AI builds the shortlist now. Are you on it?
Before a buyer opens a review site or books a demo, they ask an AI assistant for the best tool for their use case, the top alternatives to an incumbent, and how two products compare. Those answers decide your pipeline. CiteRank AI measures exactly how the 8 major engines describe, rank and cite your product.
Vertical benches currently run 4 engines; full tracking covers all 8.
Category discovery moved upstream of your funnel.
SaaS buying now starts with a natural-language question, not a keyword. The engine answers with three names, a short rationale and a couple of citations — and everything below that fold is invisible.
'Best tool for X' answers rarely list more than three or four products, and the set is remarkably stable week to week.
'Alternatives to incumbent' is where challengers get discovered — or where your name is quietly omitted.
Engines summarise your product from third-party pages, so outdated or wrong descriptions become the default answer.
'Works with our CRM / warehouse / ticketing' questions route buyers to whoever documented the integration clearly.
SOC 2, data residency and DPA answers are frequently hallucinated when nothing machine-readable exists.
Content and docs changes ship blind unless something replays the prompt set and attributes each citation shift.
How your category is answered across the engines.
A sample of the B2B SaaS prompt graph, showing which products dominate the answer set and how concentrated the recommendation is.
| Category prompt | ChatGPT | Gemini | Perplexity | Copilot | Answer concentration | You cited? |
|---|---|---|---|---|---|---|
| Best analytics tool for a Series B startup | Product A, Product B, Product C | Product A, Product B, Product C | Product A, Product B, Product C | Product A, Product B, Product C | 3 of 14 | — |
| Alternatives to the category incumbent | Product B, Product D, Product A | Product B, Product D, Product A | Product B, Product D, Product A | Product B, Product D, Product A | 5 of 14 | |
| Which tool integrates with our warehouse | Product C, Product A, Product E | Product C, Product A, Product E | Product C, Product A, Product E | Product C, Product A, Product E | 3 of 11 | — |
| Cheapest option for a 20-person team | Product F, Product D, Product B | Product F, Product D, Product B | Product F, Product D, Product B | Product F, Product D, Product B | 4 of 13 | — |
Illustrative modelled data — not live client results. Names anonymised.
A mid-market SaaS challenger, modelled end to end.
A challenger product was cited on comparison prompts but almost never on top-of-funnel category prompts, so it only entered deals late and on price. We rebuilt the product entity, published machine-readable capability and integration data, and tracked weekly replays.
- Product, pricing and integration entities published with stable identifiers and consistent naming
- SoftwareApplication, Offer and FAQPage schema added across product and docs pages
- Use-case pages rewritten to answer category and alternatives prompts in the first paragraph
- Security, compliance and data-residency answers published as citable structured content
- Weekly prompt replays to attribute each citation gain to a specific change
Illustrative modelled data — not live client results. Names anonymised.
The workspace your growth team would live in.
Visibility trend and per-engine share of voice, loaded with a SaaS-shaped dataset.
AI Visibility — Share of Voice over time
12-week trend, weighted across the tracked LLMs.
Tip: tab into the chart to focus a weekly data point, then use the left and right arrow keys to step through weeks. Press Escape to exit.
AI recommendation share — you vs competitors
Per-engine Share of Voice across the last 30 days of replays. Hover or focus a bar for the breakdown.
Illustrative modelled data — not live client results. Names anonymised.
Questions from b2b saas teams.
How is this different from SEO tooling?
SEO tools measure blue links. CiteRank replays buyer-intent prompts against AI assistants and measures whether your product is named, how it is described and which sources the engine cited to say it.
Can we track our competitive set?
Yes. You define the competitive frame at onboarding and every replay reports share of voice across that set, per engine and per prompt cluster.
Do you rewrite content for us?
Higher tiers include GEO content and schema work. Every tier ships prompt-level recommendations you can hand straight to your own team.
How many prompts should a SaaS product track?
Most B2B categories are well covered by 250 to 750 prompts spanning category, alternatives, integration, pricing and compliance intent.
How quickly does anything change?
Engines refresh at different rates. Entity and schema fixes usually surface within three to six weekly replay cycles.
Find out how AI pitches your product today.
Run a free audit and get the prompt-level view of where you are shortlisted, where you are omitted and what to fix first.