Agency scale has traditionally been associated with greater media buying leverage. A new partnership between Guideline and Tinuiti is putting that independent agencies assumption to the test, using verified market intelligence to compare negotiated media costs against broader benchmarks.

For brands evaluating media agencies, buying power has long been one of the arguments favoring the largest agency networks. Greater aggregate spending, the conventional wisdom goes, gives larger organizations more leverage with media owners, platforms and ultimately better pricing for clients.

A new partnership between advertising intelligence company Guideline and independent media agency Tinuiti offers another way to evaluate that assumption. Rather than using agency size or aggregate billings as a proxy for buying leverage, verified market intelligence can benchmark negotiated media costs against broader market activity.

Guideline says its data shows Tinuiti delivering double-digit media cost advantages across several key channels. The companies did not disclose the individual channels or underlying results in the announcement, so the findings shouldn’t be interpreted as evidence that independent agencies broadly outperform larger agency networks. They do, however, raise a more consequential question for advertisers. If buying performance can be independently benchmarked, how much should agency scale influence agency selection?

Testing the Buying-Power Assumption

Under the partnership, Tinuiti is joining Guideline’s partner ecosystem as a strategic data contributor to its Ad Intelligence product while gaining access to Guideline’s advertising intelligence data.

Guideline uses verified advertising spending and pricing information to establish market benchmarks across channels, advertisers, and categories. The objective is to give buyers a reference point based on market activity rather than generic planning rates, modeled estimates, or an agency’s own assessment of its buying performance.

“This partnership is an incredible proof point for what we’ve held true from the start,” Shasta Cafarelli, Head of Media Investment at Tinuiti, told Street Fight. “Guideline’s independent data shows Tinuiti achieving exceptional pricing across several key channels, which debunks the notion that volume alone determines buying power.” 

Scale isn’t suddenly irrelevant. Large agencies still aggregate enormous media budgets and maintain extensive relationships with publishers, platforms, and media owners. Independent benchmarking does, however, give brands another way to determine whether those advantages translate into better economics for their particular media investments.

From Claimed Leverage to Measured Performance

The partnership also reflects a broader shift toward making agency buying performance more externally measurable.

“Media buying agencies across the board are in a constant battle to provide greater value for less money to the clients they work with,”

Reuben Tozman, Guideline’s Chief Data Strategy and Strategic Alliances Officer, told Street Fight. “Guideline serves as an independent benchmarking tool that provides intelligence and guardrails for media buyers on how money is flowing and at what cost.”

That potentially changes part of the agency evaluation process. Instead of relying primarily on aggregate billings, negotiated-rate claims, or perceived leverage, advertisers can ask what the agency actually negotiate relative to the market.

For independent agencies, that matters because buying power has historically been one of the perceived trade-offs brands make when choosing them over larger agency networks. Independents have typically competed on agility, specialization, senior-level attention, and innovation, while holding-company agencies could point to their scale and collective media spending.

“The value goes beyond cost efficiency,” Cafarelli said. “The ability to assess real negotiated pricing, not generic planning rates, gives our team a clearer view of the market so we can make smarter decisions about where and how our clients invest.”

For brands, she argues, that means media cost advantages don’t necessarily have to be traded for the speed and flexibility of an independent agency.

Multi-Location Growth Is Becoming an Operating Platform

What It Means for Multi-Location Brands

The issue is particularly relevant for MULO brands because their media requirements rarely fit neatly into a single national buying strategy. Brands may simultaneously manage national awareness, regional investment, local activation, and performance media across hundreds or thousands of markets.

Independent benchmarking can add another layer of evidence to those decisions. A lower CPM or CPC doesn’t automatically represent better buying when audience quality, geography, inventory, and outcomes differ, just as an agency’s overall spending scale doesn’t guarantee the strongest economics across every channel and market.

The Guideline-Tinuiti partnership doesn’t settle the independent-versus-holding-company debate, and one agency’s benchmarked performance doesn’t establish that independent agencies broadly deliver better pricing. But it does point toward a more data-driven way of evaluating one of the industry’s longstanding assumptions.

As negotiated media costs become easier to benchmark against verified market intelligence, brands may be able to judge buying power less by what an agency’s size suggests it should deliver and more by what it actually achieves. For agencies competing for MULO brand media budgets, that could shift an important part of the conversation from perceived buying leverage to demonstrated buying performance.

A national heatstroke-prevention campaign from OAAA and the Ad Council shows how OOH (out-of-home) can combine broad reach with geographic concentration and contextual relevance.

Summer may be winding down, but a national campaign warning drivers about the dangers of leaving children unattended in vehicles is designed to remain visible well beyond the hottest months of the year.

The Out of Home Advertising Association of America (OAAA) and Ad Council launched the Heatstroke Prevention campaign July 9, bringing its “Stop. Look. Lock.” message to out-of-home inventory across the country. While the campaign places particular emphasis on warmer Sun Belt markets, OAAA President and CEO Anna Bager told Street Fight that the effort addresses a year-round, nationwide risk and will continue through April 2029 using the current creative assets.

For brands and agencies, the campaign is also an example of a broader evolution in OOH: maintaining the scale and consistency of a national medium while increasingly allowing marketers to concentrate exposure according to geography, audience, context, and local market conditions.

A National Issue With Local Relevance

Pediatric vehicular heatstroke remains the leading cause of non-crash, vehicle-related deaths among children 14 and younger, according to Bager. Since 1998, 1,056 children have died in hot-car incidents, averaging approximately 37 deaths annually. As of July 22, 2026, 13 children had died from pediatric vehicular heatstroke this year.

“The number of pediatric vehicular heatstroke deaths can vary from year to year, but these tragedies remain a persistent and preventable issue,” Bager told Street Fight. 

Young children are particularly vulnerable because their bodies cannot regulate temperature as effectively as adults, but dangerous conditions can develop rapidly inside a parked vehicle even on relatively mild days. The campaign therefore focuses on establishing one simple habit: “Stop. Look. Lock.” before leaving a vehicle.

Concentrating OOH Where the Message Resonates

The campaign’s OOH assets are being distributed nationally, with particular emphasis on Sun Belt states including Arizona, California, Florida, Georgia and Texas. Bager emphasized, however, that vehicular heatstroke isn’t exclusively a warm-weather or southern-state problem. Hot-car deaths have occurred across the country, including in regions with traditionally cooler temperatures.

