I run Yellow Pencil. For years I told clients the same thing every other agency told them: get more reviews, keep the rating above 4.5, reply to every one. We practiced what we preached. By late 2023 we had 4.9 stars on Google and 87 reviews from real clients in Victoria, BC. Real names, real projects, real photos.
Then I started asking ChatGPT "who are the best web designers in Victoria BC" and we were nowhere. Not in the top five. Not in the top ten. Not mentioned at all. I kept asking variations for eighteen months. Yellow Pencil did not come up once unless I typed the name directly into the prompt.
Meanwhile a two-person shop down the street with 31 reviews and a 4.6 rating was getting cited. I went and looked at their site expecting some slick AI SEO play. Nothing obvious. No special design. Just a couple of things that turned out to matter a lot more than I understood at the time.
The signal Google reviews send is not the signal AI is reading
Google reviews are a ranking signal inside Google's own local pack. They influence the map. They influence whether someone clicks your listing after a search. That is a closed system. Google owns the reviews, Google owns the ranking, Google shows the result.
ChatGPT, Perplexity, Gemini, and Claude do not have a direct pipe into Google's review database the way Google Search does. They are trained and grounded on text that exists on the open web. When one of those engines decides to recommend a business, it is pattern-matching against language it has already seen somewhere that it can cite or remember.
A number out of five and a pile of glowing testimonials sitting inside the Google Business Profile do not generate that language on the open web. They sit inside Google. An AI model that has never indexed that specific Google page gets nothing from it. Our 87 reviews were invisible to the models because the reviews lived somewhere the models were not looking.
What AI engines actually look at
After I got tired of being invisible I spent a few months testing what moved the needle. Three things kept showing up.
First, structured data on your own site. Schema markup for LocalBusiness, Service, and FAQ is the cleanest way to hand an AI model a machine-readable description of what you do, where you do it, and who you serve. When I added proper Service schema with explicit areaServed and offers, our citations in Perplexity started appearing within about three weeks. Not because Perplexity ran a crawl that week, but because the schema gave every future crawl a clean signal to work with.
Second, third-party citations. Reddit is the big one. Industry forums, niche news sites, and local business roundups matter too. When a real person on r/VictoriaBC answered a question about web designers and named us, that single comment did more for our AI visibility than 40 Google reviews. The model had seen our name in a context it could cite, tied to a specific geography and a specific service.
Third, entity clarity across platforms. Same business name, same address, same phone, same service description on every directory and profile we appear on. Not "Yellow Pencil Inc" on one and "Yellow Pencil Design" on another. AI models resolve entities by matching strings across sources. If your name is spelled three different ways across the web, the model often treats you as three weaker entities instead of one strong one.
The Yellow Pencil case, in numbers
Here is what our situation looked like before and after.
Before: 4.9 stars. 87 Google reviews. Zero ChatGPT mentions in eighteen months of testing. Zero Perplexity citations. Our website had no LocalBusiness schema, no Service schema, and no FAQ schema. We had five Reddit mentions total across all of Reddit, three of them from 2019.
What I changed: added full LocalBusiness, Service, and FAQ schema to the relevant pages. Cleaned up name consistency across 23 directory listings. Answered about 15 questions on Reddit where a web design recommendation was genuinely useful, without spamming. Got three local publications to update old articles with a current description of what we do.
After, roughly four months later: ChatGPT cites us for "web designers in Victoria BC" queries in about 40 percent of test runs. Perplexity cites us more often than that. Google reviews, meanwhile, went from 87 to 91. The review count was essentially flat and it did not matter.
Reviews did not unlock AI visibility. Schema plus Reddit did. The review count went up by four in the same window the citations went from zero to regular.
What reviews actually do help with
I want to be clear about what I am not saying. I am not saying stop collecting reviews. Reviews still matter. Just not at the step of the funnel people assume.
Reviews are a credibility signal once an AI has already found you. When ChatGPT pulls up three web design firms in response to a prompt, and a user clicks through to learn more, your review profile is one of the first things that user lands on. A 4.9 with 87 reviews closes deals. A 3.7 with 12 reviews does not. Reviews win the human decision after the machine has already shortlisted you.
So the stack looks like this. Schema plus citations plus entity clarity get you into the shortlist. Reviews convert the traffic the shortlist sends you. Treat them as two different jobs, not one.
The mindset shift
The habit most business owners have is to measure SEO work by counting reviews, star ratings, and Google Business Profile impressions. That habit is fine for traditional search. It is a weak proxy for AI visibility.
If I could go back and redo the eighteen months I wasted, I would have spent ten percent of my review-collection energy on schema, Reddit, and name consistency. I would still have 87 reviews. I would also have been getting cited the whole time.
The review work is not wrong. It is just incomplete. Assume AI engines are reading a different book than the one Google is reading, and you will stop being surprised when a strong Google profile buys you zero ChatGPT mentions.
Where to start
If you want to see where you currently stand before changing anything, run your business through the AI visibility checker at /free-tools/ai-visibility/. It shows you what the models are actually saying about you right now, which is usually more sobering than people expect.
If your reviews are the strong part of your profile and you want to understand whether the rating itself is actually helping conversion, the review calculator at /free-tools/review-calculator/ breaks down what your current star count and volume are worth in practical terms.
Either way, do not assume a strong Google profile is doing the AI work for you. It is not, and the eighteen months I spent assuming otherwise are the only reason I am writing this.
hello@rankinglocal.ai is read by me directly.