I’m building our review acquisition strategy and want to factor in AI visibility.
What I know:
What I don’t know:
We have 200 G2 reviews (4.5 stars) but I rarely see them referenced in AI responses about our category. Competitors with fewer reviews sometimes get mentioned instead.
What am I missing? How do you optimize reviews for AI visibility?
Reviews absolutely matter for AI, but it’s more nuanced than just star ratings.
How AI uses reviews:
Aggregate Ratings “[Product] has a 4.5/5 rating on G2 with 200+ reviews”
Synthesized Feedback “Users praise [Product] for ease of use but note the learning curve for advanced features”
Use Case Matching “According to reviews, [Product] is best for mid-size teams”
Comparison Context “Reviewers often compare [Product] to [Competitor], preferring [Product] for X”
Which platforms AI pulls from:
B2B Software:
B2C/General:
What matters for AI citation:
Not just quantity. AI looks for:
Encouraging detailed reviews:
1. Ask Specific Questions Instead of “Please leave a review,” ask:
2. Timing Matters Ask after:
3. Provide Structure Send a template: “Consider including: What you were looking for, why you chose us, what results you’ve seen, who would benefit from this product”
4. Highlight Detailed Examples Share examples of helpful reviews with your ask. “Reviews like this one help others make decisions…”
5. Incentivize Completion, Not Stars Gift cards for completing a review (any rating, detailed). Never incentivize positive ratings - that’s unethical and platforms detect it.
Detailed reviews > many brief reviews for both AI visibility and conversion.
G2-specific insights:
What G2 data AI systems access:
What helps you surface in AI:
Category Leadership Being a “Leader” or “High Performer” in G2 grids gets mentioned. Aim for grid placement, not just reviews.
Feature-Specific Reviews Reviews that rate specific features help AI match you to specific queries. “Best for automation” requires reviews mentioning automation.
Segment Coverage G2 breaks reviews by company size. AI might recommend you for “enterprise” if your enterprise reviews are strong, even if overall reviews are mixed.
Comparison Reviews Reviews comparing you to competitors directly are gold. AI uses these when people ask “X vs Y?”
Strategy:
Don’t just ask for reviews. Ask customers who represent different segments and use different features. Coverage matters.
Don’t sleep on Reddit for AI visibility.
Why Reddit matters:
What works:
What doesn’t work:
Strategy:
Have your happy customers participate in Reddit discussions about your category. When someone asks “What tool do you use for X?”, real users sharing their genuine positive experience is powerful.
We’ve seen Reddit mentions correlate strongly with AI recommendations. AI trusts community-validated experiences.
Data on review characteristics and AI citations:
Analysis of 100 products across review platforms:
| Review Characteristic | AI Citation Impact |
|---|---|
| 100+ reviews | +35% citation likelihood |
| 200+ reviews | +42% (diminishing returns after) |
| Average review length 150+ words | +38% |
| Reviews mention specific features | +45% |
| Reviews compare to alternatives | +52% |
| Reviews within last 6 months | +41% |
| G2 Grid Leader badge | +58% |
Key insights:
Recommendation:
Instead of “get more reviews,” focus on “get the right reviews”:
B2C perspective:
Google Reviews impact AI:
For local businesses, Google reviews are crucial. When someone asks AI “best pizza in [city],” AI often synthesizes Google review data.
What we’ve seen work:
Volume threshold Need 50+ reviews to start appearing consistently in AI local recommendations.
Keyword presence Reviews mentioning specific attributes (“gluten-free options,” “outdoor seating”) help match specific queries.
Response quality Your responses to reviews show engagement. AI may consider this context.
Photo reviews Google reviews with photos rank higher in Google’s own system. May carry over to AI.
Trustpilot for E-commerce:
For online retail, Trustpilot is heavily cited. AI often references Trustpilot scores when discussing e-commerce brands.
Platform varies by industry. Know which review sites matter for YOUR category.
Review schema on your own site matters too.
Aggregate Review Schema:
If you display reviews on your site, implement AggregateRating schema:
{
"@type": "Product",
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": "4.5",
"reviewCount": "200",
"bestRating": "5"
}
}
Why it helps:
Embedding Third-Party Reviews:
Display G2 badges, Capterra ratings on your site with proper markup. This creates another touchpoint where AI can see your review data.
Own Your Review Narrative:
Create a “Reviews” or “Testimonials” page that:
This gives AI another source confirming your review credibility.
This thread shifted my strategy. Key takeaways:
What matters for AI:
Updated Review Strategy:
1. Quality over quantity requests
2. Platform diversification
3. Review content guidance
4. Own-site optimization
Key insight:
AI doesn’t just count stars. It synthesizes what reviewers say. Reviews that describe specific experiences, features, and comparisons are most valuable for AI visibility.
Thanks everyone for the platform-specific insights!
Get personalized help from our team. We'll respond within 24 hours.
Monitor when AI systems reference your product reviews and ratings in their recommendations.
Community discussion on how customer reviews impact AI recommendations. Marketers and business owners share data on review quantity, quality, and platform influ...
Community discussion on fixing low AI visibility scores. Real experiences from marketers on diagnosing and improving AI search presence quickly.
Community discussion on improving AI visibility scores. Marketing professionals share quick wins, systematic approaches, and real results from optimization effo...