How G2 and Review Sites Shape AI Recommendations

Last updated: November 2026

Review sites shape AI recommendations because ChatGPT, Perplexity and Google AI Overviews cite them when buyers compare options. A complete profile with a steady flow of honest reviews gives AI engines third-party evidence about you. Reviews help, but the data shows they are one factor among many, and solicitation must follow FTC and platform rules.

Key takeaways🔗

• G2 was among ChatGPT's ten most cited sources in Profound's study of 680 million citations, at 1.1% of all ChatGPT citations. Yelp, TripAdvisor and G2 all appeared in Perplexity's top ten.

• A G2-commissioned study by Kevin Indig found categories with 10% more reviews had about 2% more AI citations. Reviews explained less than 2% of the variance.

• A Trustpilot and Seer Interactive study found brands with no Trustpilot profile had a median AI citation rate of 1%, versus 75% for brands with a strong profile.

• The FTC's 2024 reviews rule bans fake reviews, sentiment-conditioned incentives and undisclosed insider reviews, and allows civil penalties.

• Platforms differ: G2 and Capterra allow disclosed, neutral incentives. Trustpilot bans incentives and selective invitations outright.

Why do AI answers cite review sites?🔗

AI answers cite review sites because they hold the kind of third-party evidence a model needs to compare products: ratings, pros and cons in buyers' own words, feature comparisons and pricing notes, all organized by category. When a buyer asks "what is the best project management tool for a 10-person agency," a G2 or Capterra category page is a ready-made comparison from people who used the products.

The citation data backs this up:

Two warnings before you act on these numbers. First, two of the three studies were paid for or published by review platforms (G2 and Trustpilot), which have an obvious interest in the result. Second, all three show correlation, not cause. Brands with lots of reviews also tend to be bigger, better known and more written about. Kevin Indig's write-up says this directly: brand authority, content quality, training data, organic visibility and mentions across the web explain most of the difference.

The fair reading: review sites are a real part of the source pool AI engines draw from, especially for software, local businesses and travel. Being absent is a gap. Having more reviews than a competitor is a modest edge, not a switch.

Which review sites matter for your business?🔗

The review sites that matter are the ones AI engines cite for your buyer prompts, and that depends heavily on your category.

Do not guess. Run 10 to 20 buyer prompts in ChatGPT, Perplexity, Claude and Google AI Overviews and note which review domains get cited. Our guide to what sources ChatGPT cites explains the usual mix, and the most cited domains in ChatGPT post shows the bigger picture. Local businesses should also read our guide to AI visibility for local businesses.

What are the rules on asking for reviews?🔗

You can ask customers for reviews, but you cannot fake them, buy positive ones, hide insider connections, or ask only the customers you expect to be happy. Both US law and the platforms' own policies set the rules.

The FTC Consumer Reviews and Testimonials Rule. The FTC announced this rule on August 14, 2024, and the FTC's Q&A says it took effect October 21, 2024. It prohibits:

• Fake or false reviews and testimonials, including reviews by people who do not exist (such as AI-generated ones) or who never used the product

• Buying positive or negative reviews, meaning incentives conditioned on a particular sentiment

• Insider reviews by officers or managers that do not clearly disclose the connection

• Company-controlled "independent" review websites

• Review suppression through groundless legal threats, intimidation or false accusations

• Buying or selling fake social media indicators, such as bot followers

The FTC can seek civil penalties against knowing violators.

The Endorsement Guides. The FTC's Endorsement Guides Q&A adds a point that catches many businesses: "Only asking for reviews from customers who you think are more likely to be happy with your product would be misleading if it substantially skews the favorability of the reviews." So "review gating," where you survey customers first and only send happy ones to G2 or Google, is a real risk.

Platform policies. Each site adds its own rules, and they do not all agree:

If you use more than one platform, the simplest safe policy is the strictest one: invite every customer in the same way, never tie anything to a positive rating, and use each platform's own incentive tools where incentives are allowed. None of this is legal advice, so check with counsel if you run large review programs.

How do you build review site presence the right way?🔗

Build review site presence by claiming your profiles, filling them in completely, asking every customer at the same point in their journey, and replying to reviews in public. Here are the steps:

1. Claim your profiles. Find out which sites already list you. Software companies often have a G2 or Capterra listing created by a reviewer. Claim each one so you can edit it and reply.

