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.

For most of the last decade, local marketing technology was built around helping brands rank in search engines. That model is beginning to change as AI-powered search experiences, agentic marketing, recommendation engines, and conversational assistants play a larger role in how consumers discover and evaluate businesses. According to Yext’s recent Consumer Search Behaviors report, 28% of consumers said they tried a new local business in the previous six months because of an AI recommendation.

That shift helps explain the significance of Yext’s announcement that it is opening its enterprise agentic marketing platform to developers, agencies, technology partners, and brands. On the surface, the move appears to be a platform expansion. In practice, it represents the latest step in Yext’s effort to reposition itself around a much larger market transition: the rise of AI-driven discovery as a meaningful customer acquisition channel.

For years, Yext was known primarily as a listings and location data management company. More recently, however, the company has broadened that vision, arguing that visibility in AI-generated answers may become just as important as visibility in traditional search results. As consumers increasingly rely on AI systems to answer questions and recommend businesses, the challenge for brands is no longer simply being found. It is ensuring that AI platforms have access to accurate, trustworthy information they can confidently surface to users. That reality has elevated the importance of structured data. Business information, location attributes, reviews, services, menus, and other forms of brand content are no longer simply inputs for search engines. They are becoming the raw material that AI systems use to understand, summarize, compare, and recommend businesses.

AI Discovery Is Becoming a Customer Acquisition Channel

Today’s announcement builds on a broader repositioning effort that has been underway at Yext for more than a year. The company has increasingly framed its strategy around what it calls agentic marketing, reflecting its belief that AI agents will become an important layer in how brands manage visibility, customer discovery, and digital presence. Earlier this year, Yext launched Scout, a visibility intelligence platform designed to help brands understand how they appear across AI search experiences and monitor competitive positioning in emerging discovery environments.

Scout represented a notable shift in focus. Traditional local SEO tools were built to track rankings, website traffic, and search visibility. Scout was built around a different premise: brands need to understand how AI platforms perceive them and how they compare to competitors when AI systems generate answers and recommendations. The launch reflected a growing recognition that AI search is creating new visibility challenges for marketers. Brands can no longer assume that rankings and website traffic provide a complete picture of performance. Increasingly, discovery is happening inside AI-generated experiences where recommendations are influenced by signals that are not always visible through conventional analytics tools.

From Software Application to Platform Strategy

Opening the broader Yext platform is the logical next step in that strategy. Rather than limiting agentic marketing capabilities to its own applications, Yext is now allowing partners to build custom agents, workflows, and applications on top of the same infrastructure that powers its products. The company is exposing its data platform, APIs, knowledge graph, and visibility intelligence capabilities to external developers and technology providers, creating the foundation for a larger ecosystem of agentic marketing applications.

The move also reflects a broader shift occurring across enterprise software. The first wave of AI adoption focused largely on individual tools and productivity gains. Companies rushed to introduce AI assistants, content generators, chatbots, and workflow automation features. As those capabilities become more common, attention is increasingly shifting toward the infrastructure required to support them. AI agents are only as effective as the information they can access and the systems they can act upon. For marketers, that means trusted business data, reliable integrations, visibility intelligence, and workflows that connect insights directly to execution.

This is where Yext appears to see its opportunity. The company already manages large volumes of structured business information for enterprise brands. By opening the platform, Yext is positioning that data layer as a foundation upon which agencies, developers, and technology partners can build specialized agentic marketing solutions. The strategy mirrors a broader trend across software markets, where technology providers increasingly seek to become platforms rather than standalone applications. The goal is to create ecosystems where partners extend functionality, develop new use cases, and generate additional value through integrations.

