AI search is exposing a problem many multi-location brands have been able to hide for years: inconsistency across locations. In a world where AI systems recommend businesses rather than simply rank them, operational discipline at the location level may become one of the biggest competitive advantages in local marketing.

Multi-location brands have spent the last decade treating local visibility as a volume game. Build more location pages. Sync more listings. Respond to reviews. Track rankings. The logic was sound: more presence equals more performance.

AI-driven discovery is breaking that equation.

According to a Q2 2025 Whitespark study, AI Overviews now appear in 68% of local search queries — outpacing traditional local packs, which appear in just 39%. And consumer behavior is shifting just as fast: Yext’s 2026 Consumer Search Behaviors Report, which surveyed 3,848 consumers globally, found that nearly half of all U.S. adults used an AI tool to find a local business in the past month. Among households earning $150,000 or more, AI has already surpassed Google as the starting point for local business searches.

The implication is stark: being findable in a traditional search index and being surfaced by an AI system are two increasingly different things.

Rankings Still Matter. They’re Just No Longer Enough.

This isn’t an argument to abandon local SEO fundamentals. Accurate listings, review volume, and structured local content still matter — they’re the foundation AI systems build on. What’s changed is the standard a location must meet to be selected, not just surfaced.

AI-powered discovery doesn’t serve a list of links and let consumers sort it out. It summarizes, compares, and recommends. To be included in that layer, a location needs to be legible to the system doing the recommending — and that requires a level of consistency that many multi-location brands have never had to operationalize.

Being found and being recommended are now two different problems to solve.

The Aggregate Hides the Gaps

Here’s where most multi-location organizations are exposed: they evaluate local performance in aggregate. A brand with 400 locations of reviews, blended rankings, overall traffic trends, and network-wide review scores. The numbers look healthy. Leadership moves on.

What those dashboards hide is the variation between locations. One branch might have accurate service pages, up-to-date hours on every platform, and a healthy review profile with regular owner responses. Another location under the same brand might be running on generic copy, outdated hours, and a review page no one has looked at in months.

From a corporate reporting perspective, those two locations are equivalent data points. From the perspective of a consumer — or an AI model pulling from multiple sources to generate a recommendation — they are entirely different businesses.

The problem with aggregated performance metrics is that strong locations mask weak ones. In a traditional search environment, that trade-off was tolerable. In an AI-driven one, it’s a liability.

The Root Cause Is Operational, Not Technical

For many multi-location brands, inconsistent local data is the result of fragmented internal ownership. Website content is managed by one team. Listings by another. Reviews fall to local operators. Service information lives with operations. Each group works from its own platform, on its own timeline, with its own priorities.

Over time, that fragmentation shows up in the data. Hours fall out of sync across platforms. Service descriptions vary from one market to the next. Content goes stale.  

These aren’t new problems. What’s changed is how much they matter.

Whitespark’s 2026 Local Search Ranking Factors report — which surveyed 47 local SEO experts across 187 factors and introduced AI Search Visibility as a standalone category for the first time — found that inconsistent citations and conflicting data across platforms are now direct ranking liabilities, not just housekeeping issues. AI systems like Google’s AI Overviews, ChatGPT, and Perplexity triangulate from multiple sources to determine what a location offers, where it operates, and whether it’s credible enough to recommend. When those sources conflict, the system can’t form a confident picture, and a location it can’t confidently represent is one it’s unlikely to surface.

Recommendation Readiness Is Now a Competitive Differentiator

Getting cited in an AI answer is only step one. Yext’s 2026 consumer research found that only 5% of AI users act on a recommendation without any additional research. The other 95% verify — and they do it across multiple channels simultaneously.  

After receiving an AI recommendation, 62% immediately search Google for more information, 58% visit the business’s website directly, and 52% click through to the sources the AI cited. Critically, these verification rates hold nearly constant regardless of how much a consumer says they trust AI. Checking up on a recommendation is simply how modern purchase decisions get made.

This means showing up in an AI answer and then delivering a fragmented experience at verification — wrong hours on the website, a review profile that’s gone quiet, service descriptions that don’t match — doesn’t just create a bad customer experience. It actively loses the sale at the finish line.

When it comes to what actually converts a recommendation into a customer, Yext’s research found that review signals occupy five of the top six purchase influencers. Star ratings, review recency, and review sentiment consistently outrank price, proximity, and brand familiarity. These are the same signals AI systems use to determine credibility in the first place.

The brands that will outperform in this environment will be the ones with the highest degree of consistency across every location and structured content that gives AI systems something to work with.

Visibility compounds when the underlying data is clean and consistent. When it isn’t, AI systems don’t investigate — they simply route around the gaps.

The fundamentals haven’t changed. The margin for error has.

Less than two years after regulators blocked its proposed acquisition of Albertsons, Kroger is back in the acquisition market. This time, the company is taking a smaller and more targeted approach, announcing an agreement to acquire regional grocery chain Giant Eagle in a deal valued at approximately $1.65 billion.

At first glance, the transaction appears to be a straightforward geographic expansion play. Giant Eagle generates roughly $9 billion in annual revenue and holds strong positions across Pennsylvania, Ohio, West Virginia, Maryland, and Indiana — markets where Kroger has historically maintained a smaller presence, particularly around Pittsburgh and western Pennsylvania.

For agencies and brands, however, the larger story may be less about grocery consolidation and more about data, audience scale, and retail media.

Scale Matters More Than Ever in Commerce Media

Retail media has evolved well beyond sponsored product listings and digital coupons. Increasingly, retailers are building full advertising ecosystems that combine first-party purchase data, offsite media activation, closed-loop measurement, and connected television inventory.

Walmart has become one of the clearest examples of that evolution. Recent partnerships involving Walmart Connect, Magnite, Yahoo DSP, VIZIO, and Vibe have demonstrated how aggressively retailers are expanding beyond their owned properties and into broader advertising infrastructure. For competing retailers, that raises the stakes considerably.

Large advertisers increasingly want retail media partners that can provide not only closed-loop measurement but also national reach, advanced audience segmentation, and omnichannel activation capabilities. While regional chains often possess valuable shopper relationships, they frequently lack the audience scale required to compete with the largest retail media networks.

Kroger already operates one of the largest grocery retail media businesses through Kroger Precision Marketing, leveraging loyalty data from millions of households to power audience targeting and campaign measurement. The addition of Giant Eagle’s customer base, loyalty relationships, and transaction data further expands those assets at a time when advertisers continue shifting budgets toward commerce media.