2. Fill in every field. Use your canonical company description, current USD pricing, plan names, integrations, screenshots and the customer types you serve. G2's own study recommends a profile description of 250 or more characters and detailed pricing. Vague or outdated profiles give AI engines vague or outdated facts.

3. Pick a fair trigger. Ask for a review at the same point for everyone, such as 30 days after onboarding or after a support ticket closes, regardless of whether you think the experience was good.

4. Make it easy. Send a direct link to your profile's review form. One email and one reminder is enough.

5. Use platform incentive tools where allowed. On G2 and Capterra, use their own campaign links so incentives are disclosed properly. On Trustpilot, do not offer incentives at all.

6. Reply to reviews, especially the negative ones. A calm, specific reply that fixes the problem shows buyers, and the systems reading the page, how you handle issues. Trustpilot notes that not liking a star rating is not a valid reason to flag a review.

7. Link to your profiles. Add review profiles to your site footer, your Organization schema sameAs list and your sales emails. Our post on schema markup for AI citations covers sameAs.

8. Keep it steady. A slow, consistent flow of reviews looks more natural and keeps your profile current. A burst of 40 reviews in one week followed by silence does neither.

How do negative reviews affect AI answers?🔗

Negative reviews can show up in AI answers, because engines summarize what they read, including complaints. Seer Interactive's study notes that AI platforms amplify whatever narratives they find in reviews, and that even a single negative review can shape the sentiment of an answer.

You cannot remove honest negative reviews, and trying to suppress them is now explicitly covered by the FTC rule. What you can do:

• Fix the underlying problem if the complaint is fair.

• Reply publicly with what changed.

• Ask newer customers for reviews through your normal, fair process, so the profile reflects the current product.

• Flag reviews only when they actually break platform rules (fake, abusive, off-topic or containing personal data).

When an AI answer repeats an old complaint, check which pages it cites. Often the fix is updating a stale profile or a comparison page, not fighting the review.

How do you know if it is working?🔗

Measure whether AI engines start naming you, and citing your review profiles, for the buyer prompts you care about. Review counts and star ratings are inputs. Being named in answers is the result.

TrendlyAI is a young product with few public reviews, so I am in the same position as many readers here: building a review presence from a small base, honestly and slowly. What I watch is the same thing I would tell any client to watch: run the same buyer prompts on a schedule and see whether the brand gets named and which sources get cited. TrendlyAI does this weekly on ChatGPT, Perplexity, Claude and Google AI Overviews, and our guide to tracking brand mentions explains the manual method.

For a quick baseline, the free AI visibility check runs 5 prompts on ChatGPT and Perplexity in about 30 seconds with no signup. For the full strategy, start at the GEO hub.

Frequently asked questions🔗

Does ChatGPT use G2 reviews?🔗

ChatGPT cites G2 when it searches the web for software comparisons. In Profound's analysis of 680 million citations, G2 accounted for 1.1% of ChatGPT's citations, which placed it among ChatGPT's ten most cited sources alongside Wikipedia, Reddit and Forbes.

Do more reviews mean more AI citations?🔗

Slightly. A study by Kevin Indig for G2 found that software categories with 10% more reviews had about 2% more AI citations. Review volume explained less than 2% of the variation, so brand authority, content and mentions elsewhere matter far more.

Can I offer a gift card for a review?🔗

It depends on the platform. The FTC allows incentives as long as they are not conditioned on a positive or negative review. G2 and Capterra allow disclosed, nominal incentives through their own programs. Trustpilot does not allow incentives of any kind.

Is review gating illegal?🔗

The FTC says asking only customers you expect to be happy can be misleading if it substantially skews the favorability of your reviews. G2, Capterra and Trustpilot all ban selective solicitation in their own policies. The safe approach is to invite every customer the same way.

Which review site matters most for AI visibility?🔗

It depends on your category. G2 and Capterra matter most for B2B software, Yelp and Google for local businesses, TripAdvisor for travel, and Trustpilot for many consumer brands. Check which review domains AI engines cite for your own buyer prompts before choosing.

Related reading🔗

• How to get mentioned in ChatGPT

• Reddit citations in AI answers

• AI search visibility for B2B SaaS