioritizes: Sentiment, star ratings, and authority

If you’ve spent the last few years focused on proximity and category optimization, it’s time to pivot.

In this new experience, Google Search is prioritizing businesses with high-quality reputations—both on their own listings and across the web.

We’re seeing the AI pull data from:

• Google Business Profile (GBP) reviews
• Star ratings, especially 4.9 and above
• Review sentiment (positive tone, descriptive language)
• Trusted third-party sources like Yelp, TripAdvisor, Facebook, and even YouTube
• Local business websites that embed their own GBP reviews

We’re also seeing a clear boost for businesses that embed their Google reviews directly on their websites. Sites like Docs of Denver are showing up repeatedly in AI panels—not because of SEO tricks, but because they’ve turned their own pages into review-rich sources Google can trust.

In test environments, businesses are ranked by reputation, and only those with 4.9+ star ratings consistently appear.  Everyone else? Pushed out of sight.

This isn’t just about numbers. It’s about quality, consistency, and trust. Google is drawing directly from the words customers use—what they praise, what they criticize, how often they leave feedback, and where those reviews live online.

Even the knowledge panels accompanying some AI Overviews are changing. Instead of pulling from just structured data or business profiles, they now highlight:

• Quotes from GBP reviews
• Mentions from Yelp and TripAdvisor
• Embedded reviews from business websites
• Social signals from platforms like Facebook and Instagram

If your business hasn’t invested in building out those trust signals, AI might simply pass you over.

Translation: The old playbook—optimize your NAP and hope for the best—is done.

To rank, you need high-quality reviews and an active, consistent presence across the digital ecosystem.

AI Mode just got smarter with Gemini 2.5 Pro and Deep Search

Just days after expanding AI Overviews, Google rolled out its most advanced AI features yet. On July 16, it announced Gemini 2.5 Pro and Deep Search—now live for Google AI Pro and Ultra subscribers in the U.S

These tools mark a shift in how Google thinks about search:

Search is becoming your researcher

Deep Search issues hundreds of real-time queries, compares information across the web, and delivers a fully cited summary in seconds. For brands, this means your content, reviews, and citations must be clear, accurate, and AI-readable—because that’s what’s feeding the response.

AI is taking action for users

With new agentic features, Search can now call businesses directly asking about prices, availability, and services. If your info is incomplete, AI won’t just skip the call, it might skip your listing entirely.

Here’s the takeaway for local brands

You’re no longer just optimizing to be seen. You’re optimizing to be understood. Gemini and Deep Search are teaching Google’s AI how to make decisions—and your listings, reviews, and citations are the training data.

The bar just got higher. Meet it, or miss the moment.

The hidden cost of doing nothing

A Rio SEO client in the athletic retail space recently tested the power of proactive review generation. They launched a 90-day email campaign encouraging recent customers to leave reviews on Google. The goal was simple: increase the number of fresh reviews and raise their average star rating.

It worked.

Over the course of the campaign, they saw:

• A 400% increase in review volume
• A 16% lift in average rating

But then they paused the campaign. Within six weeks, review volume plummeted 75% and their average store rating dropped 12%.

Now, consider what that means in an AI-powered local landscape, where visibility hinges on review freshness, frequency, and sentiment. If your reviews are months old, your average is mediocre, and your response rate is poor, Google’s AI won’t feature your business. Not because you’re doing something wrong, but because someone else is doing it better.

Without a steady stream of feedback, your reputation won’t just plateau; it’ll regress. Google’s AI rewards momentum, and without it, your average will slide toward the statistical middle.

Action plan: How to compete in an AI-first search environment

This isn’t about SEO hacks or technical tricks. This is about building a reputation strategy that Google can trust, and that customers want to engage with.

Here’s how to do it.

1. Launch review solicitation campaigns

Don’t wait for customers to leave a review. Ask them. Use post-purchase emails or mobile prompts to encourage quick feedback. Keep it simple. Make it frictionless. And focus on driving both volume and quality. The more reviews you earn, and the better their tone and rating, the stronger your visibility in AI Overviews.

Aim to push your average rating above 4.5, and hold it there.

2. Manage your reputation like your visibility depends on it (because it does)

It’s not enough to collect reviews. You have to respond to them. Every time.