Unlike the proposed Albertsons merger, which sought to create national scale through transformational consolidation, the Giant Eagle acquisition appears designed to strengthen Kroger’s position in adjacent regional markets while avoiding many of the regulatory challenges that derailed the larger transaction.

A Different Kind of Grocery Consolidation

Since the collapse of the Albertsons merger, many observers have questioned whether traditional grocers could continue competing with Walmart, Costco, Amazon, and Target without pursuing additional consolidation. Those concerns have only intensified as inflation pressures and changing shopping behaviors have pushed consumers toward larger retailers with stronger value propositions.

Giant Eagle itself has spent the past several years investing heavily in store renovations, pricing initiatives, and operational improvements while reshaping its portfolio around its core grocery business. Those moves arguably left the company better positioned as an acquisition target and made the fit with Kroger more straightforward than the larger Albertsons transaction ever was.

For Kroger, the deal offers a relatively clean way to expand market share without recreating the national concentration concerns that surrounded the previous merger attempt.

The Data Opportunity May Be Bigger Than the Store Opportunity

For marketers, the real value of grocery acquisitions increasingly lies in customer data rather than physical footprint. Retail media has fundamentally changed how retailers think about customer relationships, turning purchase behavior, loyalty activity, pharmacy engagement, and basket composition into valuable advertising assets capable of supporting audience targeting, attribution, and closed-loop measurement.

The competitive benchmark is increasingly being set by Walmart Connect, Amazon Ads, and other large commerce media players that can combine audience targeting, media activation, and sales attribution within a single environment.

Kroger Precision Marketing has long been viewed as one of the strongest grocery retail media businesses outside of Walmart. But in commerce media, scale compounds value. More households create stronger audience models. More transactions improve attribution. More loyalty engagement creates richer signals for segmentation and activation.

That makes Giant Eagle’s assets particularly attractive. Beyond the stores and revenue, the acquisition brings additional loyalty relationships, pharmacy data, and purchase histories into Kroger’s ecosystem. Those capabilities are becoming increasingly important for CPG advertisers, health and wellness brands, and consumer marketers that want to understand not simply who saw an advertisement but who ultimately made a purchase.

What It Means for Agencies and Brands

For agencies and brands, the acquisition reinforces a broader trend that extends well beyond grocery. Retailers increasingly compete not only for consumer spending but also for advertising budgets, and the winners are likely to be those capable of combining first-party data, media inventory, transaction measurement, and large addressable audiences into a single platform.

That dynamic helps explain why retailers continue investing heavily in audience products, in-store media, commerce partnerships, and advertising technology infrastructure. It also helps explain why acquisitions that may once have been evaluated primarily on store count and market share are increasingly judged by the quality and scale of the data they bring with them.

As retail media networks mature, advertisers are showing growing preference for platforms capable of delivering meaningful audience reach and standardized measurement across large geographic footprints. Regional players with strong customer relationships remain valuable, but increasingly they need larger ecosystems to fully monetize those assets.

More Than a Grocery Deal

Kroger’s acquisition of Giant Eagle is unlikely to reshape the grocery industry in the way the Albertsons transaction might have. It may, however, represent something equally important: the continued evolution of retailers into media companies.

Walmart’s recent moves involving Magnite, Yahoo DSP, VIZIO, and Vibe show how quickly the largest retailers are assembling commerce media ecosystems that extend well beyond their owned properties. Kroger’s acquisition of Giant Eagle does not replicate that strategy directly, but it strengthens one of the assets that underpins it all: first-party customer data at scale.

For agencies and brands, that distinction matters less than it once did. Retailers are no longer simply stores with advertising businesses attached to them. Increasingly, they are media companies with stores attached to them.

Imagine a billboard that changes based on the weather, local events, or what’s happening in the neighborhood around it. Big Happy says the next generation of 3D DOOH advertising is designed to do exactly that.

Which will it be, contextual relevance and visual impact? Brands that want both in the DOOH channel no longer have to choose. Ad-tech platform Big Happy has launched dynamic creative optimization (DCO) capabilities for 3D digital-out-of-home (DOOH) advertising that can integrate weather, location, and live environmental conditions into 3D DOOH executions all in the service of helping brands deliver more relevant messaging and stronger campaign performance.

With the advances in 3D creative, DOOH is no longer a static channel. Now these ads have motion quality, depth, and render fidelity that is necessary cinema-level creative.

Jonathan Frohlinger, CEO, Big Happy, sat down with StreetFight to provide more details on the launch of this new offering.

For multi-location brands and retailers, how can local marketers customize campaigns while maintaining brand consistency across markets?

Multi-location brands and retailers don’t have to choose between local relevance and brand consistency. By leveraging Dynamic Creative Optimization (DCO), brands can create a primary creative template that maintains consistent branding while dynamically tailoring key elements by market. This can include location-specific messaging, locally relevant product features, store information, regional promotions, and even local brand partnerships. DCO enables brands to deliver personalized, market-specific experiences at scale, helping local marketers connect more effectively with their audiences while ensuring every execution remains aligned with overall brand guidelines.

Can campaigns get so contextually granular that they respond beyond weather and location such as local events, traffic patterns, sports outcomes, air quality, or neighborhood-level audience behaviors?

DOOH screens refresh on a slower cycle than mobile, so DCO for DOOH works differently than it does in a browser or app environment. Creative assets have to be pre-built and mapped to triggers in advance; when a signal fires, the screen serves the matching execution rather than rendering something new in real time. Within that model, the range of triggers is broader than most expect. Weather and air quality can update on the hour. Location works at the proximity and DMA level. Local events can be targeted by geography, with creative tailored to specific moments — a game day, a festival, a product launch in market.

Is there evidence that dynamic 3D DOOH outperforms traditional 3D or standard DCO campaigns?

Early signals are strong. Recent industry research shows that 3D and CGI creative in out-of-home already drives significantly higher recall, engagement, and business outcomes than standard formats. What we’re seeing in our own initial testing is that layering real-time dynamic triggers on top of that creative amplifies the effect further — because the message isn’t just visually hitting you, it’s also relevant to exactly where you are and what’s happening around you. As we scale this across more brands and regions, we expect that lift to grow.

How does the platform handle creative production at scale when every screen or market could potentially require different versions of a 3D asset?