That creates a media strategy balancing national reach with geographic relevance. Creative and messaging can remain consistent across the country while additional exposure is concentrated in markets where environmental conditions make the warning particularly immediate.

For MULO brands and their agencies, the approach mirrors a familiar marketing challenge. National organizations need centralized creative and consistent brand messaging, but media investment can be weighted according to local conditions, consumer behavior, seasonality, store footprints, or individual market opportunities.

OOH Is Becoming More Precise

The campaign comes as advertisers are increasing their investment in OOH while the medium itself becomes more digital and measurable. U.S. OOH advertising revenue reached a record $9.46 billion in 2025, up 3.6%, with digital OOH increasing 10.5% and accounting for more than 36% of industry revenue. That momentum accelerated in early 2026. OOH generated a record $2.12 billion during the first quarter, up 7.1% year over year, while DOOH revenue increased 12.9%.

The bigger shift for brand marketers, however, may be happening in how the medium is bought. Research previously covered by Street Fight found U.S. marketers already using programmatic DOOH expect to increase spending by an average of 49% over 18 months, while its presence in campaigns is projected to increase from 34% to 52%. Ninety-one percent said they had incorporated programmatic DOOH into broader digital or programmatic activity during the previous year.

Those numbers point to OOH moving beyond its traditional role as a primarily broad-reach awareness channel. Programmatic buying, digital inventory, audience data, and improved measurement are giving advertisers greater ability to deploy national campaigns while adjusting execution according to local markets and conditions.

Inside the Dutch Bros National Expansion Strategy

Reaching Consumers in the Right Context

The Heatstroke Prevention campaign illustrates why that combination can be powerful. OOH reaches consumers while they are driving, commuting, shopping, or otherwise moving through the physical environment where the desired behavior needs to occur.

The campaign isn’t limited to OOH. Television, radio, digital, and social assets reinforce the message across multiple touchpoints, while OAAA is encouraging media owners to donate available outdoor inventory to amplify “Stop. Look. Lock.” nationwide.

For marketers, that demonstrates how OOH can complement digital channels rather than compete with them. Digital and social can establish awareness and frequency throughout the consumer journey, while OOH can reinforce the same message in a specific geographic and physical context.

National Scale Meets Local Context

OAAA and the Ad Council plan to continue using the current creative through April 2029 rather than treating heatstroke prevention as a short-term summer initiative. That longevity reinforces another element of the strategy: a simple national message can remain consistent while its relevance changes by market, season, and consumer context.

For MULO brands and agencies, that’s increasingly where OOH’s value proposition becomes interesting. Centralized creative, national reach, geographic weighting, contextual placement, and digital execution can coexist within the same media strategy.

The Heatstroke Prevention campaign happens to apply those principles to a public-safety message rather than a commercial one. But the underlying model is increasingly relevant to brands trying to solve the same fundamental problem of how to operate at national scale without sacrificing local relevance.

AI-powered local discovery is moving beyond the recommendation and closer to the transaction. Yelp’s expanded integration with ChatGPT brings new capabilities into the conversational experience, potentially shortening the path between discovering a location and becoming a customer.

For multi-location brands, appearing in an AI recommendation is quickly becoming only part of the challenge. The next question is whether consumers can act on that recommendation without leaving the conversational experience.

Yelp’s expanded integration with ChatGPT moves local discovery further in that direction. Yelp’s local business information, ratings, reviews, and photos can help inform restaurant discovery within ChatGPT, while Yelp Reservations and Waitlist bring consumers closer to taking action. A customer can move from a conversational query about where to eat toward booking a table or joining a waitlist with fewer steps between consideration and conversion.

For restaurant chains and other multi-location brands, the development represents another sign that the traditional boundaries between search, reputation, recommendation, and conversion are beginning to disappear.

From Finding a Restaurant to Acting on the Recommendation

Consumers have traditionally moved through several platforms when choosing a restaurant. They might begin with Google, check reviews on Yelp, visit a restaurant’s website, and then move to a reservation platform before completing a booking.

Conversational AI has the potential to compress that journey. A consumer can ask for restaurants matching specific criteria and increasingly see restaurant information, reputation signals, and availability as part of the same experience.

For multi-location restaurant brands, that reduces the distance between being discovered and generating a customer. It also raises the value of the location-level information and reputation signals that help consumers and AI systems determine which businesses deserve consideration in the first place.

Yelp Extends Its Reach Into Conversational Discovery

The integration fits a longer-running Yelp strategy of making its local business information and services available beyond Yelp’s own properties. It also reflects a change in consumer behavior as AI assistants become another entry point for local search and business discovery.

In a conversation with Street Fight, Chad Richard, Yelp’s Senior Vice President of Business and Corporate Development, said the latest integration builds on Yelp’s existing presence in ChatGPT, where reviews, ratings, and business information already surface within search results.

“A growing number of consumers are turning to AI for local searches and expect instant answers they can trust, along with the ability to take action right where the conversation happens,” Richard told Street Fight. “With Yelp Reservations and Waitlist now integrated in ChatGPT,

… consumers can seamlessly go from discovery to booking a table or joining a waitlist without leaving their chat.”

Richard characterized the expansion as a “major milestone” in Yelp’s effort to power local discovery across the AI ecosystem. That distinction is important because AI creates a potentially more consequential distribution environment than simply placing Yelp content on another platform. The interface can synthesize business information around a consumer’s specific intent, narrow the available choices, and increasingly connect those recommendations with actions.

For Yelp, that makes its combination of business data, consumer reviews, photos, reputation signals, and transactional capabilities potentially valuable infrastructure for conversational discovery. For brands, it means their Yelp presence may influence customer decisions occurring well beyond Yelp’s website or app.

That becomes particularly important for franchise organizations and multi-location brands managing hundreds or thousands of individual business profiles. Location accuracy, reviews, operating information, attributes, and availability increasingly become inputs into a broader discovery and conversion ecosystem rather than assets confined to an individual platform.

Recommendation and Conversion Begin to Converge

The development also builds on a shift Street Fight examined earlier this summer: consumers are increasingly using AI not simply to research brands, but to narrow their choices before visiting a website or physical location.