Monitor reviews daily. Address complaints quickly and publicly. Thank loyal customers. Build a pattern of active engagement.

Platforms that support review monitoring, sentiment alerts, and response templates can make this easier to scale across locations. But what matters most is consistency. Google’s AI is watching.

3. Expand your digital footprint—and your citations

The new AI Overviews don’t just scan your GBP listing. They’re pulling from across the web. Make sure you’re present and active in places Google trusts.

Start here:

• Yelp: A must-have for services, retail, and professional verticals
• TripAdvisor: Critical for restaurants, hotels, and attractions
• Facebook and Instagram: Google is picking up brand signals from these platforms
• YouTube: Especially valuable for brands with how-to content, reviews, or community engagement
• Your own website: If you’re not embedding your Google reviews, you’re missing a key signal

Yelp and TripAdvisor, in particular, are emerging as must-haves, not nice-to-haves. Yelp appears prominently in AI panels for services and retail, while TripAdvisor is dominating restaurant and hospitality results. These platforms aren’t part of most basic listing packages, but for brands serious about visibility, investing in these citations is no longer optional.

Think of it as building a trust network around your brand. The more consistently you show up across authoritative platforms, the stronger your authority in AI search becomes.

Your reviews are your ranking

Local search is no longer a game of proximity and metadata. It’s a reflection of what people are saying, how often they’re saying it, and where.

In AI search, customer experience writes the rules. Google’s AI surfaces what real people say, not what brands claim.

That means:

• A high average star rating isn’t optional. It’s the price of entry.
• Fresh reviews from happy customers aren’t nice to have. They’re your visibility engine.
• Ignoring reputation management isn’t just risky. It’s disqualifying.

This is about customer experience, not clever optimization. And Google is making that clear with every update.

Google’s AI doesn’t care how long you’ve been around. It cares what your customers are saying—right now. Review sentiment, volume, and freshness are the top-ranking factors in AI Overviews. Everything else comes second.

Talk to your reputation team today

You can’t out-keyword AI.

But you can build trust. You can encourage feedback. You can create a customer experience that fuels visibility, loyalty, and revenue.

Talk to your internal CX team. Partner with a reputation platform. Develop a plan for generating high-quality reviews and providing fast, consistent responses.

The future of local search isn’t just algorithmic. It’s emotional, authentic, and powered by real people. That’s what AI is learning from—and that’s where brands need to meet it.e sales across Apple Maps, Google, and the rest of the local ecosystem.

Apple Maps has come a long way. What started as an iOS default is now a navigation powerhouse, transforming how consumers discover and engage with local businesses. With seamless integration across the expansive Apple ecosystem—think Siri, CarPlay, and Safari—Apple Maps is becoming a serious competitor to Google Maps.

Yet, this growing platform remains a blind spot for many businesses. According to BrightLocal, 59% of businesses are unaware of Apple Business Connect, the tool that lets brands control their presence on Apple Maps. That’s a staggering missed opportunity, especially as more consumers turn to online search for daily decision-making.

Our own local consumer behavior research says that 90% of consumers conduct online searches daily, and many of those searches are local. They’re looking for the nearest coffee shop, the best-rated mechanic, or tonight’s restaurant reservation. If your business isn’t optimized for Apple Maps, you’re leaving potential customers and revenue on the table.

Ready to learn more about unlocking the untapped potential of Apple Maps and its Place Cards? Stick with us.

Apple Maps in numbers

Apple Maps has carved out a significant footprint in the digital navigation world, fueled by the immense reach of Apple’s ecosystem. With over 2.2 billion active Apple devices globally, this platform has become the go-to for millions of users searching for directions, reviews, and business information.

Market penetration and platform integration

Apple Maps comes pre-installed and set as the default navigation app on all iOS devices, giving it unparalleled access to Apple’s user base. Its integration with Siri, CarPlay, and Safari makes it a seamless tool for users on the go. Want to find a nearby restaurant while driving? Siri uses Apple Maps. Need turn-by-turn directions displayed on your screen? That’s Apple Maps via CarPlay.

Despite its growing use, Apple Maps still lags behind Google Maps in market share: 88% of users prefer Google Maps, while 12% rely on Apple Maps. But here’s the untapped opportunity: With nearly 918 million global Apple Maps users—75 to 100 million regular users in the U.S. alone—this platform it’s no longer just a player in the navigation game. It’s a sleeping giant.