With Big Happy, the decisioning happens within our ad server itself — meaning the ad server evaluates real-time signals (weather, location, pollen counts, etc.) at the exact moment an impression request is received and determines which creative to serve on the spot. Big Happy’s ad server can not only handle the decision-making needed to serve particular 3D DOOH creatives based on these dynamic triggers but is still able to respond to SSP calls to our VAST tag in ~100ms on average. Why is this important? The industry gives you ~500ms to 2s before a screen gives up and skips the ad. The result is a 3D ad that not only gets served fast, but it actually renders and plays smoothly. Ads that render are ads that perform, and that’s what advertisers pay for.

What role do automation and AI play in generating and managing those creative variations?

This is an area where Big Happy has a genuine edge. Our compression and rendering workflows are built to move fast. Once a concept is finalized, we can version, re-render, and compress a large number of creative variations at a fraction of the time it takes most producers. AI-assisted creative tooling handles the versioning work, producing the full set of executions that our ad server then picks up and delivers in real time, serving the right version to the right screen based on whatever dynamic trigger is in play. The result for brands is faster time to market without sacrificing creative quality. It’s something we’ve been quietly building for years, and it’s now one of the most powerful parts of how we bring dynamic 3D DOOH to life at scale.

How are you attributing outcomes from dynamic 3D campaigns, and what KPIs are brands most focused on today?

One of the biggest misconceptions about DOOH is that it’s only an awareness channel. While it’s incredibly effective at building awareness and consideration, it’s also highly measurable and increasingly capable of driving lower-funnel outcomes. Today, brands can measure everything from foot traffic and store visitation to CPG sales, streaming subscriptions, app downloads, and other conversion metrics.

What differentiates Big Happy’s approach from existing DCO solutions in the market?

Most DCO in out-of-home has always forced a tradeoff: you could have dynamic messaging, or you could have stunning creative, but rarely both. We’ve built our reputation on CGI and 3D production that genuinely stops people, the kind of work that makes consumers look at advertising differently. Now we’ve paired that with a contextual trigger engine with DCO, built directly into our ad server, pulling real world signals and connecting with media owners and screens to deliver the right version at the right moment. Brands no longer have to sacrifice creative impact to deliver a relevant message. You get both, and that’s what makes this a genuine game changer for the DOOH market.

As brands demand greater accountability from every media channel, the distinction between awareness and performance continues to blur. If Big Happy is right, the future of DOOH may not simply be three-dimensional. It may be contextual, responsive, and increasingly intelligent.

Google’s new Search Agents could fundamentally change local discovery by moving from answering questions to finding businesses and completing transactions on behalf of consumers. This means location pages, booking flows, and local data consistency may soon matter more than rankings alone.

Google is adding Search agents to Google Search, beginning with information agents that run continuously in the background, monitoring the web on a user’s behalf and surfacing relevant updates with options to act. Alongside this, Google is expanding agentic booking capabilities directly within Search for local services and experiences.

How Search Agents Work for Local Search

Rather than waiting for a user to initiate a query, Search agents run standing instructions. A user defines what they want once: the service, the location parameters, the price range, the availability requirements.

The agent then continuously monitors everything Google indexes and delivers a synthesized update when it finds a match, along with a direct path to transact wherever one exists. The possible use cases for local search are many. Think:

• A user tells their agent to find a physical therapy clinic accepting new patients within ten miles.
• Another instructs it to monitor for oil change specials at nearby auto service shops.
• A third asks it to find a fitness studio with morning class availability starting next week.

In each case, by the time the agent surfaces a result, the user has already done much of their decision-making. The business that gets surfaced first is likely to get a booking before the customer ever visits their site.

What This Means for MULOs

A national or regional brand with dozens or hundreds of locations cannot treat agent-readiness as a single website audit. Each location needs to be findable, accurate, and actionable on its own terms.

Consider a family restaurant chain with 80 locations. A user’s Search agent is looking for a family restaurant with availability for a family of four on Sunday within five miles of a specific zip code.

Whether that brand appears in the result depends not on the national homepage, but on whether the individual location page for that zip code reflects current hours, availability signals, and a clear path to make a reservation. If half of those location pages are thin, outdated, or lack any booking functionality, the brand loses half its potential coverage in agentic search before a single query is run.

The same applies to service businesses with distributed footprints: home services franchises, dental and vision chains, automotive service brands, fitness studios, and similar categories where the transaction is inherently local even when the brand is national.

Location Pages Are the Unit of Optimization

For MULOs preparing for agentic search, the location page is the critical unit of optimization. Each location page needs to function as a complete, actionable destination.

That means current and accurate information: hours that reflect seasonal or location-specific variations, services offered at that specific location rather than a generic brand-level list, and pricing or promotional content that is actually relevant to that market. It also means transactional capability: a booking form, an appointment scheduler, an order system, or at minimum a direct contact path that does not require the user to navigate away and start over.

Google has published guidance on what makes a website navigable for AI agents, and the requirements align closely with long-standing best practices for local SEO and web accessibility. Agents parse pages using HTML structure, visual analysis, and accessibility trees.

Pages with stable layouts, semantic HTML, properly labeled form fields, and visible interactive elements are pages agents can act on. Pages that hide booking flows behind modal windows, load availability calendars through opaque third-party scripts, or bury location-specific CTAs beneath brand content are pages agents will struggle to convert on, regardless of whether they surface the result.

The Consistency Problem at MULO Scale

For multi-location brands, inconsistency across location pages could create unpredictable agent behavior. If some location pages have an appointment booking widget and others have a “call us” link, agents will be able to complete transactions at some locations and not others. If interactive elements are implemented differently across a templated location page system, some will be actionable and some will not, often for reasons that are not obvious from a human review.

This is a problem that single-location businesses do not face in the same way. For MULOs, the question is not just whether the template is agent-friendly, but whether it has been implemented consistently across every location in the system.

A franchise brand where individual franchisees have customized their location pages, or a regional chain that has acquired locations with legacy web infrastructure, is likely carrying significant inconsistency that can affect agentic search performance at the location level.

What Agencies Should Be Doing Now

Google Search agents are rolling out in summer 2026, alongside continued expansion of agentic booking in Search. For agencies managing multi-location clients, now is the time to start ensuring location pages are agent-friendly.