What It Means for Agencies and Multi-Location Brands

The announcement could prove particularly relevant for agencies serving multi-location brands. Many agencies currently manage a fragmented collection of local SEO, listings, reputation management, analytics, content, and reporting platforms. Agentic workflows create an opportunity to connect those functions more closely and automate many of the repetitive tasks that consume operational resources today. An AI agent could identify declining visibility in a market, analyze competitive positioning, detect inconsistencies in business information, recommend corrective actions, generate optimized content, and deploy updates across hundreds of locations. Rather than simply generating insights, the system becomes capable of executing work.

Opening the platform gives agencies and technology partners greater flexibility to build those types of workflows themselves rather than waiting for vendors to create them. As brands increasingly seek ways to operationalize AI across marketing functions, that flexibility could become a meaningful competitive advantage. The broader implication is that agentic marketing may evolve less as a collection of standalone tools and more as an interconnected ecosystem built on shared infrastructure.

Betting on the Infrastructure Layer

The larger story behind today’s announcement is not developer access or APIs alone. It is Yext’s belief that the mechanics of customer discovery are changing and that marketing technology must evolve accordingly. If AI-generated recommendations continue gaining influence, the companies that provide trusted business data, visibility intelligence, and execution infrastructure could become increasingly important participants in the marketing ecosystem.

The question is becoming less about whether AI will influence customer discovery and more about how they will compete in an environment where AI systems increasingly shape consumer decisions. By opening its platform to partners and developers, Yext is seemingly echoing the view that the next phase of marketing is an ecosystem challenge rather than a product challenge.

The winners in agentic marketing may not simply be those building the best AI tools, but the infrastructure that enables those tools to work.

Digital advertising has long operated with two separate measurement systems. On one side sit performance metrics such as clicks, conversions, cost per acquisition (CPA), and return on ad spend (ROAS). These indicators provide near real-time visibility into campaign activity and allow marketers to optimize media while campaigns are running. On the other side are brand metrics such as awareness, ad recall, consideration, and purchase intent. Those measurements often arrive days or weeks after a campaign concludes, making them useful for evaluation but far less useful for optimization.

For agencies and brands, that separation has become increasingly difficult to justify as marketers face growing pressure to demonstrate both short-term performance and long-term brand impact from the same media investments.

“Advertisers face immense pressure to prove both immediate performance and long-term brand impact,” Matt Sauls, General Manager of the Technology Division at Basis, told Street Fight.

That challenge sits at the center of a new partnership between Basis and Cint, which brings Cint’s Lucid Measurement technology directly into the Basis platform. The integration allows advertisers to launch and manage brand lift studies alongside campaign execution, turning brand measurement into a workflow that operates within the campaign itself rather than outside of it. The announcement reflects a broader shift occurring throughout the advertising industry. As AI and automation make campaign planning, buying, and optimization faster, marketers are increasingly searching for measurement systems that explain not only what happened, but why it happened.

Bridging the Gap Between Brand and Performance

Performance marketing has traditionally benefited from immediate feedback loops. Marketers can quickly identify which audiences, channels, and creative assets are generating engagement and conversions, allowing budgets to be adjusted while media is still in market. Brand measurement has typically followed a different path, relying on separate studies and reporting cycles that often arrive after a campaign has concluded.

Traditional brand lift studies frequently require separate setup processes, manual implementation steps, independent reporting workflows, and coordination across multiple vendors. While these studies can provide valuable insights into awareness and consideration, they rarely influence the campaigns they are measuring because the results arrive too late to affect decision-making.

Basis believes that model no longer aligns with how modern media teams operate. By embedding Cint’s technology directly into the campaign workflow, the company is attempting to eliminate many of the operational barriers that have historically limited the use of brand lift measurement.

“By integrating Cint’s brand lift technology into Basis, we’re not just giving them access to great measurement technology, we’re removing all the setup inefficiencies that have always come with it,” Sauls said. “They can do everything in a single platform, skip the complexity of manually trafficking measurement tags, and get streamlined reporting in one place.”

The goal is not simply to make brand measurement easier. It is to make brand metrics relevant while campaigns are still active.