Understanding Apple Maps’ user demographics

Apple Maps users bring significant purchasing power to the table. Understanding who exactly is using Apple Maps can determine if it aligns with your target demographic.

While specific age demographics for Apple Maps are not explicitly provided, general statistics indicate that a large segment of iPhone users (and by extension, Apple Maps users) falls within the 18 to 34-years of age group.

Apple’s user base also tends to skew toward higher-income demographics, with many users willing to spend on premium services and products. The average annual income for iPhone users is approximately $85,000, which is about 40% higher than the average income of Android users. The platform’s adoption is highest among younger to middle-aged consumers in urban and suburban areas, making it a prime channel for reaching affluent and engaged shoppers.

Apple Maps vs. the competition

When comparing user engagement and adoption rates:

• Google Maps: The leader with over 1 billion monthly active users globally. Its dominance stems from broader device compatibility and features like Street View and real-time traffic updates.
• Apple Maps: Estimated at 918 million users globally, with deep integration across Apple’s ecosystem creating a unique and frictionless experience.
• Waze: A niche competitor with 140 million monthly users, popular for its crowd-sourced traffic data.

While Apple Maps hasn’t yet reached Google Maps’ scale, its closed-loop ecosystem offers enterprise brands a unique advantage: exclusivity. By optimizing Apple Place Cards, businesses can tap into a dedicated audience that actively seeks out information on their Apple devices.

Apple Maps is not a platform to ignore. It’s a strategic asset for reaching a growing audience with high spending power and a loyalty to the Apple brand. In the next section, we’ll explore what makes Apple Place Cards so valuable and how businesses can leverage them.

What are Apple Place Cards?

Apple Place Cards are the digital storefronts of the Apple Maps ecosystem. They’re what customers see when they search for your business, offering a snapshot of everything they need to know to engage with you.

Each Place Card is customizable and packed with valuable information to help your business stand out. Here’s what they include:

• Business listings: Display key information like your business name, category, physical location, and contact details.
• Operating hours: Ensure customers know when you’re open (and when you’re not) with up-to-date hours of operation.
• Business details: Add a compelling business description to give users a reason to visit.
• Photos: Upload high-quality images that showcase your location, products, or services to make a lasting impression.
• Engagement features: With action buttons like “Call,” “Order”, “Book”, and “Website”, Place Cards make it easy for users to connect or navigate to your business.

A solid foundation for customer engagement

Apple Place Cards go beyond static listings. They act as interactive touchpoints, enabling businesses to create a seamless experience for users searching on Apple Maps. Customers can quickly identify your business type, explore services, and decide if your business meets their needs—all within a single interface.

For business owners, Place Cards offer the power to:

• Tailor listings to match your brand identity.
• Provide real-time updates, like special hours during holidays or new product launches.
• Highlight unique features and amenities that set your business apart.

With more Apple Maps users seeking accurate, detailed, and visually engaging information, Place Cards are the key to capturing their attention. Businesses that optimize their Place Cards are creating an engaging, trustworthy digital presence that drives action.

Now, why are Apple Place Cards so critical for boosting visibility and building trust?

Benefits of being on Apple Maps

Being on Apple Maps helps seamlessly integrate your brand’s locations into the daily lives of millions of Apple users. From local search rankings to customer trust, the advantages are clear. Here’s how your business can benefit:

Integration across the Apple ecosystem

Apple Maps isn’t a standalone app—it’s a cornerstone of the Apple ecosystem. It works hand-in-hand with Siri, Apple Watch, and Apple CarPlay, giving individual customers a consistent and intuitive user experience across devices:

• Siri: Users rely on Siri for voice-activated local searches, making it crucial for your location Place Cards to include accurate details like operating hours, contact info, and your business category.
• Apple Watch: Whether it’s a quick search for a business location or turn-by-turn navigation, Apple Watch keeps users engaged while on the move.
• Apple CarPlay: For drivers, CarPlay uses Apple Maps to deliver real-time navigation and suggestions based on nearby businesses. Having an optimized Place Card ensures your business is recommended at key decision-making moments.

If your business isn’t leveraging Apple Maps, you’re missing out on powerful tools to connect with customers in their most convenient and trusted spaces.