For each location, audit whether an AI agent can find it, understand what it offers, and complete a transaction. If not, the brand is leaving agentic search coverage on the table. The good news is that the work required to make pages agent-friendly overlaps substantially with existing local SEO best practices. The key to maximizing conversions in agentic local search will be ensuring consistent agent-readiness across every location in a brand’s portfolio. A brand that is only 80% optimized for agentic search has 20% of its locations that agents cannot fully act on. If a competitor has done the work across all of their locations, that gap is a competitive liability.

As retailers strengthen their hold over shopper data, multi-location brands are searching for new sources of customer intelligence. The next major first-party data channel may not be digital advertising or loyalty programs, but the package already sitting in a customer’s hand.

There was a point in time when it looked like ecommerce would swallow up retail whole. But it hasn’t quite worked out like that; online sales growth has slowed to a steady single-digit pace across most mature markets after the heady heights of the pandemic years.

Ecommerce now accounts for around 16.6% of all US retail sales, according to the latest Census Bureau figures, which means roughly one in six retail dollars is spent online, with physical stores still taking the rest. For multi-location brands, this should be good news. But in practice, the uncomfortable truth is that brands are digitally blind on the physical shelf.

Retailers collect rich shopper data through their loyalty schemes, but those insights stay with the retailer. Brands selling through third-party stores rarely see who bought their product, and largely depend on someone else’s closed-loop program for a relationship that should belong to them. The first-party data that fuels modern marketing, the kind that drives personalization and co-branding opportunities, is just out of their reach.

There is a channel that brands control completely, yet many still treat it as passive cardboard: packaging.

The package is a media channel brands already own

Every product a brand sells is a physical touchpoint already in the customer’s hand. A connected package, (built around a QR code or NFC tag), turns that touchpoint into a two-way communication channel. A shopper scans, and the brand can deliver a product story or a localised offer. It could even be a gateway to an AI-powered assistant that answers questions about ingredients and provenance. Layering this technology onto the package also allows brands to capture location-based engagement data directly, without waiting for a retailer to share it.

As the technology matures, this becomes more important. The fifth annual Connected Packaging Survey, which gathered responses from 712 executives across sectors including retail, FMCG, and hospitality, found that 81.2% of respondents had already used connected packaging, up from 72.6% a year earlier. Industry confidence in its growing importance reached 92.3%, showing clearly that connected packaging has moved well beyond the experimental phase and is fast becoming standard practice.

What brands really want from this channel is data. Data collection ranked as the leading reason for using connected packaging in the survey, cited by 60.9% of respondents, ahead of factors such as compliance, sustainability, and loyalty. Brands are mining this data for the same reason they once invested in ecommerce analytics – they want to understand the customer at the point of purchase.

Disintermediation runs in reverse

Furthermore, this type of technology built into packaging gives brands the chance to bypass retailer disintermediation. When a shopper scans a package in a store aisle, or at home, the brand learns things it couldn’t have known previously, such as when and where the product was scanned, and what the customer chose to do next. These insights flow into the brand’s own CRM and data platform rather than disappearing into a retailer’s loyalty database.

Engagement on an interactive, tech-enabled package tends to run far higher than on interruptive digital media, because the shopper has already made the active choice to scan. They have the product in their hands, and interaction rates comfortably outperform the low single-digit response brands have come to expect from social and display advertising.

One package, many localized stories

Another advantage of this technology is that the destination the scan leads to can be changed. This flexibility makes the channel valuable for brands operating across many locations and regions.

For a national brand running a seasonal promotion, rather than reprinting packaging for a Halloween push and doing it again for a winter campaign, the digital experience behind the existing code can be updated. A shopper in one region can see a local stockist offer while one elsewhere sees content relevant to their market. The same package serves different stories based on where and when it is scanned.

Brands have grown used to buying audience access on retailer apps and in-store screens, but too often they have overlooked the product itself. It reaches every buyer, involves no media wastage because every scan comes from someone holding the product, and offers the reporting and dynamic content possibilities brands expect from digital advertising. The next evolution of retail media will not live only on screens and app menus, but on the package at the point of sale too.

The compliance tailwind

Brands considering updating their packaging with this storytelling, interactive technology should also be aware of fast-approaching deadlines. The GS1 Sunrise 2027 initiative, led by GS1 US, calls for every retail point-of-sale system to read 2D barcodes such as QR codes by the end of 2027. Walmart, Dillard’s, Kroger, and Target are already preparing, and brands that delay risk friction at retailers that are moving swiftly in this area.

For any product sold through US stores, a scannable digital identity will be a condition of doing business. The survey found compliance cited by 60.7% of respondents as a reason for adoption, nearly level with data collection. A brand can think of this mandate simply as a cost, or alternatively as an investment in a foundation for a data and engagement channel.

Start treating packaging as infrastructure

The brands making headway no longer think in one-off campaigns, but treat the package the way they treat their website, as a permanent channel that can update with the changing seasons and sales promotions. The data reflects this commitment, with 83.3% of respondents planning a connected packaging campaign this year, and 34.5% having created dedicated roles to manage the channel.

Physical retail is becoming measurable in a digital sense. For multi-location brands that don’t want to rely on retailers for their customer relationships, the most powerful data channel is sitting on the shelf, waiting to be switched on.

Broadsign, Global Netherlands, and Draft Digital have demonstrated what may be the first fully agentic OOH (out-of-home) campaign, with autonomous AI agents handling everything from media planning to campaign execution. The project offers an early glimpse into how AI could reshape media buying, hyperlocal targeting, and the future role of marketers.

Broadsign and Global Netherlands teamed up to use AI agents, which successfully planned, booked, and executed a fully AI-powered agentic OOH campaign for Lot of Happiness on OOH inventory.

In a first for the medium, Broadsign’s sell-side AI agent and digital marketing agency Draft Digital’s buy-side agent worked together. They completed audience and venue targeting, media selection, campaign setup, creative workflow and approvals, and execution based on the campaign goals.

Broadsign’s Chief Technology Officer Bryan Mongeau sat down with StreetFight to go into more detail.

If AI agents can autonomously plan and execute OOH campaigns, how might that change the role of local market expertise in selecting the right neighborhoods, venues, and screens?

Roles will change over time, freeing buyers from having to engage in low-value toil and enabling more strategic steering of campaign plans vs their objectives. Over time, buy-side agents will learn from these inputs and become increasingly sophisticated, eventually incorporating that local market expertise and knowledge that goes into selecting the right assets to meet a campaign’s goal.

