Closing the Franchise Gap: Local Marketing in the Age of AI (2026 Report)

Key findings

Franchise organizations have always confronted a structural tension between top-down brand control and local marketing execution. Who makes the decisions and who does the work? Over the years, various franchise organizations have sought to overcome that barrier, often with the help of software tools and technology, but never with complete success.

AI now offers a new and perhaps unprecedented opportunity for greater brand-local franchisee collaboration, efficiency and execution. AI is transforming marketing in multiple ways. Brands and local franchisees are on board; however strategy and execution remain a work in progress.

To determine the state of local franchise marketing in the age of AI, Uberall partnered with market research firm Dialog on a new survey of 352 respondents from US franchise organizations (43% brand-side, 57% franchisees) in the retail, restaurant, services and other industries in March 2026. We supplemented the survey with a set of qualitative respondent interviews for additional insights and context.

The findings reflect a market in transition, with rising expectations. But they equally reveal confusion, basic execution challenges and limited visibility into what’s actually working.

Summary of findings

Franchise brands control marketing strategy, but franchisees carry much of the local execution burden. While both groups recognize the importance of local marketing, franchisees see it as more critical than brands do.

Both groups use multiple local marketing channels and tactics, but they suffer from a variety of shared challenges and success obstacles, including:

• Not understanding what’s working
• Confusion about what content to produce
• Updating business information across the web
• Growing and responding to reviews
• Not enough budget
• Coordinating internal teams
• Too many marketing channels

When it comes to AI, adoption is approaching 90%. But despite these high penetration rates most franchise brands are still experimenting rather than fully committed. And both groups see AI search as important, though there's no consensus about what actually drives visibility.

Who controls local marketing in franchise systems?

Brands do, according to a majority of both groups. 39% of brands and 35% of franchisees describe marketing as fully centralized, and another 30% and 38% as mostly centralized with some local control. Only 25% of brands and 20% of franchisees share responsibility. Franchisees typically execute the local campaigns, following brand guidelines.

Marketing strategy and decision-making generally reside at the corporate-brand level but substantial responsibility for marketing execution falls on local franchisees. While every franchise is somewhat different, a majority from both groups agree that brands control or dictate marketing strategy and decisions with only limited discretion or control at the local level.

Yet franchisees are the ones that typically execute local campaigns, in compliance with brand guidelines, many times in ways that are inconsistent or sub-optimal.

The logic of top-down marketing control makes sense, in principle, as corporate entities seek to protect and promote their brands. However, there’s often a lack of coordination, creating friction and inefficiency at the local level.

A hybrid model involving shared responsibility is the minority scenario, with only 25% of brands and 20% of franchisees utilizing that approach.

The survey found broad alignment in channel utilization between brands and their franchisees. However, a range of challenges often compromise local marketing effectiveness:

• Inconsistent local execution: Brands launch promotions with specific messaging and timing, but franchisees may not run campaigns as intended, undermining local impact.
• Review management breakdowns: Individual franchisees often improvise, offering forbidden incentives for review generation or neglecting reviews in ways that damage brand reputation both locally and nationally.
• Listing updates and changes: Website and business listings updates may be made by brands without franchisee input causing broken location pages, duplicate listings and citation inconsistencies that harm rankings.
• Image and content gaps: Generic brand assets don’t accurately capture or reflect the character or look and feel of individual locations. But developing and deploying authentic local images and content can be surprisingly challenging.
• Off-brand local marketing: Frequently under-supported by brands, franchisees may create their own ads or promotions and social posts that aren’t fully brand compliant.
• Attribution challenges: Connecting online marketing to in-store traffic and sales is desirable but very challenging. Both brands and franchisees said they have limited or no visibility into what's actually working.

Customer spotlight: Pizzaville

Customer spotlight: Burger King Belgium

How important is local marketing to franchise brands and franchisees?

Both groups rate it highly. 29% of brands call local marketing critical and 59% very important, and more than 90% of franchisees rate it very important or critical. Franchisees are more likely to call it critical (39% vs. 29%) and generally focus on local foot traffic, while brands often focus on awareness.