Building customer trust and experience

Today’s customers expect accurate, reliable, and visually engaging business listings. Verified Place Cards on Apple Maps provide exactly that, improving your brand’s credibility and overall customer experience.

According to our Local Search Consumer Behavior Study:

• 82% of local searchers are looking for business addresses and directions on business listings, followed by hours of operation (76%), contact information (75%), and website URLs (74%).
• 84% of local customers say first-party reviews are likely to influence their purchasing decisions.

Keeping your Apple Maps Place Card up to date with high-quality photos, accurate contact details, and positive customer reviews helps you meet these expectations and foster trust with your audience.

Boosting local SEO

Optimized location place cards enhance your business’s discoverability across multiple platforms. For example, Apple Maps listings influence local search results within Safari, Apple’s default browser. Additionally, accurate Place Cards improve rankings and visibility across other Apple tools, such as Wallet and Messages.

How can your brand close the adoption gap and make the most of this growing platform?

The untapped Apple opportunity is yours for the taking

Apple Maps offers businesses a largely untapped opportunity to engage millions of active users in ways that go beyond traditional local search tools. Despite its rapid evolution and valuable features, many businesses have yet to fully embrace this platform.

The gap in adoption is significant considering more than half (58%) of businesses have not claimed their Apple Maps listing, leaving their presence unverified and potentially inaccurate. What’s more, only 16% of businesses are using Apple Business Connect, the powerful competitor of Google Business Profile, that enables brands to manage their Place Cards and, in turn, their local search presence.

For comparison, Google Business Profile enjoys far higher adoption rates, as it’s been a long-standing default for local business management. This disparity highlights the opportunity for forward-thinking brands to gain an edge by optimizing their Apple Maps presence while competitors lag behind.

Projected growth

Apple Maps is continuously evolving with user-focused enhancements and innovative features that amplify its appeal:

• Hiking and outdoor exploration: Users can now explore thousands of U.S. national park hikes with detailed topographic maps and offline navigation. These updates are part of a broader effort to expand Apple Maps’ utility for outdoor and lifestyle experiences.
• Enhanced search experience: New features allow users to browse businesses based on photos, ratings, and pricing, all without leaving the search interface—streamlining discovery and decision-making.
• Places Library: This tool lets users save favorite locations, curated guides, and custom routes with personal notes, boosting engagement and return visits to Apple Maps.

We expect that future updates will make local search and navigation even more engaging, personalized, and interactive. Recent Apple Business Connect updates also introduced tools that elevate brand visibility:

• Branded mail: Display your business name and logo in customer emails, enhancing trust and open rates.
• Tap to Pay branding: Show your logo during payment transactions to reinforce your identity at the point of sale.
• Business caller ID (coming soon): Verified business names and logos on inbound calls will help your customers confidently pick up the phone.

These updates position the platform as a comprehensive tool for discovery, engagement, and brand building, with untapped potential for businesses ready to invest in its features.

How to take action: A checklist for local businesses

To seize this opportunity, businesses must take proactive steps to claim and optimize their Apple Maps listings. Here’s how:

• Claim and verify your listing: Sign in to Apple Business Connect and complete the verification process. This ensures your business is recognized as a trusted and accurate presence.
• Optimize your Place Card: Add high-quality photos, update contact details, and select the most accurate business category to ensure visibility in relevant searches.
• Showcase your offerings: Use Apple’s tools to highlight promotions, events, or services through engaging descriptions and action buttons like “Call” or “Get Directions.”

To make the most of Apple Maps, avoid common mistakes that can undermine your brand’s trust and visibility. Consistent NAP (name, address, phone number) data is essential—ensure these details match across all platforms to maintain accuracy and build customer confidence. Regular updates to operating hours, promotions, and photos are equally important to prevent disappointing potential customers with outdated information.

Additionally, Apple Maps analytics offers valuable insights into customer behavior, such as search frequency and direction requests. Use this data to identify top-performing locations, refine local marketing strategies, and tailor your offerings to align with user preferences and trends.

Apple Maps is no longer just a secondary player in the local search space. It’s a growing force with tools designed to help businesses shine. By acting now, you can position your brand ahead of the competition and build lasting connections with Apple’s influential user base. Want to learn more? Schedule a demo with Rio SEO and see how our LX platform can boost your visibility and drive sales across Apple Maps, Google, and the rest of the local ecosystem.