How can AI-driven OOH buying better account for hyperlocal context, such as foot traffic patterns, community behavior, or time-of-day nuances, rather than just optimizing for scale and efficiency?

With traditional OOH buying, successfully implementing that hyperlocal context is hard. Foot traffic data needs to be cobbled together across media owners, and booking a lot of time-of-day tranches across many screens and many media owners can be hard to do.  AI-driven agentic OOH buying can apply the data overlays upstream and completely automate even the most complicated hyperlocal campaigns.

What does fully automated OOH buying mean for smaller, independent media owners or local operators?

We believe that for smaller operators, agentic OOH buying will help them get their fair share of the media budget when responding to campaign briefs. In particular, the traditional manual buying process entails a lot of back and forth with media owners, which disincentivizes including a few niche screens here and there, even if they index better against the target audience. Automated buying solves that.

How might this kind of agentic workflow impact the way creative is localized, especially when messaging needs to reflect specific communities or cultural moments?

In traditional OOH, dynamic creative execution across media owners is challenging.  Multiple video formats, resolutions, regulations, exclusions and varying DCO capabilities create a lot of friction. Buy-side agents can understand all these parameters and take hyper-local input data and serialize it down to each screen’s preferred format, making community and culturally aware creative easier to execute.

With AI agents handling everything from targeting to execution, where should human oversight remain, particularly when campaigns intersect with local sensitivities or public Spaces?

The campaign plan that the agents produce should still be reviewed by agency experts and the advertisers themselves to ensure it meets the campaign objectives. Media owners still need to approve the creative coming through to ensure compliance with local regulations and restrictions.  Pacing of spend should also be monitored from time to time to ensure the right adjustments are being made along the way. 

Could this technology enable more real-time, event-driven local activations (e.g.,weather, sports wins, neighborhood events), and what infrastructure is still needed to make that viable at scale?

Agentic buying workflows can help get these types of campaigns booked quicker and with less friction.  Event-driven local activations often require dynamic creative, which buy-side agents can help create as well.

As OOH becomes as easy to buy as digital media, how should brands rethink the role of physical-world touchpoints in their local marketing mix, especially in bridging online-to-offline engagement?

OOH is a powerful vehicle for brands, especially for bridging that online-to-offline engagement. Clever marketers can now weave narratives that flow from physical to digital touchpoints seamlessly.  The right OOH creative in a high-trust public space can drive brand awareness and initiate digital follow through by QR code, short urls, hashtags, or simply by looking it up.

Walmart has spent the past several years quietly building one of the most formidable advertising businesses outside of the traditional digital giants. What began as a retail media effort designed to monetize shopper data is increasingly evolving into something much larger: a full-funnel advertising ecosystem capable of competing for budgets that have historically flowed to Google, Meta, Amazon, and television.

That ambition was on display this week when Walmart announced plans to acquire Vibe.co, a self-service connected TV (CTV) advertising platform focused on small and mid-sized businesses and mid-market brands. While the acquisition is being positioned as a way to make CTV advertising more accessible, it also reflects Walmart’s broader effort to build a commerce-driven advertising platform that spans audience targeting, media activation, measurement, and business outcomes.

The move also arrives just weeks after Walmart expanded access to Walmart Connect audience data and measurement capabilities through partnerships with Magnite and Yahoo DSP. Viewed together, the announcements suggest Walmart’s ambitions extend well beyond traditional retail media and point toward a broader effort to become a significant force in commerce-driven advertising.

Walmart Is Building More Than a Retail Media Network

Retail media networks have emerged as one of the fastest-growing segments of digital advertising, largely by helping brands reach consumers close to the point of purchase using retailer-owned data and media inventory. Walmart’s strategy increasingly extends beyond that model.

Walmart’s acquisition of VIZIO in late 2024 gave the retailer a significant connected TV footprint and strengthened its ability to connect media exposure with commerce data. The Vibe acquisition builds on that foundation by bringing in a platform specifically designed to simplify connected TV advertising for performance marketers, ecommerce businesses, and smaller advertisers that often lack the resources required to navigate traditional television buying.

Vibe’s self-service platform allows advertisers to launch campaigns quickly, access premium streaming inventory, and optimize performance through automated tools. Walmart says the combination will help more advertisers activate CTV campaigns while leveraging Walmart’s audience data, closed-loop measurement capabilities, and growing media ecosystem.

The broader significance is that Walmart continues moving beyond its origins as a retail media network and closer to becoming a comprehensive advertising platform capable of serving advertisers throughout the marketing funnel.

This Is the Second Major Advertising Move in a Month

The Vibe acquisition becomes more significant when viewed alongside Walmart’s recent partnership with Magnite.

Earlier this month, Walmart expanded access to Walmart Connect audience data and measurement capabilities through Magnite and Yahoo DSP. That move signaled a shift toward a more open retail media ecosystem by allowing advertisers to activate Walmart’s commerce intelligence through platforms they already use rather than requiring them to operate exclusively within Walmart-owned buying environments.

Viewed alongside the Vibe acquisition, a consistent strategy emerges. The Magnite partnership made Walmart’s audience data easier to access, while Vibe makes connected TV easier to activate. Together, the initiatives reduce friction for advertisers while expanding Walmart’s role across audience targeting, activation, measurement, and commerce outcomes.

Industry observers see these moves as part of a broader shift occurring within connected TV.

“Performance CTV is moving from the edge of the media plan to the center of the growth conversation,” said Leif Welch, CEO of JamLoop. “Large platforms are investing here because advertisers are asking for more than reach. They want streaming TV to be easier to activate, easier to measure, and tied to outcomes they can defend.”

For agencies and multi-location brands, that may be the more important signal. Walmart is no longer simply building a retail media network. It is increasingly positioning itself as a commerce-driven advertising platform that spans audience targeting, activation, connected TV, and closed-loop measurement.

Bringing More Advertisers Into Connected TV

For decades, television advertising largely remained the domain of large brands with substantial budgets and agency support. Even as streaming platforms expanded inventory and programmatic buying simplified transactions, many small and mid-sized businesses continued to view TV advertising as expensive, complex, and difficult to measure.

Vibe’s value proposition was built around changing that perception. The platform was designed to make streaming television advertising operate more like paid social media, emphasizing self-service campaign activation, simplified workflows, performance optimization, and measurable outcomes. Walmart executives believe that approach can help unlock broader adoption of connected TV advertising among SMBs, mid-market companies, and Walmart Marketplace sellers.