Local marketing is considered “very important” or “critical” by the great majority of brands and franchisees surveyed. About 29% of brands said local marketing was “critical,” while 59% said it was “very important” to their success. More than 90% of franchisees agreed. However, the number of franchisees who said local marketing was “critical” to success was 10 points higher than for brands (39% vs. 29%). Brands are often focused on building awareness, while franchisees are generally trying to drive local foot traffic and store visits.

Both groups largely agreed on marketing channel prioritization, with a few differences. Local listings management, for example, ranked higher for franchisees (3rd of 9 channels) than for brands (8th), while brands expressed higher adoption rates of every channel, by 10 points or more on most of them.

The broader utilization of channels by brands argues for greater sophistication, more bandwidth and higher budgets than local franchisees. Yet local franchisee budgets were not insignificant; 71% of franchisees reported marketing budgets of more than $200K per year, with 37% allocating more than $500K. These are real budgets.

What are the biggest local marketing challenges for franchises?

Measurement is the most cited obstacle. 52% of brands and 51% of franchisees name tracking and understanding what’s working. Growing and responding to reviews (41% and 42%) and updating business information (34% and 38%) come next for both groups. Franchisees are more likely than brands to cite too many marketing channels (36% vs. 27%).

Despite these budgets, franchisees (and brands) face serious challenges around local marketing execution and especially attribution.

Measurement is the top pain point for everyone in the survey. Just over half of both groups said that understanding what’s actually working was the biggest barrier to local marketing success. Both groups have multiple success and attribution metrics, but neither is very confident about the frameworks they’re using.

Increased revenue was the top success metric across the board. Yet mapping marketing to revenue is at best thoughtful guesswork if attribution is opaque. Tracking and attribution have been challenges since the beginning of the internet and they remain so for many digital marketers. However the risk is that poor attribution could easily result in a misallocation of budgets.

It’s surprising that foot traffic/store visits are more widely used by brands and local franchisees are more focused on website traffic and social media engagement: online measurements. This may be because many franchisees lack the ability to connect store visits to specific campaigns or promotions.

Brands were also more focused on ratings and reviews, which wasn’t in the top 5 for the franchisees. While not universally true, many franchisees neglect local reviews and don’t have disciplined review management programs.

After tracking and attribution, reviews and listings management were the next significant challenges for both groups. These are foundational elements of local marketing. Many respondents seem to be struggling in these basic areas, despite the availability of tools and technology platforms to manage and support these functions.

Franchisees are more likely to be overwhelmed by the number of marketing channels they feel compelled to use. In interviews, several franchisees addressed this by simply focusing on the channels and promotional tools they were most comfortable with (e.g., social media) rather than taking a more systematic approach to marketing. Franchisees are also less certain than brands about what content to produce.

Surprisingly, some brands reported “not enough budget” as a local marketing challenge. This may reflect ambitious multi-channel programs. It could also be a statement of confusion over what’s working: they need to cover more channels because of that uncertainty.

It’s striking that both brands and franchisees are struggling with the same foundational issues. The result is a system where strategy is centralized, but execution is distributed and nobody has real visibility into what’s working.

How widely do franchise brands and franchisees use AI?

88% of brands and 89% [TO VERIFY] of franchisees use AI. Most are in the early-to-mid stages, and franchisee interviews indicate that use is often individual and task-based, outside any formal process. 53% [TO VERIFY] of franchisees started in the past 12 months, compared to 43% of brands, and 63% of brands push AI adoption on their franchisees.

AI adoption: broad & shallow

When asked about AI adoption, almost 90% of both groups said they were using AI (brands 88%, franchisees 89%). However, “using” is a broad term that doesn’t capture AI sophistication or the degree to which it has been operationalized and integrated into workflows.

The data shows that both brands and franchisees are generally in the early-to-mid stages of AI adoption, but franchisees are moving somewhat faster.

Franchisee interviews indicate, however, that AI adoption is often used by individuals within the organization for selected marketing purposes or tasks but not part of a formalized process.

