Your next buyer asks ChatGPT for the best tool in your category. The shortlist is set before you know the deal exists.
By G2's April 2026 numbers, 51% of B2B software buyers start their research in an AI chatbot — and 70–80% of the evaluation happens before anyone contacts a vendor. Hoss measures whether the engines name you in that unseen evaluation, fixes the reasons they don't, and re-measures every month.
AI visibility for a SaaS company is whether ChatGPT, Gemini, Perplexity, and Claude name your product when buyers ask for tools, comparisons, and alternatives in your category. It's driven by review-site presence (G2 above all), Reddit and community citations, comparison and alternatives content, readable docs, and entity clarity. It can be measured, and the gaps can be fixed.
Is AI chat really where vendor research starts now?
Yes, and the shift was fast. G2's April 2026 research found 51% of B2B software buyers start research in an AI chatbot — up from 29% in 2025 — with 70–80% of the evaluation completed before the buyer ever contacts a vendor [1].
That second number is the one that should worry you. The evaluation isn't happening on your website, in your demo, or with your sales team — it's happening in a chat window you can't see, against a shortlist you may not be on. If the engines don't name you there, you're not losing deals late. You're never entering them.
A buyer asks AI
"Best [category] for a small team." "Alternatives to [the leader]." "X vs Y — which should we pick?"
AI names a shortlist
Composed from review sites, Reddit threads, comparison pages, and docs the engines can read and corroborate.
Absence is invisible
Most of the evaluation runs on that shortlist before any vendor is contacted. Nobody emails you to say you weren't considered.
What drives which SaaS products AI recommends?
Buyers themselves say what they trust: in G2's 2026 AI Search Insight Report, 45% said a review-site citation is the most confidence-inspiring signal in an AI answer [2]. The rest of the picture is community citations and the content on your own domain.
Reviews and community
The corroboration engines cross-reference before recommending.
- G2 and review presence — review volume and recency correlate with AI visibility, per G2's own analysis [2]. A thin, stale profile reads as a thin, stale product.
- Reddit — a 2026 study found r/SaaS, r/marketing, r/entrepreneur, r/smallbusiness, and r/startups account for roughly 35% of B2B SaaS Reddit citations [3] — and Reddit overall is the single largest LLM citation source at 40.1%, per a Semrush study of 150,000+ citations [4].
Comparison content, docs, entity clarity
What the engines read on your own domain.
- Comparison and alternatives pages — "X vs Y" and "alternatives to X" content is exactly what buyer prompts retrieve; B2B SaaS AI-search guidance treats it as core inventory [5].
- Direct answers up front — a quick answer block in the first 200 words and a clear entity statement ("[Product] is a [category] for [audience]"), so a retrieval system can lift the answer cleanly [5].
- Readable docs and crawler access — documentation the engines can actually fetch and parse, with no robots.txt or firewall rules silently locking AI crawlers out.
Which questions do buyers actually ask?
Category discovery, head-to-head comparison, and displacement. Each one ends in a shortlist.
One caution before you test these yourself: don't assume one engine speaks for the rest. A study of 127,198 citations across five engines found only 2.7% of sources were cited by all five [6] — you can be ChatGPT's default pick and invisible in Perplexity. The free version of this check takes about fifteen minutes: here's the complete method.
Measure. Fix. Prove it monthly.
The same loop we run for every client, instantiated for your category and competitors. No black box: the full methodology is published, and you can see a sample report before you spend anything.
The teardown
We build a prompt suite from real buyer questions — discovery, comparison, displacement — and run it across the engines, multiple times per prompt. You get where you're named, which competitors win instead, which review sites and threads the engines cite, and what AI gets factually wrong about your product.
The engagement
A scoped fix list from your teardown: entity and schema work, comparison and alternatives pages built around what the misses trace back to, extractable answers in your key pages and docs, and the crawler and rendering repairs that let engines read all of it.
The scoreboard
Every month, the same prompt suite re-runs and you see mention rate, recommendation rate, and citation share — against your named competitors. You see exactly what moved, and what didn't.
No one can guarantee your product a spot in AI answers. Anyone who promises otherwise is selling something else.
What an honest agency can do is measure where you stand against real buyer questions, systematically raise the probability you're retrieved, understood, and recommended — and publish the scoreboard every month.
What SaaS founders ask before they book.
Do buyers really start vendor research in AI chat?
Yes — G2's April 2026 research found 51% of B2B software buyers start in an AI chatbot, up from 29% in 2025, with 70–80% of the evaluation done before vendor contact [1]. The shortlist is formed where you can't see it.
What drives which products AI recommends?
Review presence first — 45% of buyers say a review-site citation is the most confidence-inspiring signal in an AI answer, and G2 review volume and recency correlate with visibility [2]. Then Reddit and community citations, comparison and alternatives content, readable docs, and a clear entity statement.
Can you guarantee we'll be recommended?
No — no one can guarantee AI citations, and anyone who promises otherwise is selling something else. We measure, fix the causes we find, and re-measure monthly so you can see exactly what moved.
Can I check where we stand without hiring anyone?
Yes. Run your buyers' real questions through the engines in fresh chats, two or three times each, and record who gets named and which sources are cited. We published the complete free method.
Sources
- Derivatex, citing G2 (April 2026) — 51% of B2B software buyers start research in an AI chatbot, up from 29% in 2025; 70–80% of evaluation before vendor contact.
- G2 — 2026 AI Search Insight Report — 45% of buyers say a review-site citation is the most confidence-inspiring signal in an AI answer; review volume and recency correlate with AI visibility.
- Red Engage — Reddit citations in AI answers (2026 study) — r/SaaS, r/marketing, r/entrepreneur, r/smallbusiness, and r/startups account for roughly 35% of B2B SaaS Reddit citations.
- Custom Legal Marketing, citing Semrush (June 2025) — 150,000+ LLM citations analyzed; Reddit 40.1%, Wikipedia 26.3%.
- Derivatex — AI search trends for B2B SaaS — quick answer block in the first 200 words, entity statement, and comparison content as core B2B SaaS AI-search inventory.
- SurfacedBy — analysis of 127,198 AI citations across five engines; 2.7% of sources cited by all five.
Find out what AI tells buyers about your product.
A 30-minute call. We'll run real buyer questions for your category through the engines, live, and show you exactly who gets shortlisted — including whether you need us at all.
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