Amperity research found that more than half of consumers had chosen a brand they hadn’t previously considered because of an AI recommendation. Derek Slager, the company’s co-founder and co-CEO, told Street Fight that the resulting challenge for marketers is moving from competing for clicks to:

“competing to become the recommendation.”

Richard’s comments point to the next stage of that evolution: recommendation and conversion are beginning to converge. If an AI assistant can introduce a restaurant a consumer hadn’t previously considered, surface information that helps evaluate it, identify availability, and then enable the consumer to book a table or join a waitlist without leaving the conversation, several stages of the traditional customer journey begin collapsing into a single interaction.

For restaurant chains and multi-location brands, that makes AI visibility increasingly connected to measurable business outcomes. The question is no longer simply whether a location appears in an AI-generated answer, but whether the information, reputation signals, availability, and transactional infrastructure surrounding that location make it possible for the consumer to act once the recommendation is made.

AI Visibility Moves Closer to Revenue

Until recently, much of the conversation around generative engine optimization and AI visibility focused on whether a brand appeared in ChatGPT, Gemini, Perplexity, or Google’s AI-powered search experiences. That remains important, but transactional capabilities change the value of being recommended.

A restaurant that appears prominently in an AI answer but has inaccurate information, weaker reputation signals, or no convenient path to book may still lose the customer to another recommended location. Conversely, brands whose location data, reputation, and conversion infrastructure work together can potentially turn AI visibility into customer acquisition with fewer intervening steps.

That has implications for agencies as well as brands. AI visibility may increasingly need to be evaluated not simply as a ranking or share-of-voice metric but as part of an acquisition funnel that connects discovery with measurable consumer actions. AI may be changing the interface through which consumers make decisions, but the underlying local marketing fundamentals—accurate business information, strong reviews, relevant attributes, location-level availability, and frictionless conversion—remain critical.

Thryv Adds Revenue Intelligence for Franchise Brands

The Local Marketing Funnel Gets Shorter

The broader significance of the Yelp integration is the continued compression of the local customer journey. Search, reputation management, recommendations, and transactions have historically been managed as separate disciplines, often across separate technology platforms and marketing teams.

Conversational AI increasingly connects those functions. For franchise organizations, that creates a different operating challenge because listings teams cannot think exclusively about data accuracy, reputation teams about reviews, and digital teams about website traffic if all of those signals potentially influence the same AI-generated recommendation and the consumer action that follows it.

Instead, local discovery increasingly functions as a connected system in which the quality of a brand’s digital presence influences whether it is surfaced, its reputation influences whether it is considered, and its transactional infrastructure influences whether that consideration becomes revenue.

A Problem Worth Solving

Yelp’s expanded presence in ChatGPT is more significant than another distribution agreement for local business content. It illustrates how AI assistants are evolving from tools that help consumers find businesses into interfaces that can help them evaluate options and move toward completing transaction Thus changing definition of AI visibility.

Winning may increasingly require more than becoming the recommendation. Brands will also need to ensure that once AI puts them in front of a consumer, the path from recommendation to conversion is accurate, trusted, and frictionless.

What if one of the biggest line items in your marketing budget is funding a strategy that’s already dead? AI is rewriting how customers are discovered, targeted, and converted, leaving the traditional marketing funnel behind.

Most franchise brands are still budgeting for a customer journey that stopped existing years ago. For decades, performance marketing ran on a simple premise: get in front of as many people as possible, build awareness, and slowly guide them toward a purchase. That premise made sense when marketers had limited data, and broad targeting was the only real option. It doesn’t anymore, and the brands still funding it are paying for a version of the customer that doesn’t exist.

The Old Funnel Bet on Time You No Longer Have

The classic marketing funnel splits the buyer’s path into stages: awareness, consideration, and conversion. It’s a tidy model, and it was built entirely around what marketers couldn’t do.

• Broad reach existed because marketers couldn’t tell who was actually close to buying.
• Long nurture timelines existed because there was no way to move people faster.
• Demographic targeting existed because there was no better signal available.

None of those constraints hold anymore. A 2025 Boston Consulting Group study makes the same argument from a different angle: marketers have spent decades force-fitting complex, unpredictable customer behavior into a rigid, linear funnel. BCG’s case is that AI is what finally makes a genuinely adaptive, non-linear approach possible.

AI Didn’t Improve Targeting. It Replaced the Logic Behind It

This is the shift most marketers are underestimating: once a brand knows exactly who already converted, it no longer needs to guess at anyone else. It can identify people who look like those customers and target them directly.

That’s the entire premise behind AI audience targeting, and it inverts the old model. Instead of starting broad and narrowing over months, marketers start with their best, already-converted customers and let the model find prospects who resemble them: prospects who are already far more likely to convert, fast.

It works because three things finally lined up:  

• First-party data on customers who actually converted rather than just clicked
• Audience modeling built directly into major ad platforms
• Models that keep learning as new conversions come in, instead of sitting static after launch

It’s not experimental. It’s the default infrastructure now.

That excuse doesn’t exist anymore. Slowly building awareness and waiting for someone to work down the marketing funnel isn’t a smaller part of the strategy. It’s a strategy built for a marketing funnel that no longer exists.

Inside the Dutch Bros National Expansion Strategy

What It Means for Franchise Marketing

This shift matters most for multi-location and franchise brands, where inefficiency at scale is expensive in a way single-location businesses never feel. Two engagements we’re running right now make the difference concrete.

One is a national real estate investor franchise with more than fifteen years of first-party transaction data. Every closed deal, every lead source, every property characteristic tied to an outcome. That history has let us build a propensity model trained on hundreds of millions of historical mail-response data points, scoring each property’s likelihood to convert before a single piece of mail goes out.  

The result: Mail spend down 26%, cost per lead down 9.5%, cost per appointment down 11.7%. Same footprint, meaningfully less waste.

The other is a national health and wellness franchise that hasn’t opened its first-party data to this kind of modeling. Without that history to train against, targeting falls back to the old playbook (demographics, general interest, broad reach) because there’s no converted-customer signal to build from.  

The technology is available either way. The constraint isn’t AI. It’s data access, and it’s the difference between what one franchise is already capturing and what the other is still leaving on the table.

