Here is what changed and when: G2's 2026 Buyer Behavior Report found that 78% of software buyers now consult AI before they open G2. That single data point reshapes the purchase funnel entirely. AI is the first filter. G2 is what AI cites to validate the answer it already generated.
This means the question is no longer "how do we rank on G2?" It's "what does AI say about us — and does it cite G2 to back that up?"
How LLMs Use Review Platforms
When a buyer asks ChatGPT "what's the best project management software for a 50-person ops team," the model doesn't return a list of ten blue links. It generates a synthesized answer: two or three brand names, a short rationale for each, and — increasingly — citations pulled from third-party sources.
Those third-party sources are not your website. They are not your press releases. They are review platforms, community forums, and editorial directories — the same sources a buyer would trust if they were doing manual research themselves.
Perplexity citations in software categories routinely trace back to G2, Capterra, and Trustpilot. ChatGPT's software recommendations correlate strongly with review platform footprint: brands with active review platform profiles have 3x higher ChatGPT citation rates than brands without them (Kevin Indig, Growth Memo, 2025).
The trust signal in AI search is third-party validation. It always was — that's why review sites existed in the first place. What changed is the mechanism.
The mechanism is not algorithmic ranking. It is training data and retrieval. LLMs learn from what has been written about a brand across the web — and review platforms are dense, structured, high-trust sources of exactly that kind of content. A brand with 4.7 stars and 200 reviews on G2 has generated hundreds of third-party sentences describing what it does, who it's for, and why buyers chose it. That is the content LLMs synthesize from and cite.
A brand with no G2 profile, or twelve outdated reviews, has none of that. Regardless of how good the product is.
Which Platforms Matter — and Why
Not every review platform carries the same weight in the AI citation ecosystem. Here's how the major ones function:
The highest-signal platform for B2B software. It has category structure, verified reviews, and a review corpus that maps neatly to buyer intent queries. LLMs treat G2 as an authoritative source for software comparisons — it is the platform most frequently cited by Perplexity in head-to-head software queries.
Operates similarly to G2 and has significant reach with SMB buyers. Perplexity cites it frequently in software recommendation prompts. Having a presence on both G2 and Capterra increases your citation surface without duplication — the two platforms serve different audience segments.
Carries weight for general software credibility, particularly in consumer-adjacent SaaS. Its review schema is structured enough that AI systems can extract ratings, sentiment, and positioning signals directly. A high Trustpilot score read by an LLM functions as a credibility shortcut.
Different in kind from the others. Not a directory — a community. LLMs heavily index Reddit threads because they contain real buyer conversations, unedited comparisons, and use-case-specific language. Brands with a Reddit presence see 4x higher LLM citation rates on average. You can't manufacture this, but you can participate in the communities where buyers discuss your category.
Matters most for newer brands. It functions as a credentialing signal — "this product was launched, noticed, and upvoted by a peer audience." LLMs interpret that as validation of existence and relevance, particularly for products without long review histories elsewhere.
Running a Citation Audit
Before you optimize anything, establish your baseline. The process takes twenty minutes and most teams have never done it.
Fire the buyer's prompt. Open Perplexity. Type the prompt a buyer in your category would actually ask: "what are the best tools for [your use case] in 2026." Read the answer. Note which brands are named.
Trace the citations. Which review platforms appear in the source list? What do those citations say about the brands being recommended? What language is the platform using to characterize them?
Run the same prompt in ChatGPT. Compare. The overlap between ChatGPT and Perplexity citations in any given software category is only about 11% — the two systems pull from different source pools. What appears in one does not automatically appear in the other.
Search your own brand. Ask "what is [your brand] and who is it for?" Look at what the AI says. Is the description accurate? Does it reflect your current positioning, or something you communicated two years ago? Are sources cited? Which ones?
This four-step audit gives you a clear picture of where you stand: which platforms the AI is drawing from for your category, whether your brand appears at all, and whether the characterization is accurate.
What You Can Actually Do
Claim and complete every profile. G2, Capterra, Trustpilot, Product Hunt. Fill in every field. Category tags, use case descriptions, and competitive differentiators matter — these are the words LLMs learn from and reproduce when describing your brand to a buyer.
Get review volume up. Volume is a trust signal in its own right. A brand with 200 reviews signals staying power and adoption. The reviews themselves contain language about your product that AI systems index and cite. Build a systematic review-ask process into your customer journey — post-onboarding, at renewal, after a support resolution.
Maintain narrative consistency across platforms. LLMs synthesize across sources. If your G2 profile describes you as "workflow automation for ops teams" and your Capterra profile describes you as "no-code process builder," the AI gets a blurred picture. Align your positioning language across every profile so the synthesized characterization is coherent.
Flag inaccurate AI summaries. If ChatGPT or Perplexity describes your product incorrectly, that inaccuracy will persist until the underlying source data changes. Identify which sources the model is drawing from — often an outdated review or a stale directory listing — and update them. The AI will eventually reflect the corrected source.
Knowing What's Working
The challenge with review platform strategy is that the feedback loop isn't visible through conventional analytics. You update a G2 profile, generate twenty new reviews, and have no way to know whether it moved your AI citation rate — or which platform drove the change.
Shensuo's Source Influence feature maps exactly this: which external sources are driving your brand's AI citation rate across ChatGPT, Perplexity, and Gemini. You can see which review platforms are actively contributing to your citations and which ones aren't appearing in answers at all. That's the difference between optimizing with visibility and optimizing blind.
Buyers used to consult G2 directly after they'd narrowed their shortlist. Now they ask AI, and AI consults G2 on their behalf. The brands that built strong review profiles for the old search behavior are the ones getting cited in the new one.
Sources: Kevin Indig, Growth Memo, March 2025 · G2 2026 Buyer Behavior Report · Digital Bloom 2026 AI Citation Report