Turning Brand Lift Into an Optimization Signal

The most significant aspect of the integration may be its ability to make brand metrics actionable while campaigns are still live. Using Cint’s technology, advertisers can measure awareness, ad recall, and purchase intent on an ongoing basis once survey response thresholds are met. Rather than waiting until a campaign concludes, marketers gain daily visibility into how audiences are responding and can use those insights to guide optimization decisions.

That creates a fundamentally different role for brand lift measurement. Historically, brand lift studies have functioned primarily as validation tools used to assess campaign performance after the fact. Under this model, those same metrics become inputs for active campaign management.

For agencies managing omnichannel campaigns across display, video, connected TV, audio, and other channels, that distinction matters. A campaign may be generating strong engagement or conversion metrics, but brand lift data can provide additional context about whether those interactions are improving awareness, strengthening recall, or increasing purchase intent among target audiences.

If marketers discover that certain audience segments are generating stronger consideration or purchase intent than others, they can potentially adjust targeting, creative strategy, or budget allocation before a campaign ends. The result is a feedback loop that connects consumer perception directly to campaign execution.

According to Cint, this ability to connect measurement and activation more closely is becoming increasingly important as advertisers seek faster insight into how consumers are responding to campaigns.

“Cint has gained traction in the market because we provide agencies and brands with high-quality intelligence about how people are reacting to ads faster than traditional measurement methods,” said Daniel Robinson, Senior Director of Measurement at Cint. “By working with Basis to unify measurement with execution, we are helping advertisers put brand insights into action while campaigns are still live, enabling smarter optimization and stronger business outcomes.”

The Rise of the Advertising Operating System

The partnership also reflects a larger trend across advertising technology. Over the last decade, many organizations assembled campaign workflows from a collection of specialized planning, buying, measurement, and reporting tools. While those solutions often delivered strong individual capabilities, they also introduced complexity, duplicate processes, and fragmented decision-making.

Increasingly, ad-tech providers are moving toward unified operating environments that bring planning, activation, optimization, and measurement into a single platform. Basis has positioned itself as an advertising operating system capable of generating media plans from campaign briefs, activating omnichannel campaigns, and managing execution across channels. By embedding Cint’s measurement capabilities directly into the platform, the company is extending that vision to include brand metrics as a native part of campaign management.

The integration includes automated media tracking tag creation, independent measurement from Cint’s consumer panel network, downloadable reporting formats, and consolidated billing through the Basis workflow. While those operational improvements may not generate the same attention as the measurement capabilities themselves, they address a longstanding challenge for agencies and brands: the complexity associated with proving campaign impact.

Why It Matters for Agencies and Brands

The timing of the announcement is significant because the industry is increasingly moving beyond a strict separation between brand marketing and performance marketing. As campaign execution becomes more automated, marketers are placing greater emphasis on understanding how advertising influences consumer perception throughout the customer journey. Clicks and conversions remain important, but they provide only a partial picture of campaign effectiveness.

The broader implication is that awareness, ad recall, purchase intent, and conversion metrics are becoming part of the same decision-making framework rather than separate reporting systems.  If brand lift data can influence optimization decisions while campaigns are still running, measurement shifts from a reporting function into a strategic tool for improving outcomes before the campaign ends.

That may ultimately be the most significant aspect of the partnership … not simply that it measures brand impact, but that it makes those brand metrics available when marketers can still do something about them.

Google recently published its first official guide to optimizing websites for generative AI Search features. For single-location businesses, the guidance is fairly straightforward. For multi-location brands (MULOs), the same principles apply, but the complexity of executing them scales dramatically with every location you add.

Here’s what the guide says, and what it actually means if you’re managing 50, 500, or 5,000 locations.

