AI Now Decides What Customers See About Your Local Business — Here’s How to Audit It

A 3.3-star car wash in Norfolk, Virginia, recently won the top spot in Google’s AI answer for a specific query — not because of its rating, but because it matched the search context. That example, shared by GatherUp’s Annie Jackson and Jason Wertham during a Search Engine Journal session, illustrates a critical shift: AI tools now assemble their own description of each location from reviews, listings, and public web mentions, and then repeat that description to customers who never visit your website.

For Indian businesses with multiple locations — from retail chains to service networks — this means the digital reputation AI systems present may differ from the one on your Google Business Profile. The session, titled “Emergency Brand Audit: What AI Says About Your Locations,” walked through a four-prompt audit that reveals what ChatGPT, Google AI Overviews, and Ask Maps currently say about your brand. The recap below covers the key findings and actionable steps.

Why AI summaries matter for local businesses

GatherUp’s consumer data, collected in fall 2025, shows that 55% of consumers had consulted Google or Bing AI summaries for local information, 48% had asked ChatGPT about a local business, and 31% had asked multiple times. Jackson’s car wash query — “no-touch car wash for my SUV in Norfolk, VA” — is a real-world example. Google returned one business, answered the clearance height and 24/7 hours inline, and presented the 3.3-star rating only after the context. “Google answered my questions, but this business is actually showing up as a 3.3 star,” Jackson said. “It’s surfaced the context of my query above the star rating.”

Wertham added that AI tools now factor in user identity and time of day. “The time of day when you’re actually doing this query in Google Maps could impact which businesses are getting returned,” he said. An LLM that knows you own an SUV or a large dog applies that context to every future local query, whether you restate it or not.

The four-prompt emergency audit

The session’s audit starts from one fundamental shift: customers are already seeing AI-generated answers about your business. The four prompts — from a brand-name query to a location-by-location spot check — reveal exactly what those answers are. The full prompts and the audit handout are available in the on-demand recording.

The four prompts are designed to surface what ChatGPT, Google AI Overviews, and Ask Maps return for your brand. The first prompt asks for a general description of your business. The second narrows to a specific location. The third includes a competitor comparison. The fourth checks a location with a contextual modifier (e.g., “best for families”). The results vary by device, account, and time of day — what Jackson calls “the slot machine effect.”

Republishing reviews where AI can crawl them

A critical insight from the session: Google, Yelp, and other major directories block LLM crawlers from reading review content on business profiles. Reviews still support local rankings and conversion on the listing, but they only enter AI answers through surfaces LLMs can crawl. “The major directory service providers, Google, Yelp, and others, they do not allow LLM tools like ChatGPT and Claude to scrape or crawl the review data on the business listing,” Wertham said. “You’ll notice they’re not citing specific reviews from those platforms.”

The same reviews become crawlable the moment you republish them on public social channels or embed them in review widgets on your own site. “Now they’re fair game for the LLM tools to be pulling in,” Wertham said. This determines which queries you can win. When a customer asks for “popular” or “highly reviewed” businesses, the LLM searches for review text it can access. Review content confined to the directory contributes nothing to that answer.

Action item: Republish your reviews where AI can crawl them. The session covers which widget and social placements make review content readable, including how to carry the business reply with the review.

Build, manage, defend: the three workstreams

The session organises the response into three workstreams:

• Build: Consistent listings across platforms and a steady review volume. Recency and velocity matter more than the average star rating. Wertham noted that 45% of users prioritise review recency over star rating, 60% trust detailed written reviews over rating-only reviews, and 70% prefer a review request within 72 hours of the transaction. “I’d rather go to a business with 1,000 reviews and a 3.9 or 4.2 than 30 reviews and a 5.0,” he said.

• Manage: Respond to reviews within a 72-hour window. Monitor what AI says about your locations regularly.

Key data points

Metric	Value
Consumers who consulted Google/Bing AI summaries for local	55%
Consumers who asked ChatGPT about a local business	48%
Users who trust detailed written reviews over rating-only reviews	60%
Users who prefer review request within 72 hours of transaction	70%

Because LLM answers behave like a slot machine, one query is never a reliable read. Jackson cited SparkToro research where different people asked the same question across devices and accounts, and the results never returned in the same order. Position is the wrong metric for AI visibility. Total citations — the breadth of sources feeding the answer — predicts whether your brand appears at all.

For Indian multi-location brands, the key takeaway is clear: audit what AI says about your locations today, republish reviews where LLMs can crawl them, and build a steady stream of fresh, detailed reviews. The full session recording includes the exact prompts and the rollout framework.

Source: Search Engine Journal – Emergency Brand Audit: What AI Says About Your Locations via @sejournal, @lorenbaker (https://www.searchenginejournal.com/emergency-brand-audit-what-ai-says-about-your-locations-recap/583422/)