The Job Changed. Most Marketers Haven’t.

The role itself is different now. It’s no longer about architecting a sequential journey and shepherding someone through it. It’s about identifying who already looks like a brand’s best customers and getting out of the way while the technology does the matching.

That means first-party data must be clean and usable, because a model is only as good as what it’s trained on. It means tools built for audience modeling, not broad demographic guesswork. And it means treating a campaign as something that gets smarter every week, not a static asset revisited once a quarter.

For anyone overseeing multiple locations or franchise territories, the starting point is blunt: audit the first-party data, and cut the budget that’s still funding broad, top-of-funnel awareness. That’s usually where the waste is hiding.

The marketing funnel isn’t evolving into something new. It’s dead, with the multi-location and franchise brands still budgeting like it’s alive, funding a model that no longer describes how anyone actually buys.

Restaurant expansion and contraction are often explained by consumer demand, labor costs, menu innovation, or access to capital. New research from SOCi suggests another metric deserves attention: local AI visibility.

Analyzing eight restaurant chains expanding in 2026 alongside eight brands reducing their footprints, SOCi found a consistent performance gap across every major local discovery channel. Expanding brands averaged a Local Visibility Index (LVI) score of 68, compared with 47 for contracting brands—a 21-point difference spanning search visibility, reputation, localized social engagement, and AI recommendations.

While the analysis focuses on restaurants, the findings have broader implications for franchise organizations and multi-location brands as consumers increasingly rely on AI assistants alongside traditional search engines to decide where to spend their money.

AI Reveals the Largest Gap

The widest separation appeared in AI-powered discovery. According to SOCi’s research, expanding restaurant brands were recommended by ChatGPT in roughly 20% of tested prompts, compared with approximately 3% for chains closing locations. That’s a difference of nearly sevenfold. Gemini and Perplexity showed similar patterns, while expanding brands also received higher AI-generated ratings across all three platforms.

Speaking with Street Fight, Monica Ho, Chief Marketing Officer at SOCi, said the findings illustrate how growth increasingly begins before customers ever enter a restaurant. “Growth isn’t just happening at the store level anymore, it’s happening in how discoverable a brand is before a customer ever decides where to go,” Ho said.

“Our research found expanding restaurant chains are recommended by AI assistants like ChatGPT up to six to seven times more often than chains that are closing locations.”

Ho said the pattern reflects a broader shift in local marketing, where brands are increasingly managing search visibility, reviews, social media, and AI discoverability as one connected system rather than separate marketing channels. She further compared that approach to Dutch Bros’ strategy of treating customer data as shared infrastructure rather than isolated datasets, arguing that discoverability and customer retention have become complementary components of long-term growth.

AI Rewards the Fundamentals

One of the more interesting conclusions is that AI appears to reward many of the same fundamentals that have influenced local search for years. Growing restaurant chains appeared in Google’s Local Pack more than twice as often as shrinking competitors while also holding Yelp’s top organic position nearly twice as frequently. Reputation metrics followed the same pattern, with expanding brands maintaining significantly higher review ratings while responding to customer reviews faster and more consistently.

Social media produced the largest performance multiple. Expanding brands generated local engagement rates roughly 26 times higher than contracting chains while maintaining about five times as many local followers. According to SOCi, that difference stems less from publishing more content than from creating localized content that resonates with individual communities instead of relying primarily on standardized corporate posts.

Taken together, the findings suggest AI isn’t introducing a completely new marketing discipline. Instead, it is amplifying the importance of long-standing local marketing fundamentals including accurate business data, reputation management, localized content, and consistent customer engagement.

One Connected Discovery System

For franchise and multi-location brands, perhaps the most significant finding is that high-performing brands no longer treat search, listings, reviews, social media, and AI visibility as separate initiatives. Instead, those disciplines increasingly function as one connected discovery system, where improvements in one area strengthen performance across the others.

“Discoverability and retention are two sides of the same growth strategy now.”

That shift has important implications as conversational AI becomes another entry point for local discovery. Maintaining accurate location data, responding to reviews, investing in localized social content, and strengthening brand authority are no longer isolated marketing tactics. They collectively influence how AI systems interpret and recommend businesses.

Why It Matters

SOCi’s research does not argue that stronger AI visibility causes restaurant chains to expand. It does, however, suggest that the brands outperforming operationally are also outperforming digitally and that the relationship between those trends may become even stronger as AI-assisted discovery becomes more common.

For multi-location brands and agencies, the takeaway extends well beyond restaurants. The brands building sustainable growth appear to be treating local search, reputation, social media, customer data, and AI visibility as a single operating system rather than separate marketing programs. As AI continues reshaping how consumers discover local businesses, that integrated approach may become one of the strongest indicators of long-term competitive advantage.

Managing a single Google Business Profile well takes consistent effort. Managing dozens or hundreds of them well has traditionally taken a team, a lot of hours, and a tolerance for repetitive work that rarely gets easier or less time-consuming, no matter how much practice you put in.

For multi-location businesses and the agencies that manage GBPs on their behalf, every additional location multiplies the number of reviews to answer, posts to schedule, and details to keep accurate and optimized, without multiplying the hours available to do it. It’s no surprise that GBP management is often one of the first things to slip down the list of priorities when tasks pile up, even though it’s directly tied to local search visibility and customer trust.

However, agentic AI tools are starting to lighten that load in a major way, and manual GBP updates may soon become largely a thing of the past. Agentic platforms like Local Falcon’s Falcon Agent connect directly to Google Business Profiles and let users manage them through natural language prompts instead of manual logins and repetitive clicks. For MULOs and agencies, this is huge when it comes to managing GBPs effectively at scale.

The Scaling Problem Agencies Know Too Well

Agencies managing GBPs for multiple clients feel the scaling problem most acutely. A single account manager might be responsible for dozens of locations across several brands, each with its own review volume, posting cadence, and local nuances. Multiply that by a full client roster, and the manual workload becomes difficult to sustain without either adding headcount or letting quality slip.

Conversational AI agents address this by collapsing tasks that used to require touching each profile individually into a single instruction that applies actions across many profiles at once. Rather than opening 10 different GBP dashboards to reply to reviews or schedule a promotional post, an account manager can issue one prompt, including per-location instructions as needed, and let the AI apply it everywhere it’s relevant.

