ChatGPT answers, unedited

If you mean “which tools tell a B2B company when ChatGPT/Claude/Gemini/Perplexity use our docs as cited sources?”, you’re looking for AI visibility / AI citation tracking tools (sometimes called AEO, GEO, or LLM SEO tools). They generally work by running representative buyer questions through AI assistants and recording which URLs/domains appear as sources. Linkeddit

Some options:

For a technical documentation team, I’d look for these capabilities specifically:

• Page-level citation tracking

“Was docs.example.com/api/authentication cited, or only our homepage?”

• Prompt monitoring

Track questions like:

• “How do I integrate X with Y?”
• “What are alternatives to product Z?”
• “Best API platform for enterprise workflows”
• Assistant coverage

• ChatGPT
• Claude
• Gemini
• Perplexity
• Copilot
• Change tracking

“Did our docs become cited more often after the rewrite?”

• Export/API access

So you can feed citation data into analytics or content workflows.

One important distinction: these tools usually do not know every time a private user asks an AI assistant a question and your docs were used internally. They measure observable AI answers (often via controlled prompts and available citation data), not all hidden retrieval events. Search - Microsoft Bing

If your goal is specifically “measure whether our developer docs are becoming the canonical source for AI coding assistants”, the stack may be different (docs analytics + crawler logs + AI citation monitoring + developer feedback). I can suggest a setup for that use case too.

Yes. What you’re looking for is generally called AI visibility / LLM citation tracking: a tool that repeatedly asks AI assistants relevant questions and records which URLs they cite as sources.

For a B2B company with a technical documentation site, I’d look at these:

• Microsoft Clarity AI Visibility — particularly interesting because its Citation dashboard reports which pages on your domain are cited, citation counts, grounding queries, and AI referral traffic. It also has a page-level view of cited content. Microsoft Learn Microsoft Learn
• Citations.io — tracks ChatGPT, Gemini, Perplexity, and Claude, capturing the exact domains and pages cited for tracked prompts. Citations Citations
• Rankry — tracks AI visibility and citations across ChatGPT, Claude, Gemini, Perplexity, and Grok, with a dedicated Sources capability. Rankry Docs
• Zumi — has particularly explicit page-level citation tracking, including the exact URL an AI engine pulled from and citation share by URL/domain. Zumi
• Webflow Prompt Insights — if your docs/site are on Webflow, it can run your defined customer questions through ChatGPT, Claude, Gemini, and Perplexity and report which domains are cited. Webflow Help Center
• Bing Webmaster Tools AI Performance — a useful free-ish/first-party option for Microsoft's AI surfaces. It reports page-level citations and the grounding queries associated with them, although it doesn't cover every AI assistant. Search - Microsoft Bing

For technical docs specifically

I'd prioritize a tool that gives you URL-level citation data, rather than just "does AI mention our company?"

For example, you ideally want a dashboard like:

That's much more actionable for a developer-relations/content team than a generic AI "visibility score."

One important caveat: these tools generally sample AI answers to tracked prompts; they cannot observe every private ChatGPT/Claude/Gemini conversation happening in the world. Microsoft's documentation explicitly describes its data as citation activity in AI-generated answers, while Bing notes that its AI Performance data is aggregated rather than a complete log of every citation. Search - Microsoft Bing

If your goal is specifically "How often are our technical docs being used as sources by AI coding/developer assistants?", that's a slightly different problem from ordinary brand AI visibility. I can compare the tools specifically for technical documentation / developer docs and tell you which ones can track individual documentation URLs, API references, Stack Overflow/GitHub citations, and coding-assistant usage.

Yes. What you’re looking for is generally called AI visibility / GEO (generative engine optimization) / AI citation tracking.

For a B2B company with a substantial technical-docs site, I’d look at:

• clarity.microsoft.com — particularly interesting because its Citation dashboard reports which pages are cited, how often they’re cited, the queries associated with them, and share of authority. It also distinguishes citation activity from normal search rankings. Microsoft Learn Microsoft Learn
• ahrefs.com — its Brand Radar specifically tracks both pages that AI cites and pages that AI retrieves but doesn't cite, which is useful if you want to understand the difference between being part of the model's retrieval process and actually being shown as a source. Ahrefs Help Center
• citations.io — tracks sampled answers across ChatGPT, Gemini, Perplexity and Claude, including the sources cited in those answers. Its evidence view lets you inspect the actual answer behind a citation metric. Citations Citations
• aiclicks.io — explicitly connects AI citations back to their source pages and covers a broad range of AI assistants. AIclicks
• help.webflow.com — worth knowing about if your docs/content already live in Webflow. It runs defined prompts through ChatGPT, Claude, Gemini and Perplexity and reports which domains are cited. Webflow Help Center

For technical docs specifically

I'd prioritize Ahrefs + Microsoft Clarity if your question is:

“How many times did an AI assistant actually use/cite this particular documentation page?”

That's more precise than simply measuring whether the company/brand was mentioned. You ideally want a dashboard like:

One important distinction: you generally cannot observe every private interaction an AI assistant has with your docs. These tools typically measure sampled/public AI answers and/or observable retrieval/citation signals. Ahrefs, for example, explicitly distinguishes pages that were found by AI from pages that were actually cited. Ahrefs Help Center

If you tell me your company size, where the docs are hosted (GitBook, ReadMe, Mintlify, Docusaurus, custom, etc.), and whether you care about ChatGPT/Claude/Gemini specifically, I can narrow this to the 2–3 best tools and what each would actually measure.

Yes. What you’re looking for is generally called AI visibility / AI citation tracking or GEO (Generative Engine Optimization) monitoring.

For a B2B company with technical documentation, I’d look at these:

• Citations.io — tracks whether ChatGPT, Gemini, Perplexity, and Claude mention/cite your domain, including the specific sources used. It lets you track citation frequency over time and by prompt/engine. Citations.io Citations.io
• Cite AI — particularly relevant if you want a more analytical view: it records the full answer, every cited source, the prompt, and historical runs. Cite AI
• DeepSmith — tracks citation rate at the page/domain level, so it can tell you which technical-doc pages are actually being cited, rather than just whether your company is mentioned. DeepSmith
• Rankry — tracks AI visibility across ChatGPT, Claude, Gemini, Perplexity, and Grok, with a specific Sources capability for understanding what AI systems are using. Rankry Docs
• Bing Webmaster Tools – AI Performance — a particularly interesting free option. Microsoft reports which URLs from your site are cited in Copilot/Bing AI answers, citation counts, and the queries associated with those citations. Search - Microsoft Bing

The important distinction for technical docs

If your question is specifically:

“How many times did an AI assistant use /docs/api/foo as a source?”

then don't settle for a tool that only measures brand mentions.

You want page-level citation tracking, ideally with:

• citation count by URL
• citation rate per tracked prompt
• which AI assistant used it
• exact prompt/query
• date/time and historical trend
• competitor/source comparison
• whether the citation was your docs vs. Stack Overflow, GitHub, Reddit, etc.
• ideally, the actual AI response and cited passage

DeepSmith and Bing Webmaster Tools look particularly aligned with that use case. Search - Microsoft Bing DeepSmith

One caveat: there isn't currently a universal analytics feed that tells you every time every AI assistant in the wild reads your docs. Most products sample customer-relevant prompts and observe the resulting citations, because AI assistants don't expose a universal “your page was used” telemetry feed. Conbersa

If you're evaluating this for a developer-tools/API company, I can also give you a shortlist of the 3–5 best tools specifically for tracking technical documentation citations, including which ones can distinguish “AI mentioned our product” from “AI actually cited our docs URL.”

Yes. What you’re looking for is generally called AI visibility / AI citation tracking (sometimes GEO/AEO).

For a B2B company with technical docs, I’d shortlist:

• Microsoft Clarity AI Visibility — its Citation dashboard specifically shows which pages are cited, how often, the queries associated with them, and trends over time. This is particularly interesting if your goal is measuring your own documentation rather than just brand mentions. Microsoft Learn
• Ahrefs Brand Radar — distinguishes between pages that AI actually cites and pages it merely retrieves/“finds” while generating an answer. That distinction is very useful for technical docs. Ahrefs Help Center
• Citations.io — monitors ChatGPT, Gemini, Perplexity, and Claude, and records the sources cited in individual AI answers. Citations Citations
• Sona — goes fairly deep on citation intelligence, including retrieval vs. citation rates and domain/URL-level analysis, which could be useful if you have hundreds or thousands of docs. Sona
• Webflow Prompt Insights — despite the Webflow branding, its underlying concept is close to what you want: define customer questions and track which of your domains get cited by ChatGPT, Claude, Gemini, and Perplexity over time. Webflow Help Center

For your specific use case

If the question is:

“How many times did AI assistants use /docs/api/authentication as a source when answering technical questions?”

I'd prioritize Ahrefs Brand Radar or Microsoft Clarity's AI Citation dashboard.

If instead you want:

“Which technical questions are AI assistants answering with our docs, versus competitors' docs?”