That audience represents a meaningful growth opportunity. Much of connected TV’s next phase may come from advertisers that have traditionally concentrated spending on search, social media, local media, and other performance-oriented channels.

“The mid-market is now a major battleground,” Welch said. “Vibe’s positioning has centered on performance marketers, SMBs, and self-service. Walmart’s language reinforces the same point: advertisers want CTV to be more accessible, more measurable, and more accountable to growth.”

That focus is particularly relevant as connected TV platforms look beyond large enterprise advertisers for future growth. Many SMBs, franchise organizations, and mid-market brands have historically been underserved by traditional television buying models despite increasing interest in streaming video advertising.

Connecting Commerce and Television

Perhaps the most important aspect of the deal is how it strengthens Walmart’s ability to connect advertising exposure with business outcomes.

Connected TV has long been attractive because of its premium content, large-screen viewing experience, and growing audience reach. However, marketers have often struggled to understand how television exposure translates into actual purchasing behavior.

Walmart is attempting to address that challenge by combining Vibe’s campaign activation capabilities with Walmart Connect’s commerce data and closed-loop measurement infrastructure. The goal is not simply to help advertisers buy streaming television inventory but to help them understand whether those campaigns influenced shopping behavior and revenue outcomes.

That strategy mirrors broader shifts occurring across the advertising industry. Increasingly, marketers want channels that can support both brand-building objectives and measurable business results. Retail media networks possess a unique advantage because they sit much closer to actual purchase behavior than most traditional advertising platforms.

What It Means for Brands and Agencies

For agencies and multi-location brands, the acquisition represents another sign that the lines separating retail media, connected TV, and performance marketing are disappearing.

Historically, these channels were planned, purchased, and measured separately. Today, advertisers increasingly want integrated systems capable of connecting audience targeting, media activation, attribution, and sales outcomes within a single workflow.

The combination of Walmart Connect, VIZIO, marketplace data, commerce measurement, the Magnite partnership, and now Vibe’s self-service CTV platform creates a more comprehensive advertising ecosystem that can serve both large national advertisers and smaller businesses.

Welch believes that ecosystem is becoming increasingly powerful. “With VIZIO, Walmart Connect, commerce data, and now Vibe, Walmart is building a powerful CTV and retail media ecosystem,” he said. “But the more the market consolidates around large platforms, the more independence matters for advertisers that want flexibility, transparency, and control across channels and markets.”

Walmart’s latest move is about more than connected TV. Together with its VIZIO acquisition and recent Magnite partnership, the deal reflects a larger strategy to connect retail media, streaming television, commerce data, and performance measurement into a unified advertising platform.

The future of local marketing may depend less on generating leads and more on connecting marketing activity directly to business outcomes. The Scorpion acquisition of 1SEO reflects a growing industry shift toward AI-powered platforms that help businesses compete in an increasingly complex discovery environment.

Artificial intelligence is rapidly changing how consumers discover, evaluate, and choose local businesses. Search results are becoming AI-generated answers. Business recommendations increasingly come from conversational interfaces. Visibility is no longer determined solely by rankings and websites, but by how well a business is represented across the digital ecosystem that AI systems rely on to inform decisions.

That shift sits at the center of Scorpion’s acquisition of Philadelphia-based 1SEO Digital Agency, announced this week, and helps explain why the deal is about far more than expanding a client roster. While the transaction strengthens Scorpion’s position across key verticals including home services, legal, health, and franchise marketing, it also reflects a broader transformation underway in local marketing. As AI reshapes customer discovery, agencies are facing growing pressure to invest in technology, automation, data infrastructure, and performance measurement systems that help businesses compete in a rapidly evolving environment.

“For nearly two decades, 1SEO has served local businesses in many of the same verticals we know best: home services, legal, and franchise,” Jamie Adams, Chief Revenue Officer at Scorpion, told Street Fight. “What drew us to them was the depth of trust they built with their clients, and our confidence that Scorpion’s digital marketing solutions and technology would meaningfully expand the revenue growth their clients can achieve.”

The acquisition gives 1SEO clients access to Scorpion’s broader technology platform, including RevenueMAX and a series of operational integrations designed to connect marketing activity directly to business outcomes. More importantly, the deal offers a glimpse into how AI is reshaping local customer acquisition.

AI Is Reshaping Local Discovery

For years, local marketing largely revolved around rankings, websites, and lead generation. Businesses focused on appearing in search results, driving traffic, and converting prospects into customers. Those fundamentals still matter, but AI is changing the customer journey. Consumers are increasingly encountering businesses through AI-generated summaries, recommendations, reviews, and conversational search experiences before they ever visit a website.

The signals influencing those recommendations extend beyond traditional SEO to include business data, reviews, reputation signals, and content distributed across the web. As a result, local businesses need more than visibility. They need systems that help them understand how they are being represented across search, AI discovery platforms, and digital channels while providing the ability to respond quickly when performance shifts.

Adams believes this shift is already reshaping the competitive landscape.

“AI is fundamentally changing how local businesses get found and chosen online,” he said. “Our focus on building AI-driven solutions and adding more talent to our team through this acquisition puts us in a better position to help our customers navigate that shift.”

The acquisition also highlights another trend reshaping local marketing: the convergence of marketing technology and business operations. Historically, marketing platforms operated separately from the software businesses used to run day-to-day operations. Marketing teams measured traffic, leads, and conversions, while operational systems tracked appointments, customer activity, staffing, and revenue. Those worlds are increasingly coming together as businesses seek a clearer connection between marketing investments and business outcomes.

Scorpion has spent the last several years building integrations that connect marketing performance directly to operational outcomes. In home services, the company maintains an exclusive preferred partnership with ServiceTitan, enabling businesses to connect marketing activity with technician availability, booked jobs, and capacity management. In legal services, Scorpion holds a similar preferred partnership with Clio, allowing firms to connect marketing investments to retained clients and revenue generation.

For local businesses, generating additional leads has limited value if operational capacity is already constrained. Increasingly, brands want visibility into how marketing influences revenue rather than simply traffic. That demand is helping fuel the emergence of technology platforms built around the unique operational requirements of specific industries.

Why Technology Is Driving Consolidation

The economics of building those platforms are changing the agency landscape.