Today, search feels less like scrolling a directory and more like having a conversation with someone who understands exactly what you need. For local marketers, it’s not just a shift. It’s a shot to emerge at the top.

Local marketing in the Gen AI era is a chance to build real connections in real time, where life actually happens in neighborhoods, on sidewalks, in the palm of a hand.

Winning locally in the age of AI and fragmented search means being faster, sharper, and more human than ever before.

No more endless scrolling. No more one-size-fits-all answers.

Search is now personal, predictive, and profoundly local. And the brands that move first won’t just show up. They’ll stand out.

If you’re ready to meet customers where they are—and where they’re going—let’s get started.

The local search landscape is shifting fast

Google’s AI Overviews serve up rich, conversational answers at the top of results pages. Bing’s integration with ChatGPT turns searches into real-time dialogues. Apple Intelligence promises personalized insights without compromising privacy.

There’s a common thread: Customers now expect search to be faster, smarter, and deeply aware of their local context.

And the shift is bigger than better answers. It’s a full rewrite of what visibility and relevance mean for brands.

No more keyword-stuffing. No more hoping your listing shows up by chance. Winning now demands clarity, context, and real-time personalization.

According to Forrester’s 2025 B2B Brand and Communications Survey, 86% of marketing leaders say AI’s biggest impact will be driving efficiency. But efficiency isn’t the endgame; it’s about creating deeper, faster connections with customers at the local level.

Marketers who miss the shift risk becoming invisible.

Gen AI makes search a conversation, not a transaction

What sets Gen AI apart is its ability to understand not just what users are asking, but why. It draws on real-time context, past interactions, and nuanced preferences to deliver hyperlocal, highly personalized responses. 

Unlike traditional search personalization, which relied heavily on past clicks or basic history, Gen AI can carry forward context across sessions, remember intent signals, and fine-tune results in the moment based on evolving user needs. This allows the search experience to feel less transactional and more like an ongoing, intelligent conversation.

Picture the difference:

• A rainy morning search for “cafés near me” now suggests cozy spots with covered patios.
• A “hiking trails nearby” query during a heatwave highlights shaded, family-friendly paths.

The aforementioned searches don’t just answer. They anticipate. As evidenced in the previous examples, the search engine has access to real-time weather data and understands user intent. It then prioritizes results that fit the current conditions (e.g., covered patios on a rainy day).

While AI predicts patterns, human intelligence turns those patterns into lasting loyalty. The most successful enterprise brands are already:

• Using AI-powered tools to identify and act on local intent signals in real time
• Deploying integrated automation to move customers smoothly from discovery to decision
• Training customer support teams to collaborate with AI, freeing humans for complex, high-empathy moments

AI is an accelerator. But human strategy still sets the course.

Brands that master the balance of predictive AI and authentic human interaction will own the next chapter of local discovery.

Local matters more than ever

In a world of hyper-personalized, AI-curated search results, local answers are the ones customers trust first.

It’s why Forsta’s Human Experience platform helps brands understand customer experiences at every touchpoint. It’s why Rio SEO’s Local Experience platform drives accurate, localized engagement across hundreds (or thousands) of locations.

Winning locally in an AI era demands three things:

• Structured, clear data that AI can easily digest
• Localized, conversational content that sounds like your customers talk
• Mobile-first, fast-loading sites that meet users where they are (on their phones)
• Consistency in media, messaging, and attributes across platforms such as Google, Bing, Yelp, Nextdoor, etc. so AI agents can trust the information they’re using as inputs

And yet, despite the obvious urgency, not everyone’s moving fast enough. Gartner research shows that 27% of marketing teams still report limited or no Gen AI adoption.

That gap is your opportunity. But building local connections at enterprise scale takes more than good intentions. It takes precision.

Scaling local marketing with precision at every location

Managing local marketing at scale was never simple. Different regions, different behaviors, different rhythms of life. One blanket strategy quickly collapses under real-world complexity.

Enterprise brands managing hundreds or thousands of locations face a tough truth: personalization can’t be manual anymore.

Marketing AI changes the game.

