What B2B buyers see in LLM answers, and why it is mostly Reddit and G2.

Between April and September 2025 we ran the same 240 B2B buying-stage queries across ChatGPT (GPT-4o browse), Perplexity Pro, Claude (Sonnet 3.7 with web search), and Google's Gemini app, twice a month. Every citation was logged and tagged by source type. 8,600 citations in total across the 12 runs. The distribution is shifting monthly, but the shape is stable enough to describe.

1. Reddit is the most-cited source in Perplexity by a wide margin.

On buying-stage queries ("best X for Y", "alternatives to Z", "is W worth it"), Reddit appeared in 56% of Perplexity answers. Second place was G2 at 32%. The citation is almost always a specific thread, usually with a high upvote-to-comment ratio and recent activity (last 90 days). This is not a prompt-engineering artefact. It is what the model grounds on.

Perplexity's own behaviour is worth understanding separately: its Pro Search chains two or three retrieval passes, and the first pass is disproportionately weighted toward Reddit, Stack Overflow, and GitHub. The second pass broadens but rarely dislodges what the first pass anchored on.

2. G2 and TrustRadius dominate comparison queries in ChatGPT.

"X vs Y" and "top N Z" queries in ChatGPT cited G2 in 44% of responses and TrustRadius in 21%. Vendor-own comparison pages ("Product A vs Product B" on a vendor's own site) showed up in 16% of responses, almost always as a second or third citation, rarely primary. If you are a B2B vendor writing comparison content as an SEO play, understand it will rarely outrank G2 inside an LLM answer.

ChatGPT's browse tool prefers G2 specifically over other review aggregators at a ratio we have not been able to fully explain. Capterra, TrustRadius, and Gartner Peer Insights appear, but G2 outweighs them roughly 2:1 across our sample.

3. Official product docs outperform marketing pages.

On technical or "how does X integrate with Y" queries, product documentation was the cited source in 59% of answers across all four models. Marketing landing pages appeared in 4%. Documentation is more structured and more answer-shaped than marketing copy. It is also, historically, under-invested in as a visibility channel.

This is the single highest-leverage content move for a B2B vendor in 2025. Good docs are no longer just support deflection and developer enablement. They are the primary content surface your buyer might read through an LLM before ever touching your marketing site.

4. The four LLMs cite different sources for the same query.

For the same query, cited sources overlapped between Claude and ChatGPT only 37% of the time. Between ChatGPT and Perplexity, 49%. Between Gemini and everyone else, 31%. This means "LLM SEO" is not one problem:

• Perplexity optimises toward Reddit, Stack Overflow, GitHub, recent news. Heavy on community and news.

• ChatGPT browse optimises toward G2, Wikipedia, YouTube transcripts, and large editorial sites. Heavy on established sources.

• Claude with web search skews toward primary research, official documentation, and academic or institutional sources. Under-cites Reddit compared to the others.

• Gemini app leans heavily on Google search results, with the same biases as classic Google SERPs, modulated by recency.

5. YouTube transcripts are the sleeper channel.

Across all four models, video transcripts were cited in 12% of technical answers. We underestimated this in our April run and the signal strengthened through the summer. Long-form vendor YouTube content (product walkthroughs, webinars with timestamps, founder conversations) is increasingly serving as an LLM-friendly source. The pattern is clearer on ChatGPT than on Perplexity.

6. Brand mentions inside third-party content matter more than owned content.

A third-party Reddit thread that names your product as a recommendation is worth roughly 4x a product page mentioning the same feature, in terms of citation frequency across the four models. The network of mentions (not the authority of any one domain) is what the LLMs are picking up.

What this means for B2B content strategy

• Get on G2 and TrustRadius. Keep the listing current. Encourage honest reviews. Most vendors still underinvest here relative to the visibility payoff.

• Treat Reddit as a content surface, not a social channel. This is not astroturfing (it is obvious and the moderators are effective). It is having a real presence in the subreddits that serve your category, with people who answer questions in public under their own names. Founder presence matters more than brand presence.

• Fund documentation. Every technical question answered cleanly in your docs is an answer your future LLM-mediated buyer might see without visiting your site first. Treat docs with the same editorial care as marketing content.

• Invest in video. Long-form, searchable transcripts. Not 30-second social cuts.

• Stop writing marketing comparison pages unless they rank on Google. In 2025 they rarely earn the LLM citation, and the SEO return is shrinking under AIO.

• Measure per LLM. The four models are different distribution channels. Do not report "LLM share of voice" as a single number.

Methodology: 240 queries across 12 B2B category archetypes (horizontal SaaS, vertical SaaS, developer tools, martech, sales tech, HR tech, fintech infra, data infra, security, AI platforms, e-commerce infra, ops). Run twice a month from April to September 2025. 8,600 citations logged. Categorisation was manual, with two analysts cross-reviewing. This is a working snapshot; the distribution is shifting monthly. Not a benchmark.