How Google’s AI Search Features Actually Work

Google’s AI features rely on two core techniques. The first is retrieval-augmented generation (RAG), where AI Overviews and AI Mode (powered by the Gemini AI model) query Google’s existing search index to retrieve relevant pages, then synthesize that information into a response with supporting links. The second is query fan-out, where the AI runs multiple related queries simultaneously to build a more comprehensive answer from different angles.

The key takeaway here is that Google’s AI is not working from a separate data source. It’s pulling from the same search index that traditional SEO revolves around, which includes Google Business Profile data for businesses with physical locations or service areas. So, if your web pages rank poorly or your GBP listings aren’t fully optimized, your AI visibility can suffer in exactly the same ways your organic visibility does.

Duplicate Content Is a Bigger AI Search Problem Than You Think

Google’s guide reiterates the importance of reducing duplicate content as part of a strong technical SEO foundation. For MULOs, this is a significant operational challenge that deserves attention.

Most multi-location brands use templated location pages, and many of those templates produce near-identical content across hundreds of URLs. Swapping out the city name and address does not make a page unique. Google’s AI is specifically designed to surface content with a unique point of view and non-commodity information. In other words, content that provides real insight rather than repeating generic information.

That means each of a MULO brand’s location pages needs specific optimization. Localized content should reflect genuine differences, including regional service variations, location-specific staff or history, locally relevant FAQs, and neighborhood context.

On the technical side, the guide also emphasizes crawlability, semantic HTML, and good page experience as prerequisites for Google’s AI to access and use your content at all. At MULO scale, these issues tend to get buried. Indexing gaps, slow-loading location pages, and JavaScript rendering problems across a sprawling site architecture can quietly exclude large portions of your footprint from AI-generated results entirely.

GBP Optimization Is Non-Negotiable

The guide is explicit that Google’s AI, Gemini, relies heavily on Google Business Profile data when generating local recommendations. Wrong hours, missing categories, an incorrect primary category, or an incomplete services list can all reduce a location’s visibility in AI-generated responses.

For a single-location business, keeping a GBP updated, accurate, and optimized is a relatively straightforward task that can easily be done manually. For an enterprise-scale MULO with hundreds or thousands of locations, it’s one of the most operationally demanding challenges in local SEO.

Business information gets outdated. Listings get edited by third parties or flagged incorrectly. Seasonal hours need updating. New services need to be added. Primary categories need to be audited periodically as Google’s category taxonomy changes.

Doing this manually at scale is not realistic. This is where an AI agent purpose-built for local SEO, such as Local Falcon’s Falcon Agent, truly shines. The agent can manage GBP listings across your entire footprint, automate routine optimization tasks, create and schedule posts, reply to reviews, and surface actionable insights across locations, all without requiring a dedicated team and countless hours of manual local SEO work.

Creating Useful Content Across a Large Footprint

Beyond GBP, the guide puts significant weight on content quality. Specifically, Google emphasizes that AI search features are designed to surface content that is helpful, reliable, and people-first, with a genuine point of view rather than generic information anyone could find anywhere.

For MULOs, this raises the question of how to produce that kind of content at scale without it becoming homogeneous. The answer is not to completely get rid of templates and write every location page from scratch; that’s simply not scalable.

Instead, brands should build templates that pull in genuinely unique data points per location and establish a clear process for adding real local context where it exists. Think franchisee spotlights, local service nuances, and community-specific details. Google’s AI needs something to differentiate one location from another. Give it that, and it will.

Tracking AI Visibility Across Your Footprint

None of this optimization work means much without measurement. MULOs need visibility into how their locations are appearing, or not appearing, across Google AI Overviews, AI Mode, and Gemini.

Tracking Share of AI Voice (SAIV) at scale helps brand and agency teams understand which locations are underperforming in AI results, what sources Google’s AI is pulling from, and where gaps in GBP data or content quality are costing you visibility.

Treating SAIV as a core performance metric alongside traditional local search rankings (local pack performance) is crucial for ensuring MULO brands earn and retain visibility across Google’s generative AI search features as they continue to grow in prominence.