Notably, 53% of franchisees started using AI within the past 12 months, compared to 43% of brands. However, 63% of brands are actively pushing AI adoption on their franchisees: 40% require it across multiple functions and 23% for specific use cases. Another 25% recommend AI but do not mandate it. The mandated usage can appear in the form of industry specific SaaS tools with AI features.

In these organizations, marketing, sales and customer support (i.e., website chatbots) dominate AI deployments. Business intelligence and analytics also rank highly. In practice, what this means will vary widely by organization.

Differences appear in how AI is deployed after these dominant functions. Brands show wider adoption across functions, including reputation management (37%), product development (33%), and human resources (31%). Franchisee use is concentrated in operations/logistics (31%) and finance/accounting (31%).

The biggest gap is around reputation management. Despite it being a significant challenge, only 26% of franchisees report using AI for review management, compared to 37% of brands. This suggests a disconnect between operational pain points and AI adoption by franchisees.

As previously mentioned, it’s not clear how well integrated AI tools are into daily processes and workflows. The interviews indicated there was a mix of SaaS tools with AI features, vertically specialized AI point solutions and use of foundational LLMs (e.g., Gemini, ChatGPT) for ad-hoc marketing functions.

Customer spotlight: SUNMED | Your CBD Store

Does AI search influence purchases without a click?

Most respondents believe it does. 86% of franchisees and 78% of brands say AI search definitely or probably influences purchase decisions even when it sends no website traffic. 82% of franchisees and 69% of brands call appearing in AI results very important or critical, and 63% of franchisees track their AI appearances, compared to 47% of brands.

Is “AI search” overhyped or an important consumer discovery channel worthy of significant marketing resources? This is a heated debate among digital marketers.

AI critics and skeptics often cite the statistic, “AI-generated referrals currently account for only about 1% of total website traffic.”¹ That datapoint is used to argue that marketers are giving AI too much weight and attention vs. traditional Google.

Traffic referrals don’t tell the full story or reflect AI’s actual influence on purchase behavior. AI users often do extensive research and discovery without ever clicking-through to a website.

Seeking to confront this issue, the survey asked, “Do you think AI search/research influences customer decisions even when it doesn’t send direct website traffic?” Both brands (78%) and franchisees (86%) agreed, AI “definitely” or “probably” influences purchasing decisions in the absence of site visits. Franchisees more strongly believed that proposition than brands.

86% of franchisees say AI search drives purchases, even without a click. 78% of brands say the same.

Given the belief that AI affects buying decisions without clicks, it follows that both groups say being visible in AI results is “critical” or “very important.” Again, franchisees place somewhat higher importance on appearing in AI search results than brands (82% vs. 69%).

The attribution problem rears its head again in this AI search context. A majority of franchisees (63%) say they are tracking their AI appearances compared to 47% of brands. A lot of this tracking is fairly manual at this point.

In addition, a majority of franchisees (74%) consider their AI visibility and optimization strategies to be “strong” (41%) or “very strong” (33%). This is probably a generous self-assessment.

¹ Search Engine Land, November 2025: https://searchengineland.com/ai-1-traffic-mostly-chatgpt-464653

How are franchises approaching AI search optimization?

Both groups rank reviews, images and video, and social media as the top drivers of AI visibility. 67% of franchisees and 50% of brands have shifted budget from other channels or used experimental funds for AI optimization. 86% of franchisees and 75% of brands expect AI search visibility to become extremely or very important over the next three years.

The survey asked both groups about things that affect AI visibility including reviews, business data, citations and several other factors. There was general agreement that reviews, images/video and social media were the top three drivers of AI visibility, in different order for each group.

Following those three, in a second tier, were fresh local content, structured data, inventory data and other content types. Local landing pages and citations appear in the third tier. These rankings indicate they’re on the right track but also express a lack of confidence (in fairness, AI optimization is an evolving discipline).