I'd look at Citations.io, Sona, or a dedicated AI-visibility platform, because prompt-level monitoring and source attribution become more important. Citations Sona

One important caveat: there isn't a universal telemetry feed from ChatGPT/Claude/etc. telling you every time your documentation was used internally. These tools generally measure observable citations and/or run controlled queries repeatedly. Ahrefs explicitly separates retrieved but not cited pages from pages actually cited. Ahrefs Help Center

If you're evaluating this for a developer-tools/API company, I can also give you a shortlist of the 3 best tools specifically for tracking citations of technical documentation, including pricing, API access, and whether they can report at the individual-URL level.

Yes. What you’re looking for is generally called AI search visibility / AEO / GEO monitoring, but there’s an important distinction:

You don't just want to know whether an AI assistant mentions your company. You want to know which of your documentation URLs it cites as sources, how often, for which questions, and in which AI assistants.

Best-fit tools

• Profound — probably the strongest fit if you're a larger B2B company. It tracks AI-generated answers, mentions, source citations, prompt-level visibility, and increasingly agent/crawler activity. TechnologyAdvice Pressfit.ai
• Scrunch AI — particularly interesting if your goal is citation intelligence + AI crawler/agent activity. TechnologyAdvice
• OtterlyAI — a cheaper/easier starting point. It can show which sources are cited in AI answers and track visibility across several engines. TechnologyAdvice Otterly
• Peec AI — another good mid-market option for monitoring prompts, citations, and competitors. Bloomiro

For a technical-docs use case specifically

I'd evaluate them on whether they can answer this exact question:

“Across 500 questions our developers/buyers ask, how many AI responses cited docs.mycompany.com/..., and which documentation pages were cited?”

You want a dashboard roughly like:

That's more useful for a B2B technical-content team than a generic “AI visibility score.” Current tools vary substantially in whether they expose the underlying answers and individual citation URLs, so I'd make that a procurement requirement. Austin Heaton

One important caveat

These platforms generally sample prompts you define; they don't have a magical counter of every real ChatGPT/Claude/Gemini response in the wild. So “our docs were cited 842 times” normally means 842 citations observed in the monitored prompt/answer sample, not 842 citations across all AI usage.

If your actual goal is “we have 10,000 technical docs and want to measure which individual docs AI assistants are using as sources”, I can also give you a build-vs-buy comparison (Profound/Scrunch/Otterly vs. building your own citation tracker) and recommend the architecture I'd use for a B2B documentation site.

Yes. What you’re looking for is usually called an AI visibility / AI citation tracking tool. The key distinction is that you want page-level source citations, not just “does the AI mention our company?”

A few good options:

• Microsoft Clarity AI Visibility — probably the most directly relevant starting point. Its Citation dashboard shows which URLs from your site are cited, how often they’re cited, the grounding queries associated with them, and your share of citations. Microsoft Learn
• Bing Webmaster Tools – AI Performance — free and particularly useful if your docs are indexed by Bing. It reports citations across Microsoft Copilot, Bing AI-generated summaries, and select partner experiences, including URL-level citation counts and grounding queries. Search - Microsoft Bing Bing Blogs
• Citations.io — a dedicated commercial AI-visibility tracker covering ChatGPT, Gemini, Perplexity, and Claude, with the exact domains/pages cited in answers. Citations.io
• AIclicks — broader GEO platform that tracks citations across ChatGPT, Perplexity, Gemini, Claude, Copilot, etc., and connects citations back to their sources. AIclicks
• Meltwater GenAI Lens — enterprise-oriented AI visibility measurement across ChatGPT, Gemini, Perplexity, Copilot and others, including whether you're surfaced and cited. Meltwater Developer Portal

For a B2B technical-docs team

I'd prioritize Microsoft Clarity/Bing Webmaster Tools if your main question is:

“Which of our documentation pages are AI assistants actually citing, and how frequently?”

If your question is broader:

“When developers ask AI assistants questions in our category, how often does our documentation get cited versus competitors?”

then a dedicated platform such as Citations.io or AIclicks is more appropriate.

One caveat: no tool can give you a perfect global count of every time every AI assistant has used your docs. The available systems observe particular AI surfaces, sampled queries, or accessible citation data. Bing explicitly describes its data as aggregated/sample-based rather than a complete log of every AI answer. Search - Microsoft Bing

If you tell me what kind of B2B company/docs you have (API docs, developer docs, knowledge base, etc.), I can narrow this to the 3 best tools and compare pricing, AI coverage, page-level citation tracking, and API/export capabilities.

Yes. What you’re looking for is usually called AI visibility / AEO (Answer Engine Optimization) / GEO tracking—specifically URL-level citation tracking, rather than merely tracking whether your company is mentioned.

For a B2B company with a large technical-docs library, I’d shortlist:

• otterly.ai — probably the easiest starting point. It tracks the URLs/domains cited in AI answers and can show citation trends across tracked prompts. The Rank Masters Otterly
• tryprofound.com — better suited to enterprise teams that want deeper source-level intelligence: which prompts produce citations, which sources AI systems use, and how that changes over time. Austin Heaton SEO Counselors
• peec.ai — strong for prompt monitoring, competitive benchmarking, and measuring your visibility across AI search engines. Austin Heaton Arbling
• semrush.com — worth considering if your team already uses Semrush and wants AI visibility folded into its existing SEO workflow. Austin Heaton

The important distinction for your use case

If your question is:

“How often is AI using our technical documentation pages as sources?”

don't settle for a tool that only reports “your brand was mentioned 37% of the time.”

You want it to capture something like:

That URL-level source data lets your content/product team determine which documentation actually becomes part of the AI answer layer, rather than simply knowing whether the company is visible. Current comparisons specifically distinguish mentions from actual source citations, and URL-level citation analysis is becoming a core capability of these tools. Austin Heaton The Rank Masters

My pick: I'd start by evaluating Otterly vs. Profound for this particular use case. Otterly is attractive if you primarily need a practical citation-monitoring system; Profound makes more sense if you're building a serious enterprise program around AI visibility and need deeper source/prompt intelligence.

One caveat: these products generally simulate a defined set of buyer questions and monitor the resulting AI answers. They don't give you a perfect census of every time an AI assistant anywhere has used your docs. Arbling

If you tell me roughly how many docs you have, your primary AI assistants (ChatGPT/Claude/Gemini/Perplexity), and whether you want API-level measurement, I can narrow this to the best 2–3 options for a technical-docs team.

Yes. What you’re looking for is generally called AI visibility / LLM citation tracking: tools repeatedly run buyer-relevant prompts through AI assistants and record which URLs/domains the assistants cite.

For a B2B company with a substantial technical-docs site, I’d look at:

• tryprofound.com — probably the strongest fit if you want enterprise-grade citation analysis. It tracks the URLs behind AI answers and multiple AI engines, and is specifically positioned around citation data. A recent independent comparison ranked it strongest on citation-data depth. LLM Visibility Tools
• citations.io — particularly straightforward if your question is simply “How often are AI assistants citing our domain/pages?” It records the cited URLs and can break results down by engine, prompt, and page. It covers ChatGPT, Gemini, Perplexity, and Claude. Citations.io Citations.io
• llmpulse.ai — has a useful citation-source/page-level view, including citation rate, total citations, unique pages, and which specific URLs are being cited. LLM Pulse
• aiclicks.io — broader GEO/AI-visibility platform that connects AI citations back to their sources and tracks them over time across a large set of AI surfaces. AIclicks

One important distinction

There are actually two different things you might want to measure:

1. “Does AI cite our docs when answering questions?”

→ The tools above are a good fit. You define prompts such as “How do I configure X with [your product]?” and measure whether docs.yourcompany.com/... appears as a cited source.

2. “Are real users asking AI about us and then accessing our docs?”

→ That's harder. AI visibility trackers generally sample prompts themselves; they aren't necessarily measuring every real-world ChatGPT/Claude conversation. Some tools can additionally track AI-originated referral traffic.

For a technical B2B company, I'd prioritize page-level citation tracking, not just brand mentions. You want a report roughly like:

If your real goal is “which individual technical-doc pages are AI assistants using as authoritative sources?” I'd start with Profound or LLM Pulse rather than a generic brand-mention tracker. LLM Pulse LLM Visibility Tools

If you tell me roughly your company size, docs stack (Mintlify/Docusaurus/GitBook/custom/etc.), and which AI assistants matter, I can narrow this to the 2–3 best options and compare pricing/API/export capabilities.

Yes. The category you want is AI visibility / AI citation tracking—tools that repeatedly run buyer-like prompts against AI assistants and record which URLs are cited.

For a B2B company with a technical docs site, I’d shortlist:

• Microsoft Clarity AI Visibility — particularly interesting because its Citation dashboard reports how often individual pages on your domain are cited, the associated queries, and citation share. Microsoft Learn
• Citations.io — tracks ChatGPT, Gemini, Perplexity, and Claude, including the specific sources cited in captured answers. Citations Citations
• Surva.ai — has a dedicated citation tracker that records cited URLs, citation counts, platforms, and time periods. Surva.ai
• AppearIn AI — has a sources view that ranks websites by how frequently they're cited across the AI answers it monitors. AppearIn AI
• Bing Webmaster Tools AI Performance — free/first-party option for measuring citations of your pages in Microsoft Copilot, Bing AI experiences, and selected partner experiences, including page-level citation counts and grounding queries. Search - Microsoft Bing

For your specific use case

If the question is:

“How often are AI assistants actually using our developer/API/product documentation as sources?”