Where the Time Savings Add Up

Review responses are one of the clearest areas where MULOs and agencies can save time through agentic automation. Even with templated replies, responding to reviews across multiple locations means logging into each profile, finding new reviews, selecting and customizing a template, and posting replies, one at a time, over and over. For a business or agency handling dozens of reviews a week across several locations, that adds up to hours of busywork that produces essentially the same output every time.

With an agent enabling conversational GBP management, that entire process can be handled with a single prompt, something like instructing the AI to reply to all reviews of four stars and up with a thank you and invitation to return, or to respond to lower-rated reviews with an empathetic message and a request to connect offline. The AI pushes the replies live across every matching review, at every connected location, without anyone needing to open a single dashboard.

The same logic applies to GBP posts and profile updates. Instead of manually scheduling a weekly promotion for each location or individually updating hours across a multi-location footprint, users can set up recurring automations or issue bulk update prompts that apply everywhere at once. A change that once meant repeating the same steps across ten, twenty, or a hundred profiles becomes a single instruction.

Consistency Becomes the Default, Not the Exception

Beyond the raw time savings, conversational Google Business Profile management improves the odds that tasks get done at all. When responding to a review or updating a listing takes minutes across an entire portfolio instead of hours, there’s far less incentive to let it slide during a busy week. That matters for MULOs and agencies especially, since inconsistent review responses or outdated information on even a handful of locations can quietly undercut an otherwise strong local presence.

It’s worth noting that Google has taken a step in this direction as well, allowing Gemini web app users to manage a GBP conversationally. For now, that feature is limited to a single location, which makes it a reasonable option for small, single-site businesses, but not a practical solution for MULOs or agencies managing multiple profiles. That gap is exactly where dedicated multi-location agentic local SEO tools are built to operate.

A More Sustainable Way to Scale

For agencies, the case for conversational GBP management is ultimately about capacity. Freeing up hours that used to go toward repetitive manual updates means that same time can go toward strategy, client communication, and the kind of work that actually grows an account.

For MULOs, using agentic AI to manage GBPs at scale means the accuracy and responsiveness that a single-location business can maintain without much effort finally becomes achievable across an entire portfolio of locations.

As agentic AI tools continue to mature, conversational Google Business Profile management is likely to become less of a novelty and more of a baseline expectation. Businesses and agencies that adopt it early will be spending their time on growth instead of upkeep, while the days of grinding out manual, location-by-location GBP management tasks may quietly fade into memory.

Political advertising has long served as an early proving ground for advertising technology. The need to identify audiences quickly, optimize campaigns in real time, and measure performance under fixed deadlines has consistently accelerated innovation that later finds its way into commercial marketing. StackAdapt’s new Political Targeting and Measurement Suite is the latest example. While designed for campaigns competing in the 2026 U.S. midterm elections, where political advertising is expected to exceed $11 billion in spending, the platform reflects broader changes in how brand marketers are connecting audience intelligence, campaign activation, measurement, and optimization.

For multi-location brands the significance extends well beyond politics. The same pressure to make smarter media decisions while campaigns are still live is reshaping local marketing, where hundreds of markets, thousands of locations, and increasingly localized customer journeys demand faster, more informed decision making.

From Audience Intelligence to Campaign Optimization

At the center of the new offering is StackAdapt’s integration with L2, a nonpartisan voter data provider that compiles publicly available voter registration records alongside legally permitted demographic, geographic, political, and consumer information. The integration enables political advertisers to create and activate custom voter audiences within hours, segmenting them by attributes such as voting history, geography, political district, party affiliation, and other modeled characteristics before activating campaigns across StackAdapt’s omnichannel platform.

What differentiates the platform is not simply audience creation, but the ability to connect those audiences with campaign measurement while advertising is still in market. Rather than waiting until after Election Day to understand what worked, campaigns can evaluate how targeted voter segments are responding to messaging and adjust budgets, targeting strategies, or creative before the opportunity to influence voters has passed.

That workflow mirrors a growing expectation among enterprise marketers. Multi-location brands are increasingly looking to connect customer data, campaign execution, and measurement into a continuous feedback loop that allows regional promotions, new store openings, franchise recruiting campaigns, and localized customer acquisition efforts to be optimized while media is still running rather than after budgets have already been spent.

Looking Beyond Traditional Research

StackAdapt is careful not to position the platform as a replacement for traditional polling. Instead, it views campaign measurement as another source of intelligence that helps campaigns make better decisions throughout the election cycle. “Polling captures stated opinions from a sample of voters, while StackAdapt’s measurement capabilities provide a more immediate view of how defined voter audiences are engaging with campaign messaging,” said Mark Positano, Head of Political at StackAdapt.

Because the Political Targeting and Measurement Suite is newly launching, the company has not yet published public case studies comparing its campaign insights with polling results. Rather than predicting election outcomes, StackAdapt says the platform is designed to help campaigns continuously refine media investments while they remain active.

“Rather than replacing polling, we see the StackAdapt Voter Graph as an additional input campaigns can use alongside surveys, field research, and other voter intelligence,” Positano said.

The philosophy is increasingly familiar to brand marketers. Rather than relying exclusively on post-campaign reporting or periodic customer research, brands are combining CRM data, loyalty programs, first-party customer information, location intelligence, media performance metrics, and AI-driven insights to develop a more complete picture of customer behavior. The objective is no longer simply measuring success after a campaign ends, but creating a continuous stream of signals that improve performance while campaigns are still influencing customer decisions.

The Platform Trend Matters More Than the Political Use Case

Beyond the election cycle, StackAdapt’s announcement reflects a broader evolution taking place across advertising technology. For years, audience creation, campaign activation, measurement, and optimization have largely operated as separate functions managed across multiple platforms and vendors. Increasingly, technology providers are integrating those capabilities into unified workflows that reduce the time between identifying an audience, launching a campaign, measuring results, and making optimizations.

Political campaigns operate under uniquely compressed timelines, making those efficiencies especially valuable. Yet the same operational model is becoming increasingly relevant for franchise organizations and multi-location brands, where marketing teams routinely manage campaigns across hundreds or thousands of locations, each with different competitive conditions, customer behaviors, and market dynamics.

