The dealers ahead of this aren’t rebuilding from scratch. They’re making three targeted adjustments: where reviews go, how they’re requested, and how they’re responded to. Each one is small. Together, they change what the machine sees.
1. Split Where Your Reviews Go
Alexi Venneri, CEO of DAS Technology, made the point plainly on Daily Dealer Live: consumer reviews are now the number one driver for getting found via Generative Engine Optimization — across ChatGPT, Perplexity, Grok, and the rest. But each tool scrapes different corners of the internet, which means a reputation that only exists on Google is a reputation that much of the AI ecosystem doesn’t read.
The framework we’ve landed on: route 70% of review asks to Google to protect local SEO, and send the remaining 30% to third-party platforms like DealerRater, Cars.com, or Yelp. It’s not about abandoning Google. It’s about showing up wherever a buyer happens to be asking.
2. Stop Asking for Stars. Ask for Specifics.
AI models largely ignore “five stars, great experience.” They synthesize specific language to answer user queries. When customers mention the vehicle they bought, the service performed, or a staff member by name, that language becomes part of the record AI pulls from when building its answers.
It comes down to changing the ask. “Thanks for coming in for your engine diagnostic — if [Technician Name] kept you well-informed, we’d love to hear about it” outperforms “would you mind leaving us a review?” every time. Generic prompts produce generic reviews, and generic reviews are mostly noise to a language model.
3. Write Responses Like They’re Being Read by an Algorithm, Because They Are
Large language models don’t just read reviews. They read responses. How a dealership replies, especially to negative feedback, is part of the narrative AI uses to assess credibility.
A response that addresses the specific issue, references the service by name, and shows how it was resolved is doing double duty: managing the customer relationship and feeding the model structured, credibility-building data. Generic copy-paste replies leave that signal on the table. You’re not just replying to one customer anymore. You’re updating your public record.
Review strategy used to be reputation management. Now it’s infrastructure for discoverability and perception on evolving AI chat tools. The dealers who treat it that way are the ones the algorithm surfaces. The ones who don’t are optimizing for a search engine that no longer owns the top of the funnel.