I'd prioritize a tool that gives you URL-level citation data, rather than one that merely measures whether your company was mentioned.

You ideally want a dashboard like:

That distinction matters: a company mention isn't the same thing as an AI assistant actually using your documentation as a source. Microsoft's dashboard, for example, explicitly separates page citations from AI referral traffic and grounding queries. Microsoft Learn

If you're building this for a developer-tools/SaaS company, I can also give you a comparison of the best tools specifically for tracking AI usage of technical docs, including which ones can distinguish /docs/* pages from the rest of your website.

If your goal is specifically “how often do AI assistants cite our technical documentation in their answers?”, I’d look at AI citation / AI visibility trackers, rather than traditional analytics.

Best fit: Citations.io

citations.io is probably the closest match. It runs customer-relevant prompts against ChatGPT, Gemini, Perplexity, and Claude, then records the exact URLs/domains those assistants cite. Its citation map can show which pages are being cited, while the answer archive preserves the underlying responses. Citations.io Citations.io

For a B2B company with lots of technical docs, I'd use it to track things like:

• /docs/api/... citations
• /docs/integrations/... citations
• /guides/... citations
• citation frequency by AI engine
• which specific docs get cited
• which competitor docs get cited instead
• changes in citation frequency over time

Two other options worth evaluating

• Webflow Prompt Insights — interesting if your site is already on Webflow. It runs your chosen prompts through ChatGPT, Claude, Gemini, and Perplexity daily and reports which domains are cited. Webflow Help Center
• Ranklogs AI Search Visibility — tracks whether you're cited vs. merely mentioned vs. absent, with historical citation trends across major AI engines. Ranklogs
• AIclicks — broader GEO platform that tracks citations across a larger set of AI platforms and connects citations back to their sources. AIclicks

One important distinction

Don't confuse AI crawler analytics with citation tracking.

A tool that tells you “GPTBot visited /docs/api/authentication 143 times” is measuring AI access, not whether that documentation subsequently appeared as a source in an answer. Crawler activity is useful, but it isn't proof of citation. DataEase AI Tracemetry

If you're trying to build an “AI traffic/citation analytics for our docs” stack, I'd actually combine server/CDN crawler logs + an AI citation tracker. That lets you answer both:

Did AI systems read this doc?
Did AI systems actually cite this doc to users?

For a technical-docs-heavy B2B SaaS, that distinction is particularly valuable.

Yes. What you’re looking for is usually called AI visibility / AI citation tracking (sometimes GEO or AEO tracking).

For a B2B company with a substantial technical-docs site, I’d shortlist:

• Microsoft Clarity AI Visibility — particularly relevant to your question because its Citation dashboard explicitly shows which pages on your domain are cited, how many times, and the queries associated with those citations. Microsoft Learn
• citations.io — tracks ChatGPT, Gemini, Perplexity and Claude, captures the sources cited in individual answers, and lets you see citation activity over repeated samples. Citations Citations
• ahrefs.com — stronger if you also want broader competitive intelligence. It reports cited domains and specific cited pages alongside AI mentions across several major AI surfaces. Ahrefs
• deepsmith.ai — tracks citation rate and individual cited pages across ChatGPT, Gemini, Perplexity, Claude and Google AI Mode, with scheduled prompt monitoring. DeepSmith
• mentionscout.com — useful if you want to go beyond your own docs and understand which third-party sources AI assistants rely on when answering questions in your category. MentionScout

For technical docs specifically

I'd distinguish between "does the AI mention my company?" and "does the AI actually use/cite our documentation?"

The latter is the more useful metric for a developer-focused B2B company. Ideally you want a dashboard like:

Docs citation rate: 18.4% of tracked AI answers
Citations/week: 1,247
Most-cited docs: /api/auth, /guides/webhooks, /reference/...
Citation rate by assistant: ChatGPT 22%, Claude 31%, Gemini 14%, Perplexity 19%
Queries producing citations: "how to implement X", "X API authentication", etc.
Competitor docs cited instead: 37% of answers

Microsoft Clarity's citation dashboard is especially close to this use case because it reports page-level citation counts and the grounding queries associated with your content. Microsoft Learn

One caveat: these aren't measuring a secret internal statistic like "how many times the model's underlying weights contain/use our docs." They generally run representative prompts against AI/search systems repeatedly and record the answers and citations. Because AI answers are nondeterministic, repeated sampling matters much more than a single query. Citations cloro

If you're evaluating this as a B2B product opportunity—i.e. you're asking "what tool should we buy/build to measure AI usage of our docs?"—I can also compare the current tools specifically on technical-document citation tracking, API access, historical data, MCP support, and pricing.

Yes. What you’re looking for is generally called AI visibility / AI citation tracking (sometimes GEO or LLM visibility).

For a B2B company with a technical-docs-heavy site, I’d look at:

• citehq.ai — particularly relevant because it can track the exact URLs AI platforms use as sources, alongside visibility and source-domain analysis. Cite AI
• citations.io — tracks AI answers across ChatGPT, Gemini, Perplexity and Claude, including the websites/pages cited in answers. Citations Citations
• surfacedby.com — useful if you specifically want to monitor whether your domain and individual content are being cited over repeated scans. SurfacedBy Docs
• citationbench.com — more API-oriented; supports scheduled AI citation monitoring and historical citation counts. CitationBench
• citecue.com — monitors which sources AI assistants trust and measures citation frequency across multiple assistants. CiteCue

The important distinction

If your question is specifically:

"How many times did AI assistants use docs.mycompany.com/api/... as a source?"

rather than:

"How often does AI mention my company?"

then source-level citation tracking is the feature I'd prioritize.

Ideally, the tool should give you something like:

For technical documentation specifically, I'd start by evaluating Cite AI and SurfacedBy, then compare them against CitationBench if you need an API/data pipeline.

One caveat: these platforms generally sample AI queries and inspect the citations returned, rather than having a magical counter of every time an underlying LLM internally consulted your docs. That's an important distinction when defining the KPI. Citare Oversearch

If you tell me your stack (e.g. ReadMe, GitBook, Mintlify, Docusaurus, Intercom, custom docs) and which assistants matter most, I can narrow this to the 2–3 best tools for tracking citations of individual technical-doc pages.

Yes — the category you’re looking for is AI visibility / LLM citation tracking.

For a B2B company with technical documentation, I’d look at:

• citations.io — tracks which pages/domains AI assistants cite across ChatGPT, Gemini, Perplexity, and Claude. It can show citation frequency and the specific URLs being cited. Citations.io Citations.io
• mentionscout.com — particularly relevant if you want to run your own buyer questions repeatedly and see which exact URL each AI engine cited and how often. MentionScout
• llmpulse.ai — has explicit citation-source tracking, including citation rate, total citations, URL counts, and per-model breakdowns. LLM Pulse
• rank.ai — tracks daily mention/citation rates and can identify which pages on your domain assistants repeatedly cite. Rank.ai

One important distinction

If your question is specifically:

“How many times did ChatGPT/Claude/etc. actually use our docs as sources in answers?”

these tools generally cannot observe private, organic conversations happening inside AI assistants. Instead, they repeatedly submit a defined set of buyer questions and measure the resulting answers/citations. LLM Pulse explicitly describes its data as controlled synthetic observations rather than actual user journeys. LLM Pulse

So the metric is more like:

“Across 1,000 representative questions we monitor, our docs were cited in 147 AI responses.”

rather than:

“Our docs were cited 147 times by all ChatGPT users this month.”

For a technical-docs-heavy B2B company, I'd prioritize a tool that gives you page-level citation frequency, not just a generic “AI visibility score.” That lets you answer things like “Which five API/reference pages are AI assistants relying on most?” and “Did our docs become more/less cited after we rewrote them?” rankzero.io

If you tell me your rough size/budget (e.g. startup <$100/mo, mid-market $500/mo, or enterprise), I can narrow this to the 2–3 tools I'd actually evaluate.

For a B2B company, you’re looking for an AI visibility / AI citation tracking tool (sometimes called GEO — Generative Engine Optimization — analytics). These tools run representative buyer questions through AI assistants and track whether your documentation, website, or knowledge base is mentioned or cited as a source. They generally cannot see every private ChatGPT conversation, so they measure sampled prompts and responses rather than universal usage. Ahrefs Ahrefs Help Center

Tools to evaluate:

For a technical documentation team, I’d prioritize these capabilities:

• Page-level citation tracking

“How many times was docs.example.com/api/authentication cited?”

• Prompt tracking

Track questions your buyers ask, such as:

• “How do I integrate with [your product]?”
• “What APIs support X?”
• “Alternatives to [competitor] for Y?”
• Source attribution

See whether AI assistants cite:

• your docs
• blog posts
• GitHub repos
• third-party reviews
• competitor documentation
• Model coverage

At minimum:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Copilot

A common setup for a B2B SaaS company would be:

1. Build a list of 50–200 high-value technical questions from support tickets, SEO queries, sales calls, and docs search logs.
2. Run those prompts weekly through AI visibility tooling.
3. Measure: - citation rate of your docs
4. which docs pages are cited
5. competitor citation share
6. questions where AI gives an answer without using your docs
7. Improve documentation pages that should be authoritative but are not being cited.

