The Gap Every Franchise Knows Too Well

Every franchise brand runs on the same split. Strategy sits at headquarters. Execution sits with the operators who run the locations. It is a model built for scale, but it has a well-known weak point: What HQ designs and what happens on the ground are rarely the same thing.

Uberall's 2026 Franchise Gap report, based on a survey of 300 brands and franchisees, put numbers to that gap. A true hybrid, shared-responsibility model is still the exception, used by just 25% of brands and 20% of franchisees. More than half of both groups (51%) name the same top obstacle: uncertainty over what is actually working. And while roughly 90% report using AI in some form, adoption is broad and shallow rather than operational.

When discovery increasingly happens through AI tools and AI-assisted Google results, inconsistent local data stops being a housekeeping problem and becomes a visibility problem. Franchisees feel it first: 82% say AI search visibility is very important or critical, compared with 69% of brands.

For a QSR brand, the question is concrete. When someone searches for the nearest place to get pizza, does the right location show up, with the right hours, the right offers, and reviews strong enough to be recommended?

{{quote}}

‍

Pizza Hut’s Answer: a Hybrid Playbook, Clear Roles

Pizza Hut set out to close that gap rather than manage around it, and it does so with an explicitly hybrid model. The brand does the heavy lifting on consistency in the biggest channels, while franchisees add the local relevance around their own restaurants. As Amparo Gil, who leads digital growth marketing at Pizza Hut, describes it: "Some things are done centrally, and in others the local operators bring the local relevance."

What makes that split work is discipline about who does what. Pizza Hut defines roles and responsibilities up front, sets the pillars it wants to win as a business, then cascades those objectives with measurable metrics and a steady rhythm of check-ins, QBRs, and education on what good looks like. Technology partners are built into that structure rather than bolted on. "We lean on the technology and partners we use, like Uberall, to make sure they’re involved in those conversations and able to support our franchisees," Gil says.

The foundation is data. Uberall keeps Pizza Hut’s location information consistent across the platforms customers and AI engines actually read. Today that means 18,912 listings live across 49 directories, spanning 326 Pizza Hut Delivery locations and 61 Pizza Hut Restaurants. Getting one accurate version of every location in place is what everything else builds on: It removes the broken pages, duplicate listings, and mismatched hours that quietly erode both rankings and trust. Gil is blunt about the stakes: "You don't want to show up at one of our restaurants and find it closed. What a disappointment. So we make sure everything we give the customer is up to date, and we do it in an efficient way."

‍

Local Freedom, Brand Guardrails

The second layer is engagement, and it is where the brand-versus-local pattern usually plays out most visibly. National accounts drive awareness. Local social is what shapes local rankings and, increasingly, whether a location gets cited in AI results.

Pizza Hut’s model gives franchisees room to act without letting the brand drift. HQ runs the always-on-brand social campaigns and anchors them to key moments like the World Cup, along with reusable templates, while operators put budget behind the deals most relevant to their area and see what works locally. Delivered and scheduled through Uberall, that model produced 102 social ad campaigns and helped lift Facebook page media views by 94K, a 143% increase year over year. 

The result is the shared-responsibility model the Franchise Gap report describes as rare, made practical: consistent enough for the brand, flexible enough for the operator.

Why the Right Locations Surface in AI

Ask Pizza Hut where AI actually bites for a QSR and the answer is discovery. Customers are not researching what pizza is, they are searching for the nearest Pizza Hut that is open now, with an offer worth acting on. That puts Google Maps, now functioning more and more like an AI-driven engine, at the center of the strategy, and it puts reviews at the heart of reputation.

No single factor decides whether a location surfaces in AI results; visibility is the sum of several signals. Gil points to the two biggest levers a brand can control directly. 

• ‍Site signals: meaning accurate, complete information on your own site and on Google Maps, account for roughly 24% of the picture, and reviews for around 16%. Together they anchor Pizza Hut’s approach, because both are things the brand can actively manage rather than hope for.
• ‍Reviews are the first thing a customer checks to judge quality, and they have become an entry ticket for AI visibility as well, with some AI tools weighting toward businesses above a review-score threshold. Pizza Hut manages reviews centrally to spot the pressure points, whether the issue is taste, out-of-date information, delivery, or the in-store experience, then cascades that intelligence back to individual restaurants through regular conversations. As Gil puts it, the brand builds the picture centrally but connects locally. The numbers show the foundation is strong: a 4.6 average star rating and a 90% review response rate. 

Visibility followed. Google Maps impressions reached 38.4M, up 212% year over year. Google Directions clicks rose 15% over the same period, and with directions making up 35% of all clicks, that is a direct line from a local search to someone walking through the door. Uberall’s Revenue Estimator puts the associated revenue impact up 15% year over year.

What’s Next: Let the Agents Do the Heavy Lifting

Pizza Hut is early in its AI journey and deliberate about it. They have started using Uberall’s GEO Studio to measure and quantify the impact of AI on the business and are working through the fundamentals before scaling. As adoption grows, GEO Studio will show Pizza Hut:

• how AI engines like ChatGPT, Gemini, and Google AI Overviews describe its brand and each location‍
• AI hallucinations and how to address them
• how to turn Share of Voice gaps into prioritized fixes that lift AI visibility

The direction is clear. Managing fresh, accurate content across thousands of listings and every channel by hand is not feasible for any team, and pushing that work down to franchisees rarely delivers the consistency a brand needs.

For Gil, AI agents are how that gap finally closes. Uberall’s AI agent UB-I gives on-the-go recommendations on how to improve a profile and the quick wins an operator can action today to lift AI visibility. Leaning on those agents, she argues, helps bridge the knowledge gap between brand and franchisee: Anyone can go in, ask a question, and act on the answer. 

That is the operational load AI can carry, orchestrating data across every location, keeping information fresh and trusted, and surfacing what is working so brands and operators finally share one view of performance. It is the same conclusion the Franchise Gap report reaches. The hybrid model franchising has talked about for over a decade is now genuinely achievable, because the tools have caught up.

"AI isn’t going anywhere. It’s only moving forward, so businesses need to get on board and start actioning it. Put the customer at the core, keep your on-site signals up to date, and build a strong process for managing reviews and the reputation you have online."

— Amparo Gil, Digital Growth Marketing Lead, Pizza Hut

* 2026 vs. 2025