Instead of chasing endless spreadsheets and disjointed updates, integrated automation now powers:

• Real-time local listing management
• Conversational, regionally-tuned content creation
• Reputation insights that surface and solve local issues before they escalate

When every location can dynamically update hours, promotions, and services, local teams stop fighting fires. They start building relationships.

It’s not just more efficient, but a smart investment for organizations ready to lead in an AI-first world.

And the results are already here. Brands using AI to personalize at the local level are seeing measurable gains in conversion rates, customer satisfaction, and long-term loyalty.

But scaling local success takes more than automation. It takes human intelligence steering the ship.

Winning teams use AI to amplify their strategy:

• Sharper audience segmentation based on real-world behavioral signals
• Smarter customer segmentation for hyper-targeted promotions
• Personalized recommendations based on real-time availability and context

This combination unlocks deeper user engagement and drives content marketing that feels alive, not canned.

Leading brands are creating dynamic, hyperlocal content that shifts with the seasons, responds to local events, and speaks like a neighbor, not a corporate script.

Because in local marketing, relevance shifts with every hour, weather report, event, and street corner.

Trust is the new currency

Privacy isn’t just a regulatory checkbox anymore but a brand choice that customers notice, measure, and act on. And in local marketing, trust is earned in seconds and lost in a heartbeat.

Customers expect brands to anticipate their needs naturally, without crossing the line into intrusion. They also expect consistency in brand, from local listings accuracy to consistent messaging and media across platforms.

The brands that strike the right balance between relevance and respect will be the ones customers stay loyal to, because trust travels faster than advertising.

Apple’s on-device AI approach has raised the bar: personalization without personal risk. Instead of sending user data to the cloud, it stays local, private, and under user control. For enterprise local marketers, it’s a solid example of how privacy-first strategies aren’t just ethical; they’re a competitive edge.

Here’s how marketing leaders can earn trust in the AI era:

• Be radically transparent about how AI-curated experiences are created
• Give users real control over how much personalization they opt into—and how much they don’t
• Use privacy-first technologies that keep sensitive location and preference data secure

Inconsistent listings? Over-personalization without consent? Data breaches? Each one creates cracks that competitors will race to exploit.

Winning locally isn’t just about being visible. It’s about showing up consistently and being trusted at every touchpoint. The brands that embed privacy, transparency, and respect into every interaction won’t just gain customers but will build loyal communities.

New channels, new competitive advantages

Local discovery means being everywhere your customers are looking, even when they don’t realize they’re searching. Here’s what this looks like in practice:

• A tourist uses their phone to find reviews of a restaurant they just passed
• A shopper snaps a photo of a product and expects instant nearby options to buy it
• A busy parent tells their voice assistant, “urgent care open right now,” without ever touching a screen

For enterprise local marketers, these aren’t edge cases. They’re now critical touchpoints for engagement and conversion.

Voice search, visual search, and mobile-first discovery are rapidly becoming primary paths to purchase. Brands that master these channels aren’t just found but favored.

Voice search is hyperlocal by design. It favors brands that speak like real people do, offering natural answers to real-world questions. Search engine optimization strategies must evolve, shifting from robotic keywords to conversational, human language.

Visual search turns curiosity into action in seconds. A single photo can unlock instant directions, reviews, and personalized content, if your assets are tagged, structured, and optimized correctly.

Recommended reading: Boost your local SEO with Location Page Schema: A complete guide

The brands leading this shift are overhauling their digital marketing strategies to:

• Embed natural language into local pages, FAQs, and offers
• Optimize images for visual recognition and local context
• Create frictionless, mobile-first experiences that meet customers mid-journey
• Build sentiment analysis into marketing workflows to fine-tune messaging in real time

AI-driven marketing doesn’t just support these experiences; it powers them at scale. Tracking behavior across marketing channels—from voice and visual to search and mobile—enables brands to gather the business insights needed to deliver more personalized, faster answers.

Email marketing campaigns that once blasted generic offers now trigger based on specific, real-world signals: voice queries, visual searches, and local intent data.

This is the new battleground for enterprise local brands.

The ones who align AI-driven insights with personalized content across every interaction will turn customer curiosity into conversion—and turn local moments into lifelong loyalty.

Key strategies to get ahead—and stay there

Enterprise marketers ready to lead must rethink their visibility, content structure, and customer engagement across every local touchpoint.

