Google reviews describe what customers experience at your locations. Beyond star ratings, their content can help search engines and AI assistants understand your brand. Here is what that means for local SEO and review management across a network of locations.

Try asking an AI assistant to recommend a restaurant, clinic or auto repair shop in your city. Depending on the tool and the search, it may suggest a few names and explain its choices.

Where do AI recommendations come from?

An answer may draw on several sources: your website, business listings, directories, articles and customer reviews accessible to the engine. Sources vary with the tool and question. Attributing every recommendation solely to Google reviews would be misleading.

For multi-location brands, reviews remain a useful source of information about service, wait times and experiences that brand communications may not capture.

Local SEO, GEO and AEO: what is the difference?

Local SEO focuses on a business location’s visibility in searches associated with a place. GEO and AEO describe related goals:

SEO — Search Engine Optimization: improve visibility in search engine results.

GEO — Generative Engine Optimization: support the inclusion of content or brands in AI-generated answers.

AEO — Answer Engine Optimization: make information easy to use in a direct answer.

These approaches overlap. Google explains that SEO best practices remain relevant to its AI features. No technique guarantees a citation or recommendation.

Google reviews: why the text matters too

Google says review volume and positive ratings can help local rankings, alongside factors such as relevance and distance. Review text adds context by describing what customers experienced. These local ranking factors should not be mistaken for a universal formula for AI recommendations.

Google source: AI and SEO