As AI becomes more deeply integrated into marketing workflows, agencies face growing pressure to invest in automation, analytics, attribution, visibility intelligence, and optimization capabilities. Building those systems requires significant resources, making it increasingly difficult for smaller firms to keep pace with larger, technology-focused competitors. For firms like 1SEO, joining a larger platform creates access to capabilities that would be difficult to replicate independently.

That dynamic appears to have played a role in the transaction, with both organizations emphasizing technology and future platform capabilities as key drivers of the deal.

“We considered many sophisticated acquirors out there,” said BJ Bergey, CEO of 1SEO. “Scorpion stood out because of their intentional investment in the technology they’ve built for local businesses and in the performance and returns they’ve driven for their clients over the last 25 years.”

Bergey will remain with the combined organization following the acquisition, helping guide client success and growth initiatives. His continued involvement reflects the importance both companies place on preserving client relationships while introducing new technology capabilities.

The emphasis on technology mirrors a broader evolution occurring across the agency landscape. Increasingly, acquisitions are being evaluated not only on client overlap or geographic expansion but on the ability to accelerate product development, AI adoption, data capabilities, and technology differentiation.

What It Means for Agencies and Multi-Location Brands

For agencies, the acquisition underscores the growing importance of technology ownership as a competitive advantage. Many firms continue to rely heavily on third-party platforms and software vendors, but that model becomes increasingly challenging as clients demand deeper visibility into outcomes, faster optimization cycles, and stronger connections between marketing activity and business performance.

The implications are equally relevant for multi-location brands. Managing hundreds or thousands of locations creates operational complexity that traditional marketing workflows often struggle to address. The ability to connect media spend, lead generation, staffing capacity, customer acquisition, and revenue performance into a unified system is becoming increasingly valuable.

The distinction between marketing vendor and technology platform continues to blur as brands seek partners capable of delivering both execution and measurable business outcomes.

A Signal of Where Local Marketing Is Headed

Scorpion’s acquisition of 1SEO is ultimately a bet on where local marketing is headed. As AI changes how consumers discover and evaluate businesses, the competitive advantage increasingly belongs to companies that can combine trusted client relationships with the technology needed to navigate that shift.

The next phase of local marketing consolidation looks to be driven less by geography or client count and more by building the technology infrastructure that helps local businesses compete in an AI-driven world.

Despite commanding some of the highest levels of consumer trust in media, local media continues to lose brand advertising budgets to platforms with far weaker audience relationships. The problem isn’t reach or relevance, but an inability to measure and communicate the value of trust in terms brands can buy.

Local media owns something the rest of the advertising industry spends billions trying to manufacture: trust.

That is not a feel-good line. In Pew Research Center‘s 2024 study, 74% of Americans said they trust their local news organizations, well above the trust they place in national news. 85% called local outlets at least somewhat important to their community, and roughly 7 in 10 said local journalists are genuinely in touch with the places they cover. Add the reach and attention that local television and radio still command in their markets, and local media holds a rare combination: large audiences, deep trust, and real community context.

And yet local media keeps losing budget to platforms that can prove far less about the people they reach. That is the paradox. The most trusted, most-attended inventory in American media is losing the budget war to inventory that is simply easier to measure.

The Most Trusted Inventory Is the Hardest to Price

The instinct is to treat this as a content problem or a reach problem. It is neither. Local audiences are not smaller or less engaged than they used to be; if anything, trust in local news has held while trust in nearly everything else has eroded.

And trust travels with attention. A local newscast or a morning radio show is appointment viewing in a way an autoplay feed never is. People watch it on purpose. They lean in. And they do it in the place they actually live. That kind of engaged attention is exactly what advertisers are now chasing across every channel. 

It is also exactly what legacy measurement is worst at capturing. Reach it can estimate. Genuine attention it tends to miss, which means local’s most valuable quality is the one least likely to show up in the number a buyer sees.

The problem is that trust and attention are not denominated in anything a buyer can set next to a programmatic line item. The value is real. The unit of account is missing. A buyer cannot spend trust, they can spend a number, and local media has too often arrived at the table with the wrong one.

Local media earns the trust and loses the budget.

A Measurement Model Stuck in the Past

You can see the value most clearly when the money is biggest. 2024 was the most expensive political cycle on record. Total spending topped $10 billion, with an estimated $11.7 billion flowing into local markets, up over 21% from 2020, according to BIA Advisory Services. Roughly 40 to 45% of national political dollars went to over-the-air local broadcast. When the stakes are high enough, buyers pay a premium for trusted, local, high-attention environments. They know exactly what local delivers.

The problem is the rest of the calendar. Outside the political surge, local’s value gets measured with models built for a narrower era. The centralized, global panels buyers lean on were never built for US local at DMA and zip resolution, the level at which auto, QSR, retail, and healthcare budgets are actually decided. 

National averages smooth away exactly what makes a local market valuable. If you can’t show the audience clearly, you can’t price it properly, and undervalued inventory is how budgets quietly migrate to channels with cleaner proof, even when those channels deliver less.

More Than Ad Dollars

The stakes here run past any single rate card. The same local newsrooms advertisers say they trust are disappearing. Northwestern’s Medill State of Local News found roughly 127 newspapers closed in a single year, nearly two and a half a week, part of a decline of about 3,300 since 2005. More than half of US counties now have little or no local news, and more than 200 are full news deserts, with no local source at all.

That collapse is, at its core, a business-model failure: when local outlets cannot prove their value to advertisers, they lose the revenue that funds the journalism. Modern measurement is not only an ROI exercise for local media. For many outlets, it is the difference between funding next year’s coverage and going dark.

And the stakes are economic as much as civic. Local media is where local businesses reach their customers: the auto dealer, the regional bank, the hospital system, the QSR franchisee. When that marketplace erodes, the advertisers who depend on it lose their most trusted route to an audience, and the community loses a piece of its economic connective tissue. Measurement that proves local’s value keeps that marketplace funded on both sides: the outlets that inform a community and the businesses that sustain it.

From Trust to Confidence

Closing the gap does not require building a bigger audience. Local already has the audience, and it already has the trust. What’s missing is a way to express both in the terms buyers transact in: attention that is measured, behavior that is tracked, outcomes tied back, all at the resolution local actually operates in, not national averages.

The number a buyer believes is the number that gets priced. Right now, local is letting legacy tools shape that belief. Change the measurement, and you change the pricing conversation. You turn the trust local has already earned into confidence a buyer can act on.