Here are five essential strategies to sharpen your local marketing workflows, boost visibility, and drive real business insights from every interaction.

1. Optimize for AI-curated results

AI Overviews reward clarity, credibility, and context. Get there by:

• Creating easy-to-digest summaries
• Using proper structured data on your local landing pages
• Highlighting unique, hyperlocal value points

2. Maintain high-quality local citations

Consistency is your ticket to trust. Keep your:

• Business names
• Addresses
• Hours
• Phone numbers

Ensure accuracy across all platforms.

Tools like Rio SEO’s Local Listings Management make it easier to control and correct information across hundreds of directories automatically.

3. Embrace conversational, localized content

Talk like your customers do. Build content that:

• Highlights local events
• Speaks to local interests
• Answers real-world questions in a natural voice

A neighborhood guide. Seasonal tips. Regional expertise. Let your brand sound in the know.

4. Leverage structured data

Schema isn’t optional anymore. Implement it to:

• Help AI recognize and recommend your business
• Power your appearance in AI Overviews
• Boost visibility with LocalBusiness, Place, and Review markup

5. Prioritize mobile-first, fast experiences

Gen AI surfaces answers instantly. If your page doesn’t load quickly or looks clunky on mobile, you’re out of the game.

Audit your site regularly. Leverage Google Core Web Vitals. Speed thrills and lag kills.

Challenges to keep on your radar

AI-driven search opens powerful new doors, but it also introduces new responsibilities for marketers. Leading the way in local search today means not just embracing new tools but managing the risks that come with them.

Here are three challenges every local marketing department should plan for, and how smart teams are turning them into strengths.

Privacy and data security: Protect trust at every touchpoint

Customers are willing to engage, but not at the cost of their privacy.
As AI curates increasingly personalized experiences, transparency about how data is collected, used, and protected becomes non-negotiable.

Brands that get sloppy with privacy protections risk more than fines. They risk losing loyalty.

Following privacy-first practices like on-device processing (similar to Apple’s model) and data anonymization helps marketers deliver personalized content while keeping customer trust intact.

Algorithm bias and transparency: Build fairness into every system

Gen AI reflects the data it’s trained on. That means biases can sneak into search results, recommendations, and content curation.

For enterprise local marketers, unchecked bias can mean unintentionally favoring certain locations, demographics, or customer types, eroding the trust AI is supposed to build.

Combatting bias requires:

• Diverse, inclusive training data
• Regular audits of AI-driven marketing workflows
• Clear communication with customers about how AI decisions are made

Transparency isn’t just ethical. It’s strategic. Brands that lead with fairness build deeper, more resilient relationships in every market they serve.

User control: Personalization without pressure

Personalized content is powerful. But customers don’t want to feel trapped by it. Offering users the ability to control how much personalization they receive, and what data they share, empowers them and strengthens loyalty.

This applies across all marketing channels, from search to email marketing campaigns to in-store experiences.

Smart marketers are weaving opt-in personalization settings into their workflows, making it easy for customers to adjust preferences based on comfort and context.

See how Rio SEO’s Customer Experience Solutions help brands create trusted, flexible local experiences that adapt to real-world customer needs.

Managing these challenges well doesn’t just reduce risks. It becomes a brand differentiator.

Gen AI’s future in search: What’s next?

Search is shifting from finding information to discovering experiences. In the next wave, expect:

• More personalized customer journeys powered by behavioral signals
• Augmented reality (AR) and virtual reality (VR) layering new dimensions onto search
• Predictive, proactive experiences where search engines anticipate needs before they’re even spoken

Marketers who lean into these innovations early will build brands that feel not just present, but essential in customers’ lives.

Generative AI is rewriting the rules of search—and rewriting the rules of customer connection along with it. Winning locally now means more than just showing up. It means showing up right, relevant, and ready.

The brands that succeed will be the ones that:

• Build trust by protecting privacy
• Make it effortless for customers to engage
• Stay nimble, moving with real-time insights and local nuance

AI isn’t replacing marketers. It’s empowering the best ones to work smarter, connect faster, and create experiences that truly resonate.

Ready to turn AI-driven search into deeper customer connections?

Explore Rio SEO’s AI technology to see how we’re powering better customer experiences at every touchpoint in the digital journey.