Brands and franchisees are likely drawing upon their understanding of local SEO rather than a distinct AI visibility strategy. And the difference between GEO/AEO and SEO is also a matter of evolving debate. A plurality of respondents (50%) from both groups said they believed SEO and AI optimization are distinct but with “some” overlap.

The survey asked about budget allocations and whether respondents had:

• Shifted money from other channels to AI
• Used money from an “experimental” budget
• Expanded the marketing budget overall

A majority in both groups reported that money had in fact been reallocated to support AI optimization.

Just over two-thirds (67%) of franchisees said they had moved budget from other channels (26%) or drawn upon from experimental funds (41%). That compares to 50% of brands, which moved money from other channels or tapped experimental budgets (31%). Brands were more likely than franchisees to fund AI optimization through budget expansion. Finally, 27% of brands and 13% of franchisees had not deployed funds to support AI optimization or were simply not attempting to optimize.

Brands and franchisees both believe AI search visibility will only increase in importance over the next three years; 86% of franchisees and 75% of brands said it would become “extremely” or “very” important. And brands are considering increasing their AI investments overall. A majority (53%) say they will increase spending “modestly,” while 22% expect to make “significant” spending increases.

What is Location Performance Optimization (LPO)?

Location Performance Optimization (LPO) is Uberall’s name for managing visibility, reputation and engagement across Google, social media and AI search. It is designed for the structure of franchise organizations: it connects brand strategy with local execution and uses AI to turn fragmented activity into a managed, measurable system. Its four pillars are visibility, reputation, engagement and outcomes.

A new operating model

Traditional local SEO was built for a world where Google was the alpha and omega of local discovery. That is changing, as purchase journeys become more complex and customers move between Google, social media sites and AI-generated search before deciding what to buy or where to shop.

While the industry debates what to call the emerging discipline of managing visibility, reputation and engagement across all these channels, Uberall has dubbed it Location Performance Optimization (LPO), a model designed for the unique structure of franchise organizations. LPO connects brand strategy with local execution, using AI to turn fragmented activity into a managed, measurable system.

AI platforms increasingly provide conversational answers rather than ranked results that require further investigation. If a franchise brand doesn’t appear, it may be excluded from consideration. This shift requires a broader view of location visibility and performance across a range of sites and platforms where customers search, including AI interfaces.

This can be understood across several pillars:

• Visibility: Across search, maps, social, and AI results
• Reputation: Accurate and correct business data, ongoing reviews
• Engagement: Regular updates, posts, and responses signaling activity
• Outcomes: Visits, calls, and transactions generated by that activity

All these elements reinforce and support one another. Fragmented approaches, where listings, reviews, and content are managed independently, miss out on the benefits of coordinated management. And this is the central problem identified in the survey:

Strategy is defined centrally, but execution happens locally and inconsistently.

Operational priorities

Data consistency and accuracy remain foundational in the AI era. When location data is fragmented or outdated, trust and visibility decline. Standardizing core business information across platforms is critical. Yet, as the survey showed, updating business information remains a surprisingly significant challenge for both brands and franchises.

Content is even more important as discovery becomes conversational and intent-driven. Location-specific FAQs and service descriptions must better reflect actual customer needs, while a regular flow of reviews (and responses) strengthens credibility.

Measurement and visibility gaps

Most organizations lack a clear view into how often their locations appear in AI-generated results. Tracking is often manual and inconsistent, and visibility changes by platform, search query and location. AI sources can change quickly and sometimes be difficult to identify, let alone influence. Without consistent measurement, visibility gaps remain elusive or invisible.

Fragmentation to coordination

Across platforms and channels, the ultimate objective remains consistent: connecting marketing activity to real-world outcomes. Signals such as listings accuracy, review activity, engagement, and visibility must translate into actions: calls, visits, and revenue.

The survey shows that these signals are often managed in isolation, executed unevenly and measured inconsistently. This creates the inefficient system characteristic of most franchise brands today.

This combination of fragmented execution, inconsistent data and unreliable measurement are the core challenges the survey captures. It raises the critical question for all franchise operations: how do you move from disjointed and fragmented brand-local activity to improved systemwide performance?

