A 3.3-star car wash just won the AI answer.
When Annie Jackson, Director of Revenue Operations and Growth at GatherUp, asked Google for a no-touch car wash that fits an SUV in Norfolk, VA, Google returned a 3.3-star business and answered the clearance and hours questions above the star rating itself. Query match outranked rating.
That example frames the session Jackson presented with Jason Wertham, Vice President of Review Defense Operations at GatherUp: AI tools assemble their description of each location from reviews, listings, and public web mentions, then repeat that description to customers who never reach your website.
Jackson and Wertham walked through the four-prompt emergency audit they run to surface what ChatGPT, Google AI Overviews, and Ask Maps say about a multi-location brand today, then the build, manage, defend rollout that changes the answer.
The recap below covers the findings. The prompts, the rollout, and the audit handout live in the full session. Watch it on demand.
How Do Customers Use AI To Find Local Businesses Now?
They ask a full question and accept the summarized answer. In GatherUp consumer data collected in fall 2025, 55% of consumers had consulted Google or Bing AI summaries, 48% had asked ChatGPT about a local business, and 31% had asked multiple times.
Jackson’s car wash query shows what that looks like in practice. Instead of “car wash near me,” the search was “no-touch car wash for my SUV in Norfolk, VA.” Google pulled from its 300 million places and 500 million review contributors to return one business, with clearance height and 24/7 hours answered inline.
“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 these tools now factor in who you are and when you ask. “The time of day when you’re actually doing this query in Google Maps could impact which businesses are getting returned in those results,” 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 session’s audit starts from this behavior shift: four prompts, from a brand-name query to a location-by-location spot check, that show you the answer your customers already see. See the four audit prompts.
Do Google Reviews Feed AI Answers?
Not from the listing itself: Google, Yelp, and the other major directories block LLM crawlers from reading review content on business profiles. Reviews still support local rankings and conversion on the listing; 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. Post them to public social channels or embed them in review widgets on your own site and, in Wertham’s words, “now they’re fair game for the LLM tools to be pulling in.”
That 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.
“If you’re relying on the review platforms to do that for you, it’s not going to be enough,” Wertham said.
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.
Wertham also broke down first-party review capture, the survey responses that never reach Google, and why one customer’s 11,000 of them mattered. That segment lives in the on-demand recording.
Does Your Star Rating Still Matter In AI Search?
It matters less than review recency and velocity. No AI answer in the session’s audit examples cited an average star rating; every one cited review content.
The consumer data points the same direction: 45% of users prioritize 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.
Wertham noted that consumers routinely override Google’s default “most relevant” review sort and switch to “newest,” because the most recent review predicts the experience they will get. A high average built on years-old reviews carries less weight than a current, steady stream.
“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,” Wertham said.
The session organizes the response into three workstreams, build, manage, and defend: building consistent listings and review volume, managing responses and monitoring within a 72-hour response window, and defending the rating you earned against policy-violating reviews and burial tactics like review smothering. Walk through the build, manage, defend rollout.
Why Does AI Give A Different Answer About Your Business Every Time?
Because LLM answers behave like a slot machine, one query is never a reliable read. Jackson cited SparkToro research in which different people asked LLMs the same question across devices and accounts, and the results never returned in the same order.
“Asking AI a question is kind of like a slot machine,” Jackson said. “It’s going to be giving back similar data, but each time it’s going to look a little differently.”
Position is the wrong metric for AI visibility. Total citations, the breadth of sources feeding the answer, predicts whether your brand appears at all. Your brand can miss one device’s answer entirely and lead the next.
Google published its own guide to optimizing for generative AI and updated it this month. Wertham flagged one change with teeth: the AI slop penalty. Google now detects low-value AI-generated content and, in his words, is “essentially penalizing businesses” for it. Generic AI blog posts and glorified FAQ scraping targets now cost you rather than getting ignored.
Action item: Run your audit prompts in incognito or temporary-chat mode so stored context stops shaping your results, and re-run them on a schedule. The session shows the monthly re-run method for measuring whether your visibility work is moving the answer.
Q&A: Most Helpful Questions From The Webinar
Q: What is the fastest thing I can do this week to change what AI says about my company?
“Address your listings. Make sure your listings are all correct and all consistent, whatever platforms you’re on. And then make sure that you are evangelizing your reviews off of the third-party directory where you’re receiving them. Post them to your social media platform, post them to a section of your website.” Jason Wertham, 49:23 in the on-demand recording.
“Make sure you have the basics down. Get the basics down, make sure those are set, and then you can move into the more elaborate things.” Annie Jackson, 50:30 in the on-demand recording. Jackson illustrated the point with a local restaurant whose Facebook page listed the owner’s personal cell number; he never knew why the calls kept coming.
Q: How long before content changes actually show up in AI answers?
Annie answered: small facts move fast, positioning moves slowly. Store hours and phone numbers update quickly, but “what you’ve been known for will take a little bit longer,” generally two weeks to a month with a long tail beyond that. She pointed to your own website as the fastest lever: a new offering has to appear on your own channels first, because reviews will not announce it for you. Full answer at 54:19 in the on-demand recording.
Q: My weakest location has old bad reviews that keep showing up. Do I have to wait for them to age out?
Jason answered: age fades a review’s relevancy naturally, but keyword-heavy reviews and reviews from Local Guides hold ranking longer, and emoji reactions keep a review from slipping even when they add no upward momentum. Policy-violating reviews stay disputable at any age; his review defense team removes reviews more than ten years old regularly. The reliable fix is volume and velocity, since recency outweighs content in long-run relevancy. Full answer at 47:33 in the on-demand recording.
Q: How should franchisors handle this when each franchisee controls their own profile?
Jason answered: franchise reputation management fails at the consistency gap, because each franchisee owns their listing while the brand absorbs the AI answer. Establish best practices, offer white-labeled or partner tools franchisees will use, and put a playbook in their hands. He also suggested running the audit prompts on behalf of franchisees and coaching them on the results, since one location’s wrong AI answer costs the whole brand. Full answer at 55:46 in the on-demand recording.
Watch The Full Webinar
The on-demand session contains the four emergency audit prompts and downloadable handout, the complete build, manage, defend rollout, the monthly measurement method, the review defense walkthrough for disputing policy-violating reviews, and Jackson’s AI narrative audit offer. Watch the full webinar on demand.
