Reddit Was 0.5% of AI Citations on B2B SaaS and Fintech Buying Questions

When AI engines were asked to compare or choose SaaS and fintech products, Reddit pages made up 0.5% of the sources they cited. These are the questions that sit closest to a purchase. On these questions, pages built to compare products drew 22% of citations.

The short version

• Reddit was a small source: It drew 178 of 35,514 citations on buying questions (0.50%), and none at all on 43 of the 76 questions.
• Comparison pages were a large one: Pages with "best-", "-vs-", or "-alternative" in the address drew 7,911 citations (22.3%), 44 times Reddit's share.
• Most of those pages were vendors' own: In a hand-coded sample, 58 of 75 sat on vendors' blogs, not on review websites or publishers.

What to do with this

1. Treat Reddit as a small channel for B2B SaaS and fintech buying questions. It stayed under 1% on the other tracked questions too. Consumer products, which this data does not cover, may differ.
2. List the comparison pages AI answers cite for each buying question. Most will be other vendors' roundups, so check that the product appears on them with correct facts. Where an independent publisher wrote the list, ask to be included.
3. When the cited lists leave the product out, publish a comparison page with checkable facts. A vendor's own "Best X" or "X vs Y" page competes for the same citations.

Comparison pages drew 22.3% of citations, Reddit 0.50%

Across 76 questions shaped like "best [category] software for [industry]" or "[market leader] alternatives", answers gave 35,514 citations. Pages with "best-" in the address drew 19.4% by themselves.

Answers to all 76 questions cited more comparison pages than Reddit pages. The gap also held within each company's buying questions.

Our read: We think buying answers lean on pages that compare products, because those pages hold the product names, features, and prices the question asks for. A Reddit thread rarely does, so it gets cited less. Matching by address misses roundups without these words, so 22.3% is a floor for comparison content.

On questions without list words, comparison pages still drew 15.0%

Just over half the questions used words such as "best", "vs", or "alternatives", which pull in pages with the same words. On those, comparison pages drew 26.4% and Reddit 0.63%. On the rest, comparison pages still drew 15.0%, and Reddit 0.28%.

Reddit was not larger on other kinds of question either. In the same 7 companies, it drew 0.35% of citations on their other tracked questions (56 of 16,229). Across all 111,101 citations behind our earlier analysis of how AI agents shortlist software, it drew 0.63%.

Our read: We think question wording changed how many comparison pages were cited, not whether they led. Even plain questions about a need drew 54 comparison-page citations for every Reddit one. The question types come from the tracking tool, so a few labels may be off.

Methodology

Question. When AI engines are asked to compare or choose B2B SaaS and fintech products, which sources do the answers cite, and how much of that is Reddit?

Data. Every citation Atomic AGI recorded for 13 B2B companies' tracked prompts, July 13 to October 11, 2026. That is 111,101 citations from 8 AI engines (ChatGPT, Claude, Perplexity, Gemini, Copilot, Grok, Google AI Mode, and Google AI Overviews).

Sample. Buying questions are the 76 prompts, from 7 of the 13 companies, that the tracking tool labels consideration or decision, that do not name the tracked company, and that had answers in the window. The 7 sell B2B SaaS or fintech products, from payments and compliance software to AI tools. A legal-services company's questions are left out.

Coding. Reddit means any reddit.com page (174 of 178 were threads). Comparison pages are those whose address contains "best-", "-vs-", or "-alternative", counted once even when an address matches two patterns; 40 "best-practice" citations are left out. G2 and other review websites are matched by domain. Who wrote the comparison pages comes from a random sample of 408 coded citations, 75 of them comparison pages; without Perplexity, 39 of 49 sat on vendors' blogs.

Analysis. 95% intervals resample the 76 prompts: 19.2% to 25.2% for comparison pages and 0.34% to 0.69% for Reddit. Prompts are grouped within 7 companies; resampling companies instead widens the intervals to 12.5% to 27.5% and 0.13% to 0.68%. The gap holds either way.

Limitations. Tracked prompts in a few B2B niches, chosen by each company, not a random sample of real searches. A citation shows a source was listed, not that it shaped the answer. Address matching undercounts comparison content. One window, so no trend. Atomic AGI, which collected the data, is Omnius's product.

Reproducibility. The chart data tables give every count behind the shares. Prompt lists stay internal, because they could identify a company.

Correction. The agentic-seo article counted 111,337 citations on October 11, 2026; a later recount by the tracking tool removed 236 in one company's prompts. Reddit's 698 citations did not change.

Sources

Omnius articles this note builds on

• Agentic SEO: How AI Agents Shortlist B2B SaaS Products, October 13, 2026