As AI continues to accelerate campaign planning and optimization, marketers are also raising expectations for how quickly platforms should surface actionable insights. Rather than waiting for weekly or monthly reports, brands increasingly want systems that identify performance trends early enough to change outcomes while campaigns are still live.

Privacy and Governance Remain Foundational

Political advertising inevitably raises questions around voter privacy, data governance, and microtargeting. StackAdapt says the Political Targeting and Measurement Suite applies the company’s existing privacy, security, and compliance standards to political advertising. Rather than providing access to personally identifiable voter records, the platform creates privacy-conscious audience segments and reports aggregated measurement insights.

Political advertisers must also comply with applicable federal and state regulations, advertiser verification requirements, creative review policies, and ongoing platform monitoring designed to prevent unlawful discrimination, deceptive voting information, voter intimidation, or other prohibited activity.

Those safeguards reflect another trend that extends beyond political campaigns. As marketers gain access to richer audience intelligence and more sophisticated targeting capabilities, privacy governance and responsible data use are becoming core requirements rather than compliance afterthoughts.

A Glimpse Into the Future of Marketing Platforms

While StackAdapt built its new suite for political advertisers, the larger takeaway is the direction enterprise marketing technology continues to move. The future is less about adding another data source or another reporting dashboard and more about connecting audience intelligence, activation, measurement, and optimization into a single operating workflow.

For multi-location brands and franchise organizations, that shift could have significant operational implications. Managing hundreds of local markets requires marketers to make thousands of campaign decisions each year. The faster platforms can convert audience signals into actionable recommendations, the more efficiently brands can allocate media budgets, improve local customer acquisition, and support individual locations.

Political advertising may be the immediate application, but the technology behind StackAdapt’s latest launch offers a glimpse of how brand marketers are likely to manage campaigns in the years ahead.

Opening more coffee shops may be the most visible part of the Dutch Bros growth strategy. Behind the scenes, however, the company is building something just as important: the marketing infrastructure needed to acquire customers more efficiently, personalize engagement, and increase customer lifetime value. As Dutch Bros expands nationally, that infrastructure may prove to be one of its most durable competitive advantages.

The strategy is already producing measurable results. During the first quarter of 2026, Dutch Bros increased revenue 30.8% to $464.4 million, while system same-shop sales rose 8.3%, driven by 5.1% transaction growth. Management also raised its full-year outlook for revenue, adjusted EBITDA, same-shop sales, and new shop openings, signaling confidence that its investments in customer engagement and operational execution are translating into stronger business performance.

That momentum reflects a strategy first articulated during the Dutch Bros inaugural Investor Day in 2025. Management outlined plans to accelerate unit growth, increase transactions, expand digital engagement, improve unit economics, and grow from roughly 1,000 locations toward more than 2,000 by 2029. CEO Christine Barone described the objective as creating “a long-term engine of innovation, personalization and loyalty” capable of reaching “the right customer at the right moment.” While Investor Day focused heavily on store development and financial targets, it also revealed an equally important priority: building the customer infrastructure needed to support long-term national expansion.

First-Party Data Is the Foundation

The cornerstone of that strategy is Dutch Rewards, which now accounts for 74% of all transactions. Rather than functioning simply as a loyalty program, it has become one of the company’s richest sources of authenticated first-party customer data. Every purchase, preferred beverage, visit frequency, store location, and mobile interaction helps Dutch Bros better understand customer behavior while reducing its dependence on increasingly expensive paid customer acquisition.

To activate that data, Dutch Bros combines a customer data platform (Segment) with a customer engagement platform (Braze). Together, those systems unify customer information across digital touchpoints and enable personalized communications through email, SMS, push notifications, and the mobile app.

Instead of sending identical promotions to every customer, Dutch Bros can tailor communications based on purchasing behavior, visit frequency, and previous interactions. Customers showing signs of declining engagement can automatically receive retention offers, while seasonal products and promotions can be personalized using purchase history. The result is a lifecycle marketing strategy that becomes more effective as customer relationships mature.

Customer Experience Fuels Better Marketing

Order Ahead illustrates how Dutch Bros increasingly views operations and marketing as complementary investments rather than separate initiatives. Beyond reducing wait times and improving shop throughput, every authenticated digital order generates additional customer insight while creating new opportunities for personalized engagement.

Combined with expanded food offerings and continued investments in operational efficiency, these initiatives create a virtuous cycle. Better customer experiences encourage more digital interactions, richer first-party data, more relevant marketing, and ultimately stronger customer retention. Rather than optimizing individual touchpoints, Dutch Bros is steadily connecting them into a single customer journey.

“Dutch Bros is a great example of a growth-stage brand treating customer data as core infrastructure rather than a side project,” said Monica Ho, chief marketing officer at SOCi.

“Turning every transaction into an actionable signal is exactly the operational discipline that tends to separate brands that scale well from brands that stall out.”

Expansion Means Integrating Customers, Not Just Stores

Dutch Bros’ acquisition of Clutch Coffee demonstrates why that infrastructure matters. The transaction provided an immediate presence in North and South Carolina, accelerating the company’s entry into attractive Southeastern markets. But converting stores is only one part of the integration process. The larger opportunity lies in converting existing Clutch customers into loyal Dutch Bros customers.

That requires much more than changing signage. Success depends on enrolling customers into Dutch Rewards, encouraging adoption of mobile ordering, personalizing communications, and building habits that lead to repeat visits. With customer data unified and engagement coordinated across its marketing platform, Dutch Bros has the infrastructure to integrate customers—not just physical locations.

Management has also indicated that acquisitions could become another avenue for accelerating expansion alongside traditional new-store development. If that strategy continues, the ability to quickly migrate customers into the Dutch Bros ecosystem may become just as valuable as the ability to open new stores.

A Blueprint for Multi-Location Growth

The investments underway today closely mirror the priorities management outlined during Investor Day. Increasing transactions requires higher visit frequency. Improving unit economics depends on more efficient customer acquisition and stronger retention. Accelerating expansion requires bringing new customers into the ecosystem quickly while building relationships that continue long after the first purchase.