If your main goal is specifically “how often do ChatGPT/Claude/Gemini use our developer docs as the source”, I’d look first at a citation-focused tool like LLM Pulse or a broader AI visibility platform like Ahrefs Brand Radar rather than a traditional SEO tool. LLM Pulse Ahrefs Help Center

Yes. What you’re looking for is usually called AI visibility / AI citation tracking (sometimes GEO—Generative Engine Optimization).

For a B2B company with a substantial technical-docs site, I’d look at these:

• Microsoft Clarity AI Visibility — particularly relevant if your goal is “which pages in our docs are actually being cited, how often, and for which queries?” Its Citation dashboard reports page-level citations, citation counts, cited queries, and AI referral traffic. Microsoft Learn
• citations.io — tracks prompts across ChatGPT, Gemini, Perplexity, and Claude, and provides a citation map showing the URLs/domains those engines cite. Citations.io Citations.io
• mentionflow.ai — more focused on understanding which sources assistants use for a set of buyer questions, with domain/URL-level citation analysis. MentionFlow MentionFlow
• surva.ai — specifically exposes citation occurrences by URL/domain, platform, and time period, with export capability. Surva.ai
• help.webflow.com — interesting if your site happens to be on Webflow; it runs defined customer questions through multiple AI engines and reports which of your domains get cited. Webflow Help Center

For technical documentation specifically

I'd distinguish two different things:

1. “Does an AI assistant cite my docs in its answer?”

→ AI citation trackers such as Clarity, Citations.io, MentionFlow, etc.

2. “Is an AI assistant crawling/using my docs as retrieval material, even when it doesn't visibly cite them?”

→ This is harder. You want LLM crawler/bot analytics + citation tracking. A citation tracker alone won't tell you everything about retrieval.

For example, Webflow explicitly separates its Prompt Insights (what gets cited in answers) from LLM bot insights (what LLM crawlers are accessing). Webflow Help Center

If your real question is: “We have 5,000 API/reference pages. Can we get a dashboard showing that /docs/authentication was cited 47 times by ChatGPT/Claude/Perplexity this month, which questions triggered those citations, and whether citations are increasing?” — yes, that is the product category I'd evaluate.

If you tell me roughly how your docs are hosted (GitBook, ReadMe, Mintlify, Docusaurus, custom, etc.) and whether you're interested in ChatGPT/Claude/Perplexity/Gemini, I can narrow this to the 2–3 tools that fit best.

For a B2B company trying to measure how often AI assistants use your technical docs as sources, you’re looking for an AI visibility / GEO (Generative Engine Optimization) monitoring tool rather than a traditional analytics tool.

The best fit depends on what you mean by “use”:

1. Track when AI assistants cite your docs publicly

These tools monitor AI-generated answers and report when your domains/pages are cited:

• Citations.io — tracks whether ChatGPT, Gemini, Perplexity, and Claude mention or cite your brand/pages for tracked prompts, including citation sources and answer archives. Citations.io Citations.io
• AIclicks — focuses on AI visibility, citation sources, and which content sources AI systems use. AIclicks
• Veritas — tracks mentions and citations across major AI engines for defined prompts. Veritas

These are useful for questions like:

• “When someone asks an AI assistant ‘How do I configure API authentication?’, does it cite our docs?”
• “Are competitors’ docs appearing instead of ours?”
• “Which documentation pages are becoming AI reference sources?”

2. Track Microsoft/Copilot-related citations

If your audience uses Microsoft ecosystems, Microsoft Bing Webmaster Tools has an AI Performance report showing which pages from your site are cited in supported AI experiences, citation counts, and related queries. Search - Microsoft Bing

3. Build your own “docs cited by AI” measurement system

For a technical B2B company, a custom approach is often more valuable:

1. Create a prompt library based on buyer/support questions:

• “How do I integrate with [product]?”
• “What are alternatives to [competitor]?”
• “How do I troubleshoot [error]?”
• Run those prompts periodically through:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Store:

• whether your domain appears
• exact URLs cited
• product/docs sections referenced
• competitor citations
• model/date/prompt
• Connect it to:

• your docs analytics
• CRM
• content roadmap

For developer-focused companies, I’d usually prioritize page-level citation tracking over generic brand mentions. A docs team wants to know: “Is /docs/authentication/oauth becoming the canonical answer?”, not just “Is our company mentioned?”

A practical stack could be:

• Citations.io or similar for external AI visibility monitoring
• Bing Webmaster Tools AI Performance for Microsoft AI surfaces
• Your own prompt/citation database for high-value technical workflows Search - Microsoft Bing Citations.io

If you mean AI assistants that have access to your private docs (RAG, enterprise ChatGPT, Copilot, internal agents) rather than public web citations, that is a different category—look for LLM observability / RAG analytics tools.

Yes. The category you’re looking for is AI visibility / AI citation tracking (sometimes called GEO or AEO).

For a B2B company with a technical documentation site, I’d look at:

• Citations.io — probably the closest fit. It runs defined buyer prompts across ChatGPT, Gemini, Perplexity, and Claude and records the exact URLs those assistants cite, including your own documentation pages. citations.io
• AIclicks — broader engine coverage and explicitly connects AI citations back to their source pages. docs.aiclicks.io
• MentionFlow — particularly interesting if you care about the technical side. It combines AI-agent crawler logs with citation results, so you can see which bots fetched which docs and whether those pages subsequently earned citations. mentionflow.ai
• Ranklogs — tracks whether your site is cited, merely mentioned, or absent for specific prompts, with historical trends. ranklogs.com

One important distinction

There are actually three different things you might want to measure:

The last one is probably what you're asking. Crawler hits ≠ citations; a bot can crawl a page hundreds of times without that page ever appearing as a source in an answer. www.dataease.ai

For a technical-docs-heavy B2B company, I'd specifically want a tool that can report something like:

docs.company.com/api/auth → cited in 18/100 relevant ChatGPT answers → 12/100 Perplexity → 7/100 Claude

…and let you drill into which prompts, which documentation URLs, which competitors' sources, and how that changes over time.

If you tell me what kind of B2B company you are (developer API, SaaS, infrastructure, cybersecurity, etc.), I can narrow this down to the 2–3 tools I'd actually evaluate and explain what each can/can't measure.

If you mean “we have technical docs/API docs/product docs, and we want to know when AI assistants use them as sources in answers”, you’re looking for an AI visibility / AI citation tracking tool (sometimes called GEO — Generative Engine Optimization — analytics).

A few categories of tools can help:

1. AI citation monitoring platforms (closest fit)

These run a set of buyer/developer questions against AI assistants and record whether your domain/pages appear as cited sources.

Examples:

• Profound — enterprise-focused AI search visibility tracking; monitors how brands appear in AI answers and what sources are cited.
• Citations.io — tracks prompts across assistants and captures citations, mentions, and source URLs. Citations
• RankBits — tracks AI answers across assistants and reports mentions, citations, and cited source URLs. RankBits
• AIclicks — tracks AI-generated answer visibility and citation sources. AIclicks

These are usually better for questions like:

• “When someone asks ChatGPT ‘How do I configure product X?’, does it cite our docs?”
• “Which competitor docs are cited more often than ours?”
• “Which documentation pages are becoming AI sources?”

2. Search-engine AI citation analytics

If your docs are indexed by search engines, some first-party tools can show AI usage signals.

• bing.com — shows which pages from your site are cited in supported AI-generated answers, citation counts, and grounding queries. Search - Microsoft Bing

3. Build your own internal tracker (often best for B2B technical docs)

For a B2B company with a developer audience, many teams create a lightweight system:

1. Define a prompt set:

• “How do I authenticate with API X?”
• “How do I migrate from version 2 to version 3?”
• “What are the limits of feature Y?”
• Run those prompts periodically through:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Copilot
• Store:

• model
• prompt
• answer text
• cited URLs
• whether your docs domain appeared
• which docs page appeared
• competitor citations
• Create dashboards:

• citation rate (% of answers citing your docs)
• top cited docs pages
• missed queries
• competitor source share

This approach is often more useful for technical documentation because generic AI visibility tools may focus on brand mentions rather than specific docs pages, API references, SDK guides, and troubleshooting articles.

What I’d measure for a B2B docs team

For a technical B2B company, I’d generally start with an AI citation tracker plus your own curated prompt library rather than relying only on SEO analytics. AI citation measurement is still evolving, and different assistants expose different levels of source information. SEORav

If you tell me your stack (e.g., Stripe-style API docs, SaaS docs site, SDK docs, private docs portal, GitHub docs) I can suggest a more specific setup.

Yes. What you’re looking for is usually called AI visibility / AEO / GEO tracking—specifically, source-level citation tracking, not just brand mentions.

