An AI answer can recommend your SaaS without linking to your website. It can also cite your documentation while recommending a competitor. Those are different situations, and they need different follow-up work.
For a B2B SaaS team, the useful question is where that gap appears: in the answer's wording, your own pages, or the independent sources it cites.
These five tracking tools can help investigate it. I'm a co-founder of Screpy, which is included. This comparison uses official capabilities and plans checked on October 29, 2026, rather than hands-on accuracy testing. The images are the vendors' homepage social graphics.
Separate brand mentions from owned citations
For your report, keep these observations separate:
| Observation | What to record | What it doesn't prove |
|---|---|---|
| Brand mention | Your product's name appears in the answer | A recommendation, a link or a visit |
| Owned citation | The answer links to your domain or a specific page | That the answer recommends buying your product |
| Third-party citation | The answer links to a review, comparison or other independent page | That the page mentions you accurately, or at all |
These are working definitions for an audit. Check each tool's own metric definitions before comparing its percentages.
Imagine reviewing 20 saved answers for a fictional SaaS product. Eight mention the brand, while three link to its domain. Your mention rate is 8 ÷ 20 = 40%, and your owned-citation rate is 3 ÷ 20 = 15%.
Those groups can overlap. Don't add them together or subtract them to claim five answers “need a backlink.” Read the responses first. Some may cite a review that recommends you; another may cite your docs to describe a limitation.
For B2B SaaS, this matters when reporting to different people. A product marketer may need to correct an outdated feature claim. A content owner may need to review the cited implementation guide. An independent comparison may need a factual correction from its publisher.
Keep the prompt, market, platform, date, answer and cited URL together. Otherwise, a higher mention rate can hide the exact source problem you were trying to understand.
1. Screpy: trace mentions back to answers and source pages
Screpy AI Visibility separates brand appearances from cited sources. You can open a saved answer with its question, platform and analysis date, then investigate source domains or individual page URLs.
That lets you ask a more useful question than “Did visibility go up?” For example: did the answer mention our product, cite our security page, or rely on a third-party comparison with an old pricing claim?
Source views can trace citations back to the prompts and answers where they appeared. The source's share of recorded citations isn't referral traffic. Likewise, brand position is mention order among detected tracked brands, not proof of a first-place recommendation.
On Screpy's pricing page, Max includes 50 AI prompts per project and 15 projects. Its regular annual price is $456, paid upfront. Pro doesn't include AI Visibility. The seven-day trial becomes paid unless cancelled; subscriptions renew automatically. Welcome offers have separate conditions, so check the checkout total.
I'd consider it when the same team also handles technical audits and rank tracking. MCP can bring stored evidence into an assistant workflow, subject to plan eligibility; it doesn't automatically repair your pages or make a sampled answer representative of every buyer.
2. OtterlyAI: a focused prompt set for citation monitoring
OtterlyAI combines brand monitoring with citation-source tracking. For a small SaaS team, its useful entry point is a deliberately narrow set of buying questions.
Lite costs $29 a month on monthly billing, with 15 prompts checked daily. The four core engines are ChatGPT, Google AI Overviews, Perplexity and Microsoft Copilot. Claude, Google AI Mode and Gemini are extra add-ons.
An illustrative 15-prompt allocation could cover five category questions, five alternatives questions and five implementation questions. Keep those groups separate when reviewing mentions and sources. Winning a branded implementation question tells you something different from appearing in a category shortlist.
The limit is easy to reach once you add products, markets or different question wording. Choose the questions first, then price the engine coverage. API and MCP access are listed on Standard at $189 a month, rather than Lite.
I'd shortlist Lite for a compact monitoring baseline. During evaluation, check whether you can get from a source summary to the answer you need to audit. A citation count is useful only when your team can explain what was cited and why it matters.
3. Peec AI: compare brand visibility with cited sources
Peec AI reports brand visibility alongside source analytics. That combination is relevant when the product marketer and content team need to discuss the same answer from different angles.