How can franchises close the local marketing gap?

AI can act as an orchestration layer that serves brands and franchisees simultaneously. Brands gain an improved ability to keep listings accurate, reviews addressed and content within guidelines across locations. Franchisees get potential relief from deciding what content to produce, managing reviews, keeping business data current and choosing channels. The structural tension between central strategy and local execution remains.

As we’ve discussed, the core challenge in franchise marketing is structural: brands dictate strategy, franchisees execute, and visibility into performance is limited or broken. AI does not eliminate those challenges. But it introduces something that hasn’t existed before: a kind of mediation or orchestration layer that can serve both sides of the franchise relationship simultaneously.

For brands, that means an improved ability to maintain guidelines and consistency at scale, ensuring listings are accurate, reviews are addressed and content meets guidelines across locations without relying on franchisee discipline alone. For franchisees, it means potential relief from a significant operational burden: figuring out what content to produce, managing reviews across locations, keeping business data current, determining which channels matter.

AI-enabled Location Performance Optimization offers an integrated model where brands and franchisees coordinate from the same foundations across platforms and channels to improve local visibility, reputation, engagement and conversions.

And when execution is coordinated and observable, brands and franchisees gain confidence and visibility into what’s working to make more disciplined marketing investments.

The organizations that adapt and succeed will be those that treat AI not as a collection of tools, but as infrastructure connecting brand strategy and local execution. That shift introduces consistency and efficiency where previously there was variability and fragmentation.

That said, AI is not a panacea. The structural tension between centralized strategy and distributed local execution will persist. But there’s now the possibility that it can be managed systematically rather than improvised by hundreds or thousands of local franchisees.

The brands that recognize and embrace this approach will not just operate more efficiently, they will transform and be able to put more distance between themselves and their competitors.

Survey methodology

The findings in this report are from a survey of 352 qualified franchise respondents fielded in March 2026 using an online panel. Participants were screened to include only individuals operating or working in multi-location franchise organizations with 25 or more locations, up to 500+, in the United States.

The sample includes corporate or brand-side respondents (43%) and local franchisees (57%). A primary objective of the research was to determine how aligned were the two groups in their approach to local marketing and use of AI.

Brand respondents came from retail, restaurants and business services, among several other industries. Those same groups also dominated franchisee respondents.

Survey respondents came from a variety of organizational roles. Brand representatives were from customer service/support, operations/management, marketing and IT. Franchisee respondents were more evenly distributed, representing technology/IT, owner/operators, customer service and operations management.

Both groups answered parallel survey questions to enable direct answer comparisons. The qualitative interviews provided additional color and context for the survey findings.

Frequently asked questions

Who took part in the Closing the Franchise Gap survey?

352 qualified respondents from US franchise organizations with 25 to 500+ locations answered the survey through an online panel in March 2026. 43% work on the brand side and 57% are local franchisees, with retail, restaurants and business services as the largest industries. Uberall ran the survey with market research firm Dialog and added qualitative interviews.

How big are franchisee marketing budgets?

71% of franchisees report annual marketing budgets above $200K, and 37% spend more than $500K. The largest group (34%) spends between $200,000 and $499,999 a year, and 17% spend $1 million or more.

Do franchises track whether they appear in AI answers?

63% of franchisees say they track their AI appearances, compared to 47% of brands. Much of this tracking is still fairly manual. 74% of franchisees also rate their AI visibility and optimization strategies as strong or very strong, which is probably a generous self-assessment.

What do franchises think drives AI search visibility?

Both groups rank reviews and review responses, images and video, and social media posts as the top three factors. Fresh local content, structured business details, FAQs and inventory data form a second tier, and local landing pages and third-party citations form a third.

Do franchises see SEO and AI search optimization as the same discipline?

A plurality of respondents from both groups (50%) say SEO and AI optimization are distinct but with some overlap. Both groups likely apply what they know about local SEO to AI visibility. The difference between SEO and GEO/AEO (generative and answer engine optimization) is still a matter of debate.