How Multi-Location Retail Brands Are Navigating AI Search and Local Discovery
A conversation with leaders from John Lewis, United Rentals, and a prominent department store chain on what's changing — and how they're responding.
Navigating the Shift to AI Search
AI search has changed how customers find businesses, evaluate them, and decide whether to walk in. And for marketing teams managing hundreds or thousands of locations, that shift is forcing hard questions: Is your store data complete enough to be cited? Are you responding to the right reviews? Are your location pages structured properly — for humans and machines?
Recently, we spoke with three marketing leaders who have been on the front lines. One manages digital strategy for a prominent American upmarket department store chain with hundreds of locations. Filipa Silva leads SEO and AI optimization for John Lewis, a UK department store brand. And Amber Wilcox oversees digital marketing for United Rentals, the largest rental fleet in the world.
All three are figuring out the same core challenge: how do you show up in AI search on the brand and local level — in a way that ultimately drives action?
Yext: Our latest research shows that 42.7% of consumers used AI specifically for local search in the past month. What changes are you actually seeing in how customers find you?
Digital strategy manager, department store chain: One of our biggest recent wins has been seeing new stores appear in AI Overviews — and not just for branded searches. When we look up non-branded terms, we’re starting to show up. That's especially notable for stores that haven't even opened yet, where there's very little prior history to pull from.
Filipa Silva, John Lewis: We came to local SEO relatively late; there wasn't a dedicated function before. What we've found is how much the basics matter for AI visibility. Attributes, for example: when we started auditing our listings, so many fields were empty. Getting that information from different parts of the business takes real effort, but it's foundational to how AI models understand what we offer.
Amber Wilcox, United Rentals: We're monitoring how our brand appears in AI-generated search experiences and evaluating where we're being cited. This helps us better understand visibility trends and identify opportunities to improve our presence.
Yext: How has your team's day-to-day work shifted to keep up?
Digital strategy manager: We've gotten very specific in how we describe each store — not just the city, but the surrounding neighborhoods, nearby landmarks, and the practical questions customers actually ask: Is there parking? How does curbside pickup work? Where's the return desk? We've also been careful about platform variation. Your Google Business Profile, your Apple listing, and your store page shouldn't be identical. They should reflect the same message in different ways, native to each surface.
We couldn't do this alone. We've partnered with our brand team, digital merchandising, and our field teams to gather authentic local information. They know things we'd never know at the corporate level — which expressways are nearby, which parks or landmarks are adjacent. We use that data to help draft hyper-local content, and then validate it with the teams before it goes live. It's not fast, but it's working.
Filipa Silva, John Lewis: We've focused on fundamentals first. There's no point making big plans without getting the basics right. That means complete and accurate listings — but it also means changing how we handle reviews. We used to respond only to one- and two-star reviews. The problem is that AI models and Google read engagement as a signal of importance. If we're only engaging with negative reviews, that's what gets surfaced. Responding to four- and five-star reviews signals to the algorithm — and to customers — that there's something worth highlighting.
Amber Wilcox: We've focused on increasing awareness of local search performance across our organization. Sharing performance insights helps teams understand the impact of their local presence and encourages ongoing engagement.
Yext: In a world that’s no longer just about the click, what metrics matter most to you right now?
Digital strategy manager: Reviews are top of mind. AI platforms like ChatGPT and Perplexity tend to surface results with ratings above 4.0 — that creates pressure at scale. And Google has made review solicitation guidelines stricter, so you have to think carefully about how and when you ask. Getting meaningful review velocity across hundreds of locations, especially in lower-traffic areas, is a real challenge. I don't have a clean answer to it.
Filipa Silva, John Lewis: We've moved away from watching where we rank in an LLM response — first, second, or third. Position in an AI answer depends on the prompt and the user's history, so it's not a reliable signal. What we track instead is whether we're being cited at all, our share of voice across different service areas, and sentiment. Those tell us more about what's actually happening.
Amber Wilcox: We're evaluating a variety of visibility indicators to better understand how AI platforms surface our brand and how consistently we appear across different experiences.
Yext: Where do you see the biggest opportunity in the search space today? And what — if any — challenges are you preparing for?
Digital strategy manager: The review challenge is the thing that keeps me up at night. Apple Maps is now using geolocation and reviews as primary ranking signals. AI is aggregating review sentiment automatically. And the parameters around how you can ask customers for reviews keep getting narrower. For a brand our size, without franchisees who have financial stake in the outcome, getting consistent review quality and velocity across every location is genuinely hard — and the consequences of getting it wrong are bigger than they used to be.
Filipa Silva, John Lewis: Map pack position is losing meaning as AI overviews appear first. By the time a customer scrolls past the AI answer, a lot of decisions are already made. So I think about presence and sentiment in those AI results now, more than where we appear in the traditional search stack.
Amber Wilcox: One of the biggest opportunities is building awareness across the organization about the importance of local digital presence. When teams understand their role in maintaining accurate information and engaging with customers, it strengthens overall visibility.
Yext: From your experience over the past year, what advice would you give to other brands navigating this shift to AI?
Digital strategy manager: Start with your data, and get specific. The brands showing up in AI results are the ones that have done the work of creating genuinely local content — something that reflects the actual neighborhood and community, not a templated description pasted across every location. Bring in your field teams. They have information you don't. And accept that this is an ongoing process, not a one-time project.
Filipa Silva, John Lewis: Do the basics first. Making sure your listings are accurate and complete, and that you're engaging with all your reviews — not just the negative ones — is foundational. It's not glamorous work, but without that foundation, everything else is harder to build on.
Amber Wilcox: Success in local search requires collaboration across teams. Creating shared ownership and aligning stakeholders around common goals can help drive stronger and more sustainable results.
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