Dutch Bros opened 41 new shops during the first quarter and increased its 2026 outlook to at least 185 new locations. As expansion accelerates, the systems supporting customer acquisition and retention become just as important as the pace of new store development. The companies that scale most effectively will increasingly be those that connect marketing, operations, digital engagement, and customer data into a unified growth engine.

That’s the broader lesson for multi-location brands. National expansion is no longer defined solely by where brands open their next location. Increasingly, competitive advantage is determined by what happens after a customer walks through the door for the first time. Brands that systematically transform every transaction into customer intelligence, stronger relationships, higher visit frequency, and greater customer lifetime value are likely to build more durable advantages than those focused solely on adding new locations.

Dutch Bros’ store count may define its growth, but the marketing infrastructure developing behind the scenes may ultimately determine how profitable and sustainable that growth becomes.

Vevo is bringing its premium music videos into brick-and-mortar businesses through a new partnership with Rockbot, giving MULO brands another way to create more engaging and consistent in-store experiences

For multi-location brands, the in-store experience is becoming an increasingly important competitive differentiator. While digital channels continue to dominate customer acquisition, what happens inside a physical location often determines whether customers stay longer, spend more, and return. As a result, operators are investing in technologies that help create more engaging, immersive, and consistent experiences across every location in their network.

That trend received another boost this week as Vevo announced an exclusive partnership with Rockbot to bring premium, professionally curated music video programming into commercial venues nationwide. The agreement makes Rockbot the first platform to offer Vevo’s music videos for business environments, giving restaurants, retailers, fitness centers, hospitality companies, and other multi-location operators access to centrally managed, ad-free programming designed specifically for commercial use.

In-Store Media Becomes a Brand Asset

The partnership introduces six curated Vevo channels at launch. The three channels of Rock, Hip-Hop, and Dance are organized by genre, while Day, Night, and Late Night are programmed around customer traffic patterns and the changing atmosphere businesses want to create throughout the day. The channels will also be available alongside Rockbot’s broader portfolio of news, sports, lifestyle, family, and ambient programming, allowing brands to build entertainment experiences that align with their audience, operating hours, and brand identity.

Rather than asking individual locations to create playlists or manage entertainment independently, the platform enables brands to deploy professionally curated programming across an entire location network while maintaining centralized oversight. That approach helps ensure customers receive a consistent brand experience regardless of which location they visit while reducing the operational burden placed on store managers and franchisees.

As customer expectations continue to evolve, entertainment is becoming more than background ambience. Alongside digital signage, lighting, and store design, media is increasingly viewed as another touchpoint that influences how customers perceive a brand, how long they remain engaged inside a location, and ultimately how memorable the overall customer experience becomes.

Location Management at Scale

Rockbot currently powers entertainment and media experiences across more than 50,000 business locations, serving national brands including Best Buy, Planet Fitness, Shake Shack, Lucky Strike, and Great Wolf Lodge. Its platform enables businesses to centrally manage music, television programming, and digital signage while allowing individual locations to adjust programming based on local audiences, regional preferences, or dayparting requirements.

That balance between centralized governance and localized flexibility has become increasingly important for franchise organizations and enterprise retailers. National marketing teams want every location to reinforce the same brand standards, while local operators need the ability to adapt experiences to reflect local audiences, seasonal demand, or regional preferences.

Under the partnership, Vevo’s music video channels become another centrally managed content option that can be deployed consistently across hundreds or thousands of locations without increasing operational complexity.

Garrett Dodge, CEO and co-founder of Rockbot, said businesses require a fundamentally different streaming experience than consumers, emphasizing the importance of licensed, commercial-free programming that reflects a brand while remaining easy to manage across large location networks. He said adding Vevo’s music video catalog allows companies to match entertainment to the energy of different times of day while controlling programming across one location or an entire enterprise from a single platform.

Physical Locations Become a New Premium Video Channel

For Vevo, the partnership represents more than another distribution agreement. It reflects the company’s belief that premium video consumption is no longer confined to connected televisions, computers, or smartphones, but is increasingly extending into the physical spaces where consumers shop, dine, exercise, and socialize.

Speaking with Street Fight, Natalie Gabathuler-Scully, Executive Vice President of Revenue, Distribution & Data Operations at Vevo, said consumers no longer think about premium content in terms of channels or devices. Instead, they expect high-quality viewing experiences wherever they are, creating new opportunities for premium publishers to reach audiences beyond the living room.

Gabathuler-Scully said bringing professionally curated music videos into brick-and-mortar businesses is part of a broader evolution in content distribution that recognizes physical spaces as an increasingly important extension of the premium video ecosystem.

That perspective aligns with broader changes taking place across retail, restaurants, hospitality, and fitness. As consumers spend more time engaging with digital content outside the home, businesses are looking for professionally managed programming that enhances the customer experience while reinforcing their own brand identity. For multi-location operators, entertainment is becoming another strategic touchpoint that can be centrally managed alongside digital signage, promotions, and other in-store media.

Experience Is Becoming a Marketing Channel

The announcement highlights how enterprise media platforms continue evolving beyond background music services. Today’s platforms increasingly combine music, digital signage, television programming, promotional messaging, and branded content into unified systems that can be managed centrally across an entire organization.

That convergence creates new opportunities for marketing and operations teams alike. Marketing leaders gain another channel for reinforcing brand identity inside the store, while operations teams benefit from standardized programming that reduces complexity and improves consistency across every location. Franchise organizations, meanwhile, can better ensure that independently operated locations continue delivering experiences aligned with overall brand standards.

The shift also reflects a broader change in how brands think about physical locations. Stores, restaurants, fitness centers, and hospitality venues are increasingly viewed as owned media environments where every customer touchpoint—from digital displays and promotional messaging to music and video programming—contributes to brand perception and customer engagement. As businesses compete to differentiate physical experiences from online shopping and digital-first competitors, enterprise-managed in-store media is becoming an increasingly important part of the marketing technology stack.

Why It Matters

The Vevo-Rockbot partnership is about more than bringing music videos to commercial televisions. It signals how premium content providers and enterprise technology platforms increasingly view brick-and-mortar businesses as strategic distribution channels rather than simply commercial venues.

The ability to centrally manage entertainment, digital media, and customer-facing content across every location reflects a broader shift in how brands view their physical footprint. Stores are increasingly becoming an extension of both the brand experience and the premium media ecosystem, shaping how customers engage with brands long after they walk through the front door.