Google’s recent guide reinforces something MULOs should already know: local search success comes down to accurate data and genuinely useful content, across owned web pages and GBP listings. At enterprise scale, achieving this requires the right tools and automations.

Growth creates a unique challenge for franchise organizations. Every new location expands revenue opportunities, but it also adds complexity. More locations mean more local marketing channels to manage, more reviews to monitor, more business listings to maintain, and more customer interactions that require attention. At a certain point, growth itself begins to change how marketing must operate.

That challenge is becoming increasingly relevant for The Goddard School. One of the largest early childhood education franchise systems in North America, the company recently reported a record first quarter, awarding 35 new franchise licenses and opening 10 new schools through April 2026. The expansion builds on strong momentum from 2025, when the organization signed 84 franchise agreements and opened 28 new schools across eight states. Today, The Goddard School operates more than 675 schools serving nearly 100,000 children nationwide.

The growth reflects continued demand for premium early childhood education, but it also highlights a broader issue facing many franchise organizations. As networks expand into hundreds of locations, maintaining a consistent and effective local presence becomes increasingly difficult. Every school needs to remain visible in local search, actively manage its reputation, engage prospective families, and maintain accurate information across a growing number of digital channels.

For many franchise systems, those responsibilities still fall largely on local operators. But as digital marketing expectations continue to rise, that model becomes harder to sustain. Franchisees are expected to manage reviews, maintain social media activity, respond to customer questions, update listings, and support customer acquisition efforts while simultaneously running their businesses. The challenge is no longer understanding the importance of local marketing. The challenge is finding the time and resources to execute it consistently.

Growth Changes the Nature of Marketing

Early-stage franchise growth is often driven by customer acquisition and brand awareness. As organizations mature, however, operational consistency becomes just as important. A network with hundreds of locations cannot rely solely on centralized marketing campaigns. It also needs systems capable of supporting local execution at scale.

That reality is especially important in categories built on trust. Parents evaluating childcare and early education providers frequently begin their decision-making process online, reading reviews, comparing local options, and researching reputation long before they visit a location. Visibility in local search results, review responsiveness, and community engagement all influence how prospective customers evaluate a business.

As The Goddard School continues expanding into new markets, ensuring that every location maintains a strong local presence becomes both a marketing challenge and an operational one.

Franchise Support Is Expanding Beyond Operations

The Goddard School’s growth has been accompanied by continued recognition for franchisee support. Earlier this year, the company received FRANdata’s TopScore FUND Award for the fourth consecutive year, reflecting the strength of its franchise model and support infrastructure.

Historically, franchise support has focused on areas such as financing, training, operations, and site development. Increasingly, however, marketing execution is becoming part of that equation. Franchise organizations are recognizing that helping operators succeed today requires more than providing guidance. It requires helping them manage an expanding set of digital responsibilities that directly influence customer acquisition and business performance.

That shift is driving new thinking about how local marketing gets done.

From Marketing Management to Marketing Execution

For years, franchise marketing technology focused on providing tools. The assumption was that local operators could use software platforms to manage social media, reviews, listings, and customer engagement on their own. While those tools remain important, many franchise organizations are discovering that access to technology alone doesn’t solve the underlying execution challenge.

The Goddard School’s recent marketing initiatives reflect a broader trend emerging across multi-location businesses. Rather than simply giving franchisees more tools, organizations are increasingly looking for ways to automate routine marketing activities and reduce operational burden. The goal is not to replace local engagement, but to eliminate repetitive tasks that consume time without creating meaningful differentiation.

This is where AI is beginning to play a larger role. By automating portions of reputation management, customer engagement, and local marketing workflows, franchise systems can help operators remain active and responsive without requiring constant manual intervention. The significance isn’t necessarily the technology itself. What matters is the ability to maintain consistency across hundreds of locations while freeing franchisees to focus on customer experience and community relationships.