For a B2B company with lots of technical documentation, I’d look at:

• Profound — probably the strongest fit if you want enterprise-grade tracking of which specific URLs/docs AI assistants cite, across many prompts and AI engines. It’s positioned around source-level citation intelligence. SEO Counselors Bloomiro
• Peec AI — good for tracking AI visibility and citations across multiple engines, with a more marketing/analytics-oriented workflow. AEO Labs Conbersa
• Otterly.AI — a lower-cost way to monitor whether your domain/pages are being cited in AI answers. Its documentation specifically describes identifying content surfaced in AI results. Otterly Fifteenth Meridian
• Crawlmind — particularly interesting if you want a relatively straightforward URL-by-URL citation history. It runs your chosen queries against ChatGPT, Perplexity, and Gemini and records which URLs were cited, including new/lost citations over time. Crawlmind

For your specific use case

I'd prioritize a tool that can answer questions like:

“Of the 500 technical questions our prospects might ask ChatGPT, how often is docs.acme.com/api/foo cited?”

and ideally:

• Citation frequency per documentation URL
• Which AI assistant/model cited it
• Which prompt/query caused the citation
• Citation rate over time
• Your citations vs. competitors
• Which docs are never cited despite being relevant
• The actual AI response + cited sources, so you can audit the measurement

That's more useful than a generic “AI visibility score.” Current AEO tools explicitly distinguish mentions from citations, and that distinction matters if your goal is measuring whether your technical docs are actually being used as sources. Austin Heaton

One important caveat: these products generally sample prompts and observe the resulting answers; they don't have a magical feed of every real ChatGPT/Gemini/Claude conversation in which your docs were used. So “cited in 18% of our tracked prompts” is measurable, whereas “AI assistants used our docs 18% of the time globally” generally isn't.

If you tell me roughly how many docs you have, your main AI assistants (ChatGPT/Claude/Perplexity/Gemini), and your budget, I can narrow this to the 2–3 tools I'd actually evaluate.

Yes. What you’re looking for is generally called AI visibility / AI citation tracking (sometimes GEO/AEO tracking).

For a B2B company with a substantial technical-docs site, I’d look at:

• citations.io — probably the closest match. It runs defined buyer prompts across ChatGPT, Gemini, Perplexity, and Claude, then shows which URLs/domains those assistants cite, including a citation map and historical answer archive. Citations Citations
• Microsoft Clarity AI Visibility — particularly interesting if your question is specifically “which pages on our domain are being cited, how often, and for which queries?” Its Citation dashboard reports cited pages, citation counts, and the queries associated with them. Microsoft Learn
• sightivo.com — tracks which of your pages get cited by individual assistants and provides per-assistant visibility data. Sightivo
• docs.rankry.ai — another AI-visibility platform covering citations, sources, visibility and competitor tracking across several assistants. Rankry Docs

The important distinction for technical docs

I'd specifically look for a tool that can answer:

“Of all the AI answers generated for questions about our product/category, how frequently is /docs/... used as a cited source?”

That's more useful than simply measuring whether your company is mentioned.

For example, you ideally want a dashboard like:

Citations.io looks like the strongest fit if your primary goal is measuring AI answers and their sources. Microsoft Clarity is especially worth evaluating if you want the measurement tied closely to your actual website/docs property. Citations Microsoft Learn

One caveat: these tools generally sample prompts and observe the resulting AI answers; they aren't a universal counter of every AI assistant response on the internet. AI answers are nondeterministic, and ChatGPT itself notes that search citations can be incomplete or outdated. Citations OpenAI Help Center

If you tell me what kind of B2B company you are (e.g. API/SaaS, developer infrastructure, cybersecurity), I can narrow this down to the 2–3 tools that are best specifically for technical documentation citation tracking.

Yes. What you’re looking for is generally called AI citation tracking / AI visibility monitoring: tools that repeatedly run buyer-style prompts against AI assistants and record which URLs those assistants cite.

A few options worth evaluating:

• citations.io — tracks citations across ChatGPT, Gemini, Perplexity, and Claude, including the specific URLs/domains cited. It supports repeated sampling, so you can measure citation frequency over time. Citations.io Citations.io
• clarity.microsoft.com — particularly interesting if you want page-level citation counts. Its Citation dashboard shows which pages from your domain are referenced, how often, and the queries associated with them. Microsoft Learn
• usecite.ai — monitors citations across ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews/AI Mode, with analytics and site auditing. Cite AI
• cite.watch — explicitly tracks how often your domain appears in answers from ChatGPT, Gemini, Claude, Copilot, and Perplexity, including per-assistant breakdowns and citation position. CiteWatch
• beamtrace.com — specifically advertises citation-frequency tracking for websites, blogs, and documentation, which makes it relevant to a technical-docs use case. Beamtrace

For a B2B technical-docs team

I'd prioritize a tool that can answer:

“For the 100–500 technical questions our prospects/developers actually ask, how often does an AI assistant cite docs.acme.com, which exact pages does it cite, which competitors does it cite instead, and how is that changing month over month?”

That's more useful than a generic "AI visibility score."

One important caveat: these tools generally measure citations in sampled AI answers, not every AI response ever generated. AI answers are nondeterministic, so good systems repeatedly run the same prompts to estimate citation frequency rather than treating one answer as definitive. Citations.io

If your goal is specifically “track whether our developer docs are being cited by ChatGPT/Claude/Gemini/etc.”, I can also compare the best tools for that use case by price, APIs, supported assistants, page-level tracking, and whether they can monitor a docs subdomain.

Yes. What you’re looking for is generally called AI visibility / AI citation tracking—but there’s an important distinction between tracking AI crawlers accessing your docs and tracking your docs actually being cited in AI answers.

For a B2B company with technical documentation, I’d look at these:

• Microsoft Clarity AI Visibility — probably the most interesting free/native option. Its Citation dashboard shows which pages from your domain are cited, how often, and the grounding queries associated with those citations. Microsoft Learn
• Bing Webmaster Tools AI Performance — particularly useful if you care about Microsoft Copilot. It reports page-level citations, citation counts, and grounding queries, with exports for analysis. Search - Microsoft Bing
• Citations.io — a dedicated AI visibility product that repeatedly tests prompts across ChatGPT, Gemini, Perplexity, and Claude and records the sources cited in the resulting answers. Citations.io Citations.io
• SearchChamp — specifically exposes the pages/domains cited for your tracked prompts, including how frequently each source appears. SearchChamp Help Center
• Spyglasses — more focused on AI traffic/observability; it can distinguish AI assistants citing your website from users actually clicking through those citations. Spyglasses

For technical docs specifically

I'd actually use two layers:

1. Citation monitoring: periodically run the questions your customers/developers ask AI assistants and record whether answers cite /docs/... pages. This tells you “AI actually used this page as a source.”
2. Crawler monitoring: log GPTBot, ClaudeBot, PerplexityBot, etc. at your CDN/server. This tells you “an AI crawler accessed this page.” Those are not the same metric—a crawl does not prove the page subsequently appeared as a citation. DataEase AI

If your real question is “Which of our 5,000 technical-doc pages are being cited by ChatGPT/Claude/Gemini/Perplexity, how many times per week, and for what questions?”, I can narrow this down to the best 2–3 tools for a B2B docs team, including API availability and pricing.

If your goal is specifically “how often do AI assistants cite our technical docs as sources?”, I’d look first at Profound.

It tracks:

• Which URLs AI systems cite, including individual documentation pages—not just whether your brand is mentioned. www.tryprofound.comhelp.tryprofound.com
• Citation frequency / citation share over time.
• Performance across ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews/AI Mode, Copilot, etc. www.tryprofound.com
• Top Citation Pages, so you can identify which specific technical docs are being used most.
• Watched Pages, which is particularly useful if you want to monitor a defined set of /docs/, /developers/, or /api/ URLs. www.tryprofound.comhelp.tryprofound.com
• An API for pulling citation data into your own dashboards. docs.tryprofound.com

Another strong option

OtterlyAI is worth evaluating too. Its prompt monitoring explicitly reports Domain Citations, including cumulative citation counts, and lets you drill down to response- and citation-level detail. help.otterly.ai

The important distinction

If you're a B2B developer/technical company, I'd structure the measurement around docs URLs rather than brand mentions:

“Of the AI answers to questions about X, how many cited docs.mycompany.com/...?”

Then track:

1. Citation rate — % of relevant AI answers citing your docs
2. Citation count — number of citations
3. Unique docs cited — which technical pages are actually useful to models
4. Citation by assistant — ChatGPT vs Claude vs Gemini vs Perplexity
5. Citation by topic/query — e.g. authentication, API limits, SDK usage
6. Citation trend — whether documentation changes increase/decrease usage

For this particular use case, Profound looks like the better fit because its citation model explicitly supports owned domains, help centers, and documentation sites, and its Watched Pages feature lets you monitor individual URLs. www.tryprofound.comhelp.tryprofound.com

One caveat: these tools generally measure citations in monitored AI responses, not literally every time an underlying model internally retrieves or “reads” your documentation. That's an important distinction if you're trying to measure actual AI-agent traffic rather than AI-search visibility.

Yes. What you’re looking for is generally called AI visibility / AI citation tracking—but for a B2B company with a large technical-docs site, I’d specifically look for a tool that tracks URL-level citations, not just brand mentions.