Use the brand view to investigate whether your SaaS appears. Then inspect the cited domains and URLs to distinguish your own resources from independent pages. A widely cited comparison site isn't necessarily a source of visibility for your brand; open the specific page and check what it says.
The current Starter plan is $95 a month on monthly billing, with 50 prompts, three chosen models, daily tracking, one project and unlimited users. Additional models cost extra.
The team allowance is useful if several people need access without passing screenshots around. But don't assume every analysis or automation feature in the full catalogue belongs to Starter. Verify the exact source views and exports your reporting process needs during evaluation.
I'd consider Peec for a shared brand-and-content investigation. The decision should come down to whether colleagues can trace an apparent gap to an answer and a page, rather than whether the dashboard has the largest visibility percentage.
4. Ahrefs Brand Radar: distinguish broad discovery from custom tracking
Ahrefs Brand Radar explicitly distinguishes mentions in answer text from citations linking to pages or domains. It also separates its broad AI Visibility Index from custom prompt tracking.
For B2B SaaS, that second distinction matters. A niche product may have little coverage in an index built around established search demand. Custom questions can monitor a specific buyer's job from the point you configure them. Broad discovery data and your own monitored prompt set answer different questions.
Ahrefs Lite lists $129 a month and includes 150 AI prompt checks per month. The custom prompt documentation explains that five prompts checked daily on one platform use 150 monthly checks. Adding platforms or locations consumes more checks; Claude uses eight checks per update. Larger packages and billed overages have their own pricing.
I'd investigate the included allowance first if the team already pays for Lite or above. For a new purchase, price the exact monitoring workload. Don't confuse an included custom-prompt quota with unlimited access to every Brand Radar data product.
It's a useful distinction for a small SaaS: “not found in the index” and “absent from these specific collected buyer answers” aren't interchangeable findings.
5. SE Visible: source analysis across projects and markets
SE Visible combines brand monitoring with analysis of cited domains and URLs. Its source categories, such as media, blogs and forums, can help separate owned-content work from an investigation into independent coverage.
For example, a SaaS team could inspect whether category answers cite documentation, review sites or community discussions. That gives the team a reading list to investigate. It doesn't establish that buying a placement on one of those sites will change future answers.
On the current monthly pricing view, Basic is $89 a month for 75 tracked prompts, five projects, daily tracking and unlimited users. It includes one location per project.
Location counting is important: the same question in three locations uses three tracked prompts. The prompt is checked across the engines included in the plan, but extra markets aren't free prompt copies. Check the current engine list rather than treating features marked “coming soon” as available.
I'd consider it when several products or brands need a consistent source-review process. Keep country and topic filters with the findings so one market's strong source coverage doesn't hide another market's missing answers.
Turn the gap into a useful SaaS task
A tracker should help you decide what to inspect next. Use the evidence before assigning the fix:
| Pattern in the saved answers | First investigation | Likely person to involve |
|---|---|---|
| Your brand is mentioned with an outdated feature claim | Compare the claim with current product documentation and the cited pages | Product marketer or documentation owner |
| Your page is cited, but a competitor is recommended | Read the buyer's constraints and the actual comparison | Product marketer; product team if the limitation is real |
| Independent sources are cited, but don't discuss your product | Read those pages for relevance, accuracy and missing category context | Content or partnerships owner |
| Only branded questions produce mentions | Add relevant category and alternatives questions to a separate group | Whoever maintains the prompt library |
| A check failed or returned no usable answer | Resolve collection status before counting it as absence | Tool support or the reporting owner |
These are investigation routes, not guaranteed optimization recipes. Sometimes the competitor really is a better fit for the question. Sometimes your docs are accurate and the independent source is stale. Those findings call for different actions.
During evaluation, ask each tool to support the same small audit: one category question, one alternatives question and one implementation question. Keep the market and platform consistent wherever possible. Save the full answer and exact cited page, then label mentions and owned citations separately.
Choose the tool that makes that evidence easy to review within your budget and coverage requirements. Report qualified outcomes such as “mentioned in these collected answers” or “our docs were cited here.” Keep trials, demos and revenue in your actual conversion reporting rather than treating a citation count as a sale.
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