AI search can turn a broad local query into a specific request: a business with a particular service, an available appointment, suitable amenities, and a workable location. A listing that supplies only a name and opening hours may not answer enough of that request.

That was the framing from a September 24 webinar, "Google On What's Next In AI Search + 5 Local Marketing Strategy Fixes," featuring Google's Caroline Dissaux, Adecco's Bonnie White, and Uberall's Krystal Taing. Google representatives described longer, more conversational searches and AI features that break complex requests into related questions. Taing's practical point: the familiar work of maintaining local information now has to hold up across every location.

Why specific queries need better location data

A customer asking whether a nearby location offers a service this weekend needs more than an address. Taing said businesses should make categories, attributes, services, menus, inventory, and availability both complete and consistent across their site, Google Business Profile, and other relevant surfaces. Consistency does not mean identical copy everywhere. It means customers and search systems should not encounter conflicting facts.

Taing framed the change directly: "Most of us really have been talking about these things for years. What's different is the scale, the complexity, and importance of getting these right across every location and what it means to LLMs and generative AI." (31:19)

That distinction matters for chains. A strong brand-level presence does not establish that each branch can meet a specific request. It also makes a location-by-location data audit more useful than assuming one national profile represents every store.

What to add to a Google Business Profile

Dissaux and White recommended concrete ways to keep Business Profile information fresh. These are content and accuracy priorities, not a guarantee that any single field will make a business appear in an AI answer.

Publish relevant updates, offers, and events. Google Posts can carry timely details, including event dates and offer information. Keep the cadence realistic for the business rather than copying a social-media schedule.

Connect social accounts and refresh images. Link existing social profiles to the Google Business Profile, and update photos or videos when products, spaces, or seasonal details change. A brand-wide social account is still usable when a location-specific one does not exist.

Supply structured menus or detailed services. Food businesses can list menu items, ingredients, and current prices rather than relying only on a photo of a customer-uploaded menu. Service businesses should describe offerings in their service lists; they do not need to invent a food-style menu.

Respond to reviews and keep contact options current. Reviews add customer-specific context the business's own profile cannot supply. Responding also gives teams a chance to learn which experiences or offerings need clarification. Make the available messaging channel easy to find where appropriate.

Measurement questions remain open

In the Q&A, Taing said Google Business Profile post views and clicks can now help teams assess individual posts, but those figures do not establish that a post caused visibility in AI Overviews or AI Mode. She suggested comparing post topics with the queries and AI answers a business actually sees. Dissaux cautioned that there is no clear-cut metric tying posts directly to AI visibility.

For brands posting across many locations, the speakers said the same promotion can technically be reused, but local details make it more useful to a person deciding where to go. They also advised adding prices only when the business can keep them accurate. A service with variable pricing may be better described clearly without an unreliable figure.

Five fixes to put into practice

Automation can help a central team handle the volume, but Taing argued that people still have to decide the standards and exceptions: "It doesn't mean that a human needs to manually review every single thing. You know, you can have models, you can have these elements, but it does mean that humans should be the ones establishing the strategy, the standards, the guardrails." (38:29)

Using that division of labor, the session's guidance reduces to five steps:

1. Establish one source of truth for each location. Audit hours, categories, attributes, services, menus, inventory, and booking details. Fix conflicts before syndicating updates.
2. Close the review gap. Set ownership and response standards, then use recurring customer feedback to identify missing information and location-specific problems.
3. Localize content at scale. Reuse approved offers where appropriate, but add accurate neighborhood, service, image, or location details instead of distributing generic copy alone.
4. Automate with human judgment. Let systems flag missing fields and routine updates. Require human review for policy, brand-sensitive claims, unusual complaints, and exceptions.
5. Measure at the location level. Track a consistent set of customer questions and AI answers for individual locations and competitors, then compare those observations with profile engagement and actual business outcomes over time.

The full on-demand webinar walks through Google Business Profile examples and Uberall's approach to scaling these checks. Its most useful takeaway for teams with many locations is not to add every field at once, but to give each location an owner, a source of truth, and a way to detect gaps.

The organizers have announced a follow-up session, "A New Place To Look: Where Your Next AI Citations & Clicks Come From," in which Lisa Salvatore, Sr. Manager of Integrated Marketing at CallTrackingMetrics, will cover how to pull AEO insights, FAQ content, and real customer phrasing out of data teams already collect. Her colleague Brian Barranger, Sr. Account Executive III, will cover what a qualified conversion actually sounds like and how that evidence sharpens targeting, scoring, and product-team requests.