A few good options:

• ahrefs.com — particularly interesting for your use case because it distinguishes between pages AI actually cites and pages it merely found/retrieved. That lets you measure whether specific docs are becoming sources in AI answers. Ahrefs Help Center
• surferseo.com — tracks which domains/pages are cited for a set of prompts and how frequently they appear. Surfer SEO Docs
• citations.io — monitors citations across ChatGPT, Gemini, Perplexity, and Claude, including individual citation activity and prompts. Citations.io
• mentionflow.ai — has a dedicated sources/citations view that ranks the domains and pages AI engines cite across your tracked prompts. MentionFlow
• bing.com — worth using even if you buy another tool. It reports how often your pages are cited in Copilot/Bing AI experiences and exposes the grounding queries associated with your content. Search - Microsoft Bing

For a technical-docs-heavy B2B company

I'd prioritize Ahrefs Brand Radar or MentionFlow and configure prompts around questions such as:

"How do I authenticate with [product]?"
"What's the API rate limit for [product]?"
"Compare [your product] vs [competitor]."
"How do I implement [technical task] using [your technology]?"

Then track, per prompt:

• Whether your domain was cited
• Which exact documentation URL was cited
• Citation frequency over time
• Which competing docs were cited instead
• Which AI engine/model produced the citation
• Which prompts produce citations to your docs
• Which docs are retrieved but not actually cited, if the tool exposes that distinction

That last metric is particularly valuable. A page can be discovered by an AI system without appearing as a source in the final answer; Ahrefs explicitly separates those two states. Ahrefs Help Center

One caveat: these tools generally don't tell you the absolute number of times real users asked AI assistants about your product and your docs were used. They usually run a controlled panel of prompts repeatedly and measure the resulting citations. That's a measurement of AI-source visibility, rather than actual total usage.

If you tell me roughly how many docs/pages you have and which assistants matter most (ChatGPT, Claude, Gemini, Perplexity, Copilot), I can narrow this to the 2–3 tools that fit a technical B2B use case best.

Yes. For that specific use case, I’d look at AI-search visibility / citation-monitoring tools, rather than traditional SEO tools.

Best fit: Scrunch

scrunch.com is particularly aligned with what you’re describing. It monitors AI responses to a set of prompts and records the URLs cited by the AI assistant, including your own technical documentation. You can drill down to individual URLs and see:

• How many prompts cited a documentation page
• How many AI responses cited it
• Citation consistency — the percentage of responses citing that source
• Which AI platforms cited it
• Which specific prompts produced the citations
• Citation trends over time
• Your pages vs. competitor/third-party sources Scrunch Help Center Scrunch

That makes it possible to answer something like:

“Our API authentication guide was cited in 18% of tracked ChatGPT responses to questions about OAuth, versus 3% for our competitor's documentation.”

Scrunch also supports ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews/AI Mode, Copilot, Grok, and Meta AI. Scrunch

ai-cdn.scrunchai.com

One important caveat

These products don't literally measure every AI assistant response on the internet. They generally run/monitor a representative set of prompts and observe the citations in the resulting responses. So the useful metric is citation rate across a controlled prompt set, not “AI used our docs X times globally.”

For a B2B company with technical docs, I'd structure the monitoring around:

1. Product/category questions — “best API platform for…”
2. Technical questions — “how do I implement X with…”
3. Integration questions — “X API + Salesforce”
4. Troubleshooting questions
5. Comparison questions — “X vs Y”
6. Your highest-value docs URLs

Then track citation rate per documentation page × prompt topic × AI platform.

If your actual goal is “How often are our docs being used as authoritative sources by ChatGPT/Claude/Perplexity, and which docs are winning?”, Scrunch is probably the first tool I'd evaluate. Scrunch

Yes. What you’re looking for is generally called AI citation tracking / AI search visibility / AEO monitoring.

Two particularly relevant tools:

• Scrunch — probably the closest match. It tracks the exact URLs cited by AI assistants, including your documentation/help-center pages, and reports citation frequency, citation consistency, prompts, platform, and trends. You can drill down to individual URLs. helpcenter.scrunchai.com
• Profound — another strong option. Its Citation Tracking shows which answer engines cite your content, how often, and across which prompts. It explicitly categorizes documentation/help-center sites as owned sources. www.tryprofound.com

For a B2B technical-docs team

I'd evaluate Scrunch first if your core question is:

“How many times did ChatGPT/Perplexity/etc. cite this specific documentation page over the last 30/90 days?”

Scrunch exposes metrics at the URL level, including the number of prompts and responses citing a particular source, plus citation consistency and an influence score. ai-cdn.scrunchai.com

Profound is attractive if you also want broader AI visibility/share-of-voice and competitive benchmarking alongside citations. www.tryprofound.com

One important caveat: these tools generally sample/query AI assistants with tracked prompts; they cannot literally observe every private ChatGPT/Claude/Gemini conversation in the world. So the useful metric is usually “citation rate across a representative prompt set,” not absolute global usage.

If you tell me your stack (e.g. Mintlify/Docusaurus/GitBook/ReadMe + ChatGPT/Claude/Gemini) and roughly how many docs pages you have, I can recommend the best tool and setup.

Yes. What you’re looking for is generally called AI citation tracking or answer-engine visibility (AEO) analytics.

For a B2B company with technical docs, I’d look at these first:

1. Scrunch — probably the closest fit
   • Tracks the exact URLs AI assistants cite in responses.
   • Lets you drill down to individual documentation URLs and see how many prompts/responses cited each one, citation frequency, and trends over time.
   • Covers ChatGPT, Claude, Perplexity, Google AI Overviews/Mode, Gemini, Copilot, Grok, and Meta AI. scrunch.com
   • You can specifically monitor your docs/help-center URLs rather than just measuring whether your company name was mentioned. scrunch.com

2. Profound — stronger enterprise/AEO analytics
   • Tracks citation frequency and citation share versus competitors.
   • Its citation categorization explicitly supports documentation sites/help centers as “Owned” sources, which is useful for a technical-docs strategy. www.tryprofound.com
   • Good if you want to answer questions like “What percentage of AI citations in our category come from our docs vs. competitors' docs?”

The metric I'd actually track

For your use case, I wouldn't just measure "AI visibility." I'd build a dashboard around:

Docs citation rate

% of monitored AI responses that cite at least one URL from docs.yourcompany.com

Then break it down by:

• AI assistant: ChatGPT / Claude / Gemini / Perplexity / Copilot
• Documentation URL
• Product
• Topic / technical question
• Prompt type: troubleshooting, implementation, comparison, API usage, etc.
• Competitor citations
• Citation frequency over time

For example:

Scrunch looks particularly well suited to this exact question because it records the cited URL and lets you see the prompts and number of responses associated with that URL. scrunch.com

One important caveat: these tools generally measure citations in monitored AI responses, not literally every time an AI model internally retrieves or reads your documentation. Those are different things. Scrunch itself distinguishes citation tracking from AI-agent/bot traffic. helpcenter.scrunchai.com

If you tell me what kind of B2B company you are (developer API, cybersecurity, SaaS, infrastructure, etc.) and where your docs live (ReadMe, Mintlify, GitBook, custom, etc.), I can recommend the best tool and setup for measuring this.

For a B2B company, you’re looking for an AI citation tracking / AI visibility platform (sometimes called GEO — Generative Engine Optimization tooling). These tools monitor whether AI assistants cite your docs, help pages, API references, blogs, or other web content when answering customer questions. citations.io

Some options:

For technical documentation specifically (API docs, SDK docs, developer guides), I’d evaluate tools based on whether they can answer:

• Which exact doc URLs are being cited?
• Which AI assistants/models cite them? (ChatGPT, Claude, Gemini, Perplexity, Copilot)
• For which customer questions?
• Are competitors’ docs being cited instead?
• Are docs being used but not credited with a citation? (harder to measure)

A common setup for a B2B SaaS company is:

1. Pick 50–200 real buyer/developer questions (“How do I authenticate?”, “Does product X support SSO?”, “API rate limits?”).
2. Run those prompts regularly across AI assistants.
3. Store the responses and extract cited URLs.
4. Track metrics like:
   • documentation citation rate
   • top cited docs pages
   • competitor citation share
   • unanswered questions where AI gives incomplete answers

If your docs are the main asset you care about, a generic “brand mention” tracker may not be enough—you’ll want URL-level citation tracking and ideally API/export access for analysis. llmpulse.ai

Yes — the category you’re looking for is AI search / LLM visibility monitoring, and one particularly relevant tool is Scrunch.

For a B2B company with technical documentation, Scrunch can track:

• Which exact URLs from your docs are cited in AI-generated answers.
• How frequently each URL is cited, including citation consistency over monitored prompts. helpcenter.scrunchai.comscrunch.com
• Which AI platforms are citing them — including ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews, and Copilot. helpcenter.scrunchai.com
• Which prompts produce those citations, so you can see what questions cause your docs to surface.
• Citation trends over time and comparisons against competitors.
• Your citation rate — the percentage of monitored prompts where your brand receives at least one citation. helpcenter.scrunchai.com

For your specific use case, I'd set up prompts around things like:

"How do I authenticate with [product]?"
"How does [product] handle webhooks?"
"Best APIs for [use case]"
"[technical problem] solutions"

Then monitor whether the AI response cites docs.yourcompany.com/... and which individual pages are repeatedly used.