In crowded markets, it’s tempting to follow the strategies, messaging, and tactics of fast-growing competitors. But as AI increasingly influences how brands are discovered and recommended, sustainable growth belongs to organizations with a distinctive market position, clear differentiation, and expertise that competitors can’t easily replicate.

Copycats may grow, but they rarely lead. When another brand is attracting attention and growing quickly, it’s easy to assume its strategy, messaging, or technology holds the answer. Adopting the same trends, launching similar products, or copying what appears to be working can help a business keep pace with the market. But keeping pace is not the same as creating competitive advantage.

Companies that simply imitate competitors often find themselves reacting rather than leading. Their messaging becomes interchangeable, their value proposition harder to distinguish, and their growth increasingly dependent on matching everyone else instead of delivering something customers cannot find elsewhere.

Sustainable growth comes from making deliberate choices that set a business apart, not from becoming a slightly different version of someone who is already successful. Brands that consistently outperform their peers identify underserved customer needs, solve meaningful problems, and build capabilities that competitors struggle to replicate.

Taking the Lead

Toast provides a useful example. When the restaurant technology platform entered the market, operators already had access to point-of-sale systems, payment providers, reservation software, online ordering platforms, and back-office tools. The challenge wasn’t a lack of technology—it was that most of those systems operated independently, creating friction for restaurant owners.

Rather than launching another standalone product, Toast focused on integrating service, payments, digital ordering, staff management, customer engagement, and back-office operations into a single platform built specifically for restaurants. Instead of adding another tool to the technology stack, it simplified operations.

That emphasis on solving a meaningful customer problem, rather than matching competitors feature for feature, helped Toast grow to more than 171,000 locations while reaching an annual recurring revenue run rate of $2.2 billion during the first quarter of 2026.

The lesson extends well beyond restaurant technology. In crowded markets, sustainable growth rarely comes from making more noise. It comes from identifying what customers genuinely need but cannot easily find elsewhere, then delivering it consistently enough to become the standard others eventually try to emulate.

The Cost of Looking Like Everyone Else

Most brands don’t become generic overnight. It happens gradually. One competitor refreshes its positioning, others adopt similar messaging, and before long everyone is talking about transformation, optimization, AI-powered insights, or customer-centric innovation.

The language converges, the positioning becomes interchangeable, and businesses that once felt distinctive begin to sound remarkably alike.

That creates a dangerous dynamic. When customers struggle to identify meaningful differences between providers, purchasing decisions increasingly revolve around price, speed, or convenience. In many cases, buyers simply select whichever credible option appears first.

For agencies and brands, differentiation is no longer about having the loudest campaign. It is about giving customers, and increasingly AI systems,  a clear reason to recognize, remember, and recommend your business.

AI Is Raising the Stakes

Standing apart has always mattered. AI search is making it even more important.

As Google, ChatGPT, Gemini, Claude, Perplexity, and other AI platforms reshape how people research businesses, traditional search results are increasingly giving way to synthesized recommendations. Rather than presenting long lists of websites, large language models summarize information from multiple sources, compare competing providers, and recommend organizations they determine best fit a user’s needs. That changes the economics of differentiation.

Businesses that describe themselves using nearly identical language risk being grouped together by AI systems as functionally equivalent. When every company claims to deliver innovation, optimization, or AI-powered solutions, those claims lose their ability to differentiate. The businesses most likely to stand out are those with clearly defined expertise, distinctive positioning, demonstrable customer outcomes, and a recognizable point of view.

In the AI era, standing out is no longer simply a branding exercise. It has become a discoverability strategy.

Usefulness Wins

Google’s own guidance reinforces that direction. Rather than rewarding content created primarily to manipulate rankings, its search systems increasingly prioritize information that demonstrates experience, expertise, authoritativeness, and trustworthiness (E-E-A-T) while providing genuine value to users.

That should encourage marketing leaders to rethink how they communicate.

The strongest long-term strategy is to be more useful. That means publishing original research, demonstrating named expertise, sharing measurable customer outcomes, and offering perspectives competitors cannot easily reproduce. Those assets not only strengthen customer trust, they also create richer signals that AI systems can use when evaluating authority and recommending businesses.

In a world where generative AI can produce polished but generic marketing copy within seconds, competitive advantage increasingly comes from the things machines cannot invent and competitors cannot easily imitate: authentic experience, credibility, deep industry knowledge, and original thinking.

Differentiation Starts Inside the Brand

One of the biggest mistakes growing brands make is treating differentiation as a marketing initiative instead of an operational discipline.Refreshing a brand identity or rewriting website copy can improve perception, but it cannot compensate for an undifferentiated business model. A company cannot credibly promise highly personalized service if inconsistent processes prevent it from delivering. A technology platform cannot position itself as customer-first if product development is driven primarily by competitive feature comparisons. Agencies cannot claim strategic leadership if every recommendation mirrors what competitors are already selling.

Sustainable differentiation comes from understanding customers, identifying underserved needs, and building an organization capable of consistently delivering on the promises it makes. Positioning, operations, product development, culture, customer experience, and service delivery must reinforce one another. Otherwise, differentiation becomes little more than a marketing slogan.

Many successful businesses begin with founder intuition and entrepreneurial energy. As organizations scale, however, those instincts need to evolve into repeatable operating models that preserve what makes the business unique while allowing it to grow.

Deliberate Choices Create Sustainable Growth

None of this suggests businesses should ignore competitors. Understanding how markets evolve, where others excel, and which technologies are reshaping customer expectations remains essential. The objective is to learn from competitors without becoming a reflection of them.

That requires leadership teams to ask more demanding questions. What do customers genuinely gain by choosing us? Which capabilities are difficult for competitors to replicate? Does our operating model consistently deliver on the promises our brand makes? And if AI summarized our business alongside five competitors today, would there be an obvious reason to recommend us? These questions are becoming increasingly important as AI influences how businesses are evaluated and discovered.

The goal is not to be quirky or contrarian for the sake of it. It is to be meaningfully different in ways that customers can understand, trust and value. Because in business, as in life, the companies that create lasting growth are rarely those that follow the crowd. They are the ones with the confidence to zig when everybody else zags.