That is the most valuable conversion in media today. And unlike the audience or the trust, it is something local media can still build.

Political advertising has long served as a testing ground for innovations that eventually make their way into mainstream marketing. Campaigns operate under compressed timelines, face relentless pressure to prove effectiveness, and often have only a single opportunity to influence behavior before Election Day. As a result, many of the strategies developed in political media—from audience targeting and measurement to omnichannel orchestration and real-time optimization—frequently become relevant to brand marketers as well.

That dynamic helps explain the launch of The Political Desk, a new specialized division from programmatic media agency Digital Remedy designed to help political campaigns, advocacy groups, and issue-based organizations manage voter outreach across multiple channels. While the initiative is aimed squarely at political advertisers, many of the challenges it addresses will sound familiar to agencies and multi-location brands navigating an increasingly fragmented media environment.

“Political campaigns today are operating in one of the most fragmented media environments we’ve ever seen,” said Matt Fanelli, CRO of Digital Remedy, in announcing the launch. “Campaigns need more than reach—they need transparency into where their media is running, how frequently voters are being exposed to messaging, and whether spend is actually driving incremental impact.”

The same pressures increasingly apply to brand marketers. Brands are expected to understand local market performance, coordinate messaging across channels, demonstrate measurable impact, and react quickly as consumer behavior shifts. Political campaigns simply face those challenges on a compressed timeline.

Hyperlocal Measurement Reveals What Market-Level Data Misses

One of the biggest challenges facing political advertisers is determining where media investments can have the greatest impact. While campaign reporting often rolls up to broader market definitions such as DMAs, the realities on the ground are far more nuanced.

Fanelli points to Arizona as an example. Two congressional districts may exist within the same media market, yet one could represent a highly competitive race while the other is effectively decided. Without district-level visibility, both districts appear similar in a traditional report despite having dramatically different strategic value.

The lesson extends well beyond politics. Brand marketers frequently encounter the same problem when evaluating performance across regions. Market averages can obscure meaningful differences in consumer behavior, competitive dynamics, and media efficiency at the local level. One trade area may be generating strong incremental growth opportunities while another is already saturated. Without more granular measurement, those distinctions can be difficult to identify.

As marketers increasingly seek store-level attribution, neighborhood-level targeting, and localized performance insights, political advertising offers a preview of where measurement continues to evolve. The future is likely to be less about understanding how a market performs and more about understanding which specific parts of that market deserve attention.

Omnichannel Doesn’t Mean One-Size-Fits-All

Another challenge political campaigns share with franchise organizations and multi-location brands is maintaining message consistency while adapting communications to local audiences.

The strongest campaigns typically operate from a unified messaging framework while tailoring creative execution around local concerns. Issues such as education, housing affordability, public safety, or cost of living may resonate differently from one community to another, requiring campaigns to adjust creative without abandoning their core narrative.

Digital Remedy’s Political Desk was designed around that principle. The division coordinates execution across nine channels, including connected TV, video, display, audio, native advertising, social media, search, digital out-of-home, and high-impact formats. Centralized reporting provides a unified view of performance while allowing creative and targeting strategies to adapt to local priorities and channel-specific behavior.

The approach mirrors a broader shift taking place across commercial marketing. Brands increasingly recognize that omnichannel success depends less on delivering identical messages everywhere and more on creating a consistent narrative that can be expressed differently depending on audience, geography, and context.

The Value of Local Context

One lesson that continues to transfer from political advertising into commercial marketing is the importance of balancing scale with local relevance.

While programmatic media can deliver audience reach and targeting precision, local media properties often provide context and credibility that broader inventory cannot easily replicate. Regional publishers, local news organizations, and community-focused media networks remain deeply connected to the audiences advertisers are trying to reach.

Fanelli argues that the strongest campaigns combine both approaches rather than treating them as competing strategies.

“It is the combination of local credibility with programmatic precision that makes the difference.”

Digital Remedy supports both approaches, allowing campaigns to pursue broad market saturation through local publisher networks while also layering audience targeting, geography, demographics, and issue-based segments for greater precision. For brand marketers, the principle is similar. As media consumption becomes increasingly fragmented, trusted local environments continue to offer valuable opportunities for relevance, credibility, and community connection.

Real-Time Optimization Becomes a Requirement

Another lesson emerging from political advertising is the growing importance of operational responsiveness.

Election campaigns operate in environments where debates, breaking news, polling shifts, and opponent attacks can reshape public sentiment within hours. That reality forces campaign teams to think differently about execution, creative approvals, and media optimization.

As Fanelli explains, “Speed is non-negotiable in political media. A debate moment, breaking news story, polling shift, or opponent attack can change the conversation overnight. Campaigns need to be able to move budget, update creative, and adjust targeting while voters are still paying attention.”

While brand marketers rarely face the intensity of an election cycle, they increasingly operate in environments where consumer sentiment, competitive dynamics, and cultural conversations move rapidly. The ability to identify opportunities and act on them before they disappear is becoming a competitive advantage across marketing disciplines.

That emphasis on responsiveness is reflected in The Political Desk’s structure, which includes same-day campaign launch capabilities and dedicated political operations support designed to help campaigns react while events are still unfolding. Increasingly, marketers in every category are pursuing the same objective: reducing the time between insight and action.

Capturing Shared Attention

Political campaigns are also leaning into shared attention, one of the most valuable commodities in modern media. When audiences are scattered across platforms, moments that bring large groups of people together remain relatively rare. Live sports, awards shows, and major cultural events continue to command concentrated attention that advertisers struggle to find elsewhere.

Digital Remedy’s Political Desk provides access to premium connected TV inventory surrounding events such as NFL, MLB, and NBA broadcasts, along with major entertainment programming. For campaigns, those environments create opportunities to engage voters during moments of unusually high attention and engagement.

This applies equally to brand marketers. As media fragmentation continues, live cultural moments become increasingly valuable because they offer something that many digital environments cannot: scale, engagement, and collective attention at the same time.

As political campaigns prepare for the 2026 election cycle, the technologies and strategies they adopt may once again provide an early glimpse into where the broader advertising industry is headed. Hyperlocal measurement, omnichannel coordination, contextual relevance, and real-time optimization are no longer just political campaign priorities. They are increasingly becoming requirements for marketers trying to compete in our fragmented and rapidly evolving media landscape.