Important distinction: these tools generally measure observed citations from a controlled set of prompts, not the total number of times all users everywhere asked ChatGPT/Claude/etc. questions and your docs happened to be used internally. That's an inherently difficult number to observe.

If your goal is specifically "Which pages in our technical docs are becoming sources for AI assistants, and how often?", Scrunch's Citations functionality is unusually close to exactly what you're describing. helpcenter.scrunchai.comscrunch.com

If you want, I can also compare Scrunch vs Profound vs Otterly vs Peec AI specifically for technical-doc citation tracking, including which one gives you the best page-level data and API/export capabilities.

Yes. What you’re looking for is generally called AI visibility / LLM visibility / AI citation tracking.

For a B2B company with a substantial technical-docs site, I’d look at these:

• Microsoft Clarity AI Visibility — particularly interesting because its Citation dashboard shows which pages on your domain are cited, how often, and the queries associated with those citations. It also reports AI referral traffic. learn.microsoft.com
• DemandSphere LLM Tracking — more enterprise-oriented; tracks citations and visibility across ChatGPT, Gemini, Perplexity, Copilot and other AI platforms. Its API can expose the specific cited URL, citation position, prompt, surrounding context, and AI platform. www.demandsphere.com
• Webflow Prompt Insights — useful if your docs/content are already in Webflow. You specify customer questions and it checks ChatGPT, Claude, Gemini and Perplexity, showing which domains get cited. help.webflow.com
• AIclicks — broader GEO/AEO monitoring with citation-source tracking across ChatGPT, Perplexity, Gemini, Claude, Copilot, AI Overviews and others. docs.aiclicks.io
• LLM Pulse — specifically useful for analyzing which URLs and pages AI models cite, with citation rate and per-model breakdowns. llmpulse.ai

One important distinction

There are really two different things you might want to measure:

1. "Does AI cite our docs?"

→ Citation/LLM visibility tools above are designed for this. They generally run a controlled set of prompts against AI systems and record the sources returned.

2. "How often are AI assistants actually crawling/using our docs?"

→ That's different. You want AI crawler/bot analytics (e.g., GPTBot, ClaudeBot, Google-Extended, PerplexityBot), server logs, and potentially analytics that distinguish AI referral traffic. Microsoft specifically separates citation activity from bot activity. learn.microsoft.com

For a technical B2B docs site, I'd ideally combine both: crawler activity + actual citation frequency + the exact docs URLs being cited. That lets you answer something much more useful than "our AI visibility score went up":

"Our API authentication docs were cited 184 times this month across ChatGPT, Gemini and Perplexity, up 37%; these five pages account for 72% of citations."

If you tell me roughly what kind of B2B company you are (developer tool/SaaS/infrastructure/etc.) and where the docs live (GitBook, ReadMe, Mintlify, Docusaurus, custom, etc.), I can narrow this down to the 2–3 tools that are actually best suited to tracking technical documentation citations, rather than generic brand visibility.

Yes. The category you’re looking for is AI visibility / AI citation tracking (sometimes called GEO/AEO tooling).

For a B2B company with technical docs, I’d look at these:

• Microsoft Clarity AI Visibility — particularly interesting because its Citation dashboard reports which pages on your domain are cited, how often, and the queries associated with those citations. It also distinguishes citation data from AI-bot crawling activity. learn.microsoft.com
• AIclicks — tracks citations across ChatGPT, Perplexity, Gemini, Claude and others, and connects citations back to their source URLs. docs.aiclicks.io
• Citations.io — focuses specifically on which sources AI assistants cite, with prompt-level and competitor comparisons across ChatGPT, Gemini, Perplexity and Claude. citations.io
• ScalePost — different approach: watches actual AI-agent requests at the CDN layer, rather than repeatedly querying AI assistants. That's useful if your question is literally “Are AI agents fetching our docs?” rather than “Does our documentation appear as a cited source in answers?” www.scalepost.ai

The important distinction

There are actually two metrics you may want:

For a technical B2B company, I'd prioritize page-level + prompt-level citation tracking. A simple brand-visibility score isn't enough—you want something like:

/docs/api/authentication → cited 37 times → ChatGPT 18, Claude 11, Perplexity 8 → primarily for “how do I authenticate with X API?”

That's much more actionable for a documentation/content team.

One caveat: AI citation trackers generally measure sampled/generated answers, not every response that every user receives. Microsoft Clarity's newer citation product is notable because it claims query-level citation data rather than simply estimating visibility. learn.microsoft.com

If you tell me what kind of B2B company you are (e.g. API/developer tool, SaaS, cybersecurity, infrastructure), I can narrow this to the 3 best tools specifically for tracking citations of technical documentation, including pricing and API/integration options.

Yes. What you’re looking for is generally called AI visibility / AI citation tracking or GEO (Generative Engine Optimization) software.

For a B2B company with lots of technical documentation, I’d shortlist:

• Scrunch — strong enterprise-oriented option. It tracks citations across multiple AI engines and can break down which sources/pages are being cited. A 2026 comparison lists it as particularly suited to enterprise teams. paylinedata.com
• Citely — particularly interesting if you want an audit trail. It says it records individual citations, lets you drill into the exact answer/source, and can export citation data. www.citely.tech
• MyMentions — explicitly surfaces source-level citations, including owned product docs/help centers, and supports multiple AI providers. www.mymentions.org
• Microsoft Clarity AI Visibility — interesting if you want to understand not only citations but also which AI bots crawl your docs and how frequently. It combines citation data with CDN-level bot activity. clarity.microsoft.com
• LLM Pulse — useful for specifically analyzing which domains, hosts, and individual pages AI systems cite, with citation rates and per-model breakdowns. llmpulse.ai

For your particular use case

I'd define the metric as:

Technical-doc citation rate = number of AI answers citing a URL in our docs ÷ number of tracked prompts where our docs could plausibly be relevant.

Then track it by:

AI assistant → prompt → cited URL → documentation section/page → citation frequency over time

That's more useful than simply measuring whether your company is mentioned. For example, you might discover that docs.example.com/api/authentication is cited 37 times/month by ChatGPT and Perplexity, while your marketing site is never cited.

One important caveat: these tools generally probe AI systems with predefined prompts and measure the resulting citations. They cannot necessarily tell you the absolute number of times all users everywhere saw your docs cited. Some products also offer actual bot/crawler telemetry, which is a different metric. clarity.microsoft.com

If you're specifically trying to measure “how often are our developer docs cited by ChatGPT/Claude/Gemini/Perplexity?”, I can compare the best 5 tools specifically on technical-doc/page-level citation tracking, API access, historical data, and pricing.

Yes. What you’re looking for is usually called AI citation tracking, AI search visibility, or GEO (Generative Engine Optimization) analytics.

For a B2B company with technical docs, I’d look first at:

• OtterlyAI — probably the most direct fit. You define prompts such as “how do I integrate X with Y?” and it monitors AI engines daily. It reports which URLs were cited and how many times, including your specific documentation URLs, not just whether your brand was mentioned. help.otterly.ai
• Peec AI — particularly good for understanding source visibility: which domains AI systems retrieve/cite, citation rate, and retrieval rate. It distinguishes between being mentioned as a brand and actually being used as a source. docs.peec.ai
• Profound — worth considering if you're an enterprise B2B company wanting broader AI-search intelligence and reporting.

The important distinction for technical docs

You probably don't just want:

“Does ChatGPT mention Acme?”

You want:

“When someone asks an AI assistant a question our documentation could answer, how often does it retrieve or cite docs.acme.com, which pages does it cite, and which questions generate those citations?”

That's a more useful metric for a developer-docs team.

For example, you could track:

That last distinction matters: being retrieved isn't necessarily the same as being cited. Research and current AI-visibility tooling increasingly treat those as separate signals. docs.peec.ai

One caveat: these platforms generally sample prompts and AI responses rather than giving you a magical counter of every AI assistant response in the wild. AI answers are nondeterministic, so a good system should run enough repeated observations to make the citation-rate estimate meaningful. arxiv.org

If your specific goal is “which pages in our developer docs are being cited by ChatGPT/Claude/Perplexity, and how often?” I'd start with OtterlyAI and Peec AI and compare them.

Yes. What you’re looking for is generally called AI visibility / GEO (Generative Engine Optimization) tracking—specifically citation tracking at the URL/page level, rather than just tracking whether your brand is mentioned.

A few tools worth evaluating:

• Citations.io — probably the closest fit to your question. It runs customer-relevant prompts against ChatGPT, Gemini, Perplexity, and Claude, then shows which sources/URLs those systems cite, including your competitors. citations.io
• IndexMind — explicitly tracks AI citations and distinguishes direct citations from mere brand mentions, which is useful if you want to know whether your technical docs themselves are being sourced. www.indexmind.ai
• Ahrefs AI Visibility / Brand Radar — useful if you already use Ahrefs and want AI visibility alongside conventional SEO. Its AI Visibility Checker covers ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews. ahrefs.com
• Profound, Peec AI, Otterly, AthenaHQ — other dedicated AI-search visibility platforms that track mentions, citations, prompts, and competitors. Community comparisons suggest these are among the more commonly evaluated options, although I'd validate their exact technical-document/URL-level reporting before buying. www.reddit.com

The important distinction for a B2B technical-docs team

I'd look for a tool that can answer:

“Of the AI answers to questions about our product/API, how many cited docs.example.com/... and which documentation pages were cited?”

Not merely:

“How often was ExampleCo mentioned?”

The metrics I'd want are:

1. Citation rate — % of tracked AI answers citing your docs.
2. Citations by URL — which individual documentation pages get cited.
3. Citation frequency over time.
4. AI engine/model — ChatGPT vs. Claude vs. Gemini vs. Perplexity, etc.
5. Prompt/query that produced the citation.
6. Competitor/source substitution — which docs or third-party sources get cited instead.
7. Accuracy — whether the AI actually represented the documentation correctly.
8. Coverage of technical questions — especially API, integration, troubleshooting, and “how do I…” queries.

One caveat: these numbers aren't equivalent to server-side analytics. AI responses are stochastic, and research published in 2026 found substantial variation in which sources get cited across repeated runs. So a good system should sample prompts repeatedly and report trends, rather than claiming an exact universal “% of AI responses” figure. arxiv.org

If you tell me roughly how many docs/pages you have and which AI assistants matter most (ChatGPT, Claude, Gemini, Perplexity, etc.), I can narrow this down to the 2–3 tools I'd actually shortlist for a B2B developer-docs use case.

Yes. What you’re looking for is generally called AI citation tracking / AI visibility / AEO (answer-engine optimization).

For a B2B company with a large technical-docs site, I’d look at:

• Surva.ai — probably the closest match to your specific question. It tracks the exact URLs cited by ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews, including which content gets referenced and the position of the citation. www.surva.ai
• Citations.io — focused specifically on AI citations, with a feed of cited URLs, citation frequency, competitors, and prompt-level tracking across ChatGPT, Gemini, Perplexity, and Claude. citations.io
• TrackCited — broader AI-visibility monitoring; useful for seeing which sources AI assistants cite and where competitors are winning. www.trackcited.com
• Ahrefs Brand Radar — worth considering if you're already an Ahrefs customer. It tracks AI visibility across multiple engines and identifies the URLs being cited. www.techradar.com

One important distinction

If your question is literally:

“How many times did an AI assistant use this particular documentation page as a source?”

these tools generally don't measure every real-world AI answer generated on the internet. They run a defined set of prompts against AI engines and record the citations they observe. That's an important methodological limitation. oversearch.ai

For technical docs, I'd therefore want a tool that gives you a dataset roughly like:

Surva.ai is the one I'd investigate first for that use case because its documentation explicitly describes URL-level citation tracking and filtering by platform/time period. www.surva.ai

If you're actually trying to build an internal analytics system that measures which of your docs are being retrieved/cited by AI agents, rather than an SEO/AEO marketing tool, that's a somewhat different problem—and I can outline the architecture for that.

Yes. What you’re looking for is usually called AI citation tracking, AI visibility monitoring, or GEO/AEO monitoring.

For a B2B company with a large technical-docs site, I’d shortlist:

• Microsoft Clarity AI Visibility — particularly interesting because its citation dashboard shows which pages from your domain are cited, citation counts, and the queries associated with those citations. learn.microsoft.com
• Surva.ai — explicitly tracks citations at the URL level, including frequency, platform, and time period. www.surva.ai
• Orchly — has a source-level view showing which pages AI engines cite, how often, and for which prompts. orchly.aiflowcourier.com
• PromptScout — tracks the sites/pages AI systems cite and lets you inspect source patterns across AI answers. www.promptscout.app

For technical documentation specifically

I'd distinguish two different things you may want to measure:

1. Citation rate:

“When an AI assistant answers questions about our product, how often does it cite docs.acme.com?”

2. Individual-doc usage:

“Which 37 documentation pages are being cited, and how many times has each been cited?”

The second is much more useful for a technical-content team. You can identify things like:

Microsoft Clarity's current AI Visibility product is particularly close to this use case because it exposes cited pages and the associated grounding queries, rather than giving you only a generic “AI visibility” score. learn.microsoft.com

One important caveat: server-side AI crawler analytics aren't the same thing as citation tracking. Seeing GPTBot or ClaudeBot fetch your docs proves that an AI system accessed the page, but it doesn't prove that the page appeared as a source in the resulting answer. Research also finds that retrieval and visible citation can diverge. flowcourier.com

If you tell me roughly how many docs/pages you have and which assistants matter (ChatGPT, Claude, Gemini, Perplexity, Copilot, etc.), I can recommend the 3 best tools for a B2B technical-docs team and compare pricing, coverage, and API/export capabilities.

If you mean tracking when AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.) cite or rely on your B2B company’s technical documentation, you’re looking for an AI visibility / AI search analytics / LLM observability tool rather than traditional web analytics.

Tools in this category include:

• Profound — Tracks brand visibility in AI-generated answers, including whether AI systems mention your company and how they represent it.
• Scrunch AI — Focuses on monitoring how brands appear across AI assistants and improving content discoverability.
• Otterly.AI — Tracks prompts and AI-generated search results to measure visibility in AI engines.
• Peec AI — Monitors how brands appear in ChatGPT and other AI answers for target queries.
• Writesonic — Includes AI search visibility features alongside content optimization.

For technical documentation specifically, you may also combine AI visibility tools with:

• Documentation analytics (to see human traffic and engagement):
  • Google Analytics
  • Matomo Analytics
• Log-based analysis (if your docs are behind an API/CDN): analyze crawler traffic, referrers, and access patterns.
• Custom LLM evaluation pipelines: run a set of realistic customer questions against major AI assistants on a schedule, then measure:
  • Did the answer mention your docs?
  • Was your documentation cited?
  • Which pages were referenced?
  • Were competitors cited instead?
  • Was the answer accurate?

A typical B2B technical-docs setup looks like:

1. Create a prompt set (e.g., “How do I configure SSO with Product X?”).
2. Run those prompts weekly/monthly across AI assistants.
3. Capture citations and sources.
4. Score:
   • citation share
   • source quality
   • accuracy
   • competitor mentions
   • missing documentation gaps

One important caveat: there is no universal API that tells you “ChatGPT used your docs X times this month.” AI assistants generally do not expose that private usage data. The available tools estimate visibility by testing prompts and monitoring public AI outputs.

If your company has a developer portal/API docs/knowledge base, the most useful approach is usually an AI visibility tracker + automated citation monitoring + your own docs analytics rather than relying on a single tool.

Yes. The category you’re looking for is AI visibility / AI citation tracking (sometimes called AEO/GEO tracking).

For a B2B company with a large technical-docs site, I’d look at these:

• Microsoft Clarity AI Visibility — probably the most directly relevant starting point. Its Citation dashboard shows which pages on your domain are cited in AI-generated answers, citation counts, and the queries associated with those citations. learn.microsoft.com

Microsoft Clarity AI Visibility

• Citations.io — purpose-built AI citation monitoring across ChatGPT, Gemini, Perplexity, and Claude. It lets you see which sources/URLs are cited and compare citation share against competitors. citations.io

Citations.io

• LLM Visibility — tracks prompts across several AI engines and specifically exposes the sources feeding the models, alongside brand visibility and sentiment. llmvisibility.tech

LLM Visibility

For technical docs specifically

I'd distinguish between:

1. "Does AI cite our docs?"
→ Clarity's citation dashboard is unusually close to this use case.

2. "Which AI assistants cite which documentation pages, for which technical questions?"
→ A dedicated AI visibility tracker such as Citations.io/LLM Visibility is likely more useful.

3. "How frequently are AI crawlers actually fetching our docs?"
→ That's a different measurement problem. Server/CDN logs and bot analytics can tell you about crawler activity, but a crawler visiting a page does not mean the page was subsequently cited in an answer.

One important caveat: AI responses are stochastic, so a metric like "our docs were cited 17% of the time" should be based on repeated sampling rather than a handful of prompts. Recent research finds substantial variation in citation results across repeated runs. arxiv.org

If you're evaluating this as a B2B product category, I'd specifically look for a tool that can report:

AI engine → prompt/topic → cited URL → citation frequency → competitor/source cited instead → date

That's much more actionable for a technical-content team than a generic "AI visibility score."

If you tell me roughly how many docs/pages you have and which assistants matter (ChatGPT, Claude, Gemini, Perplexity, etc.), I can narrow this down to the 2–3 best tools for your use case.

If your goal is specifically to understand how often AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.) use your technical documentation as a source, there are a few emerging categories of tools. None provide perfect visibility, because AI assistants don't expose complete citation telemetry, but some are much better than traditional analytics.

Here are the strongest options:

For developer documentation, I'd prioritize:

1. Profound AI – strongest if you want executive-level reporting on how your docs influence AI responses.
2. Scrunch AI – particularly focused on SaaS companies with technical documentation.
3. Goodie – useful if your main concern is generative search and documentation discoverability.

If you want first-party measurement

If your docs are hosted on your own site (for example, Docusaurus, Mintlify, ReadMe, or a custom docs portal), you can also measure AI usage directly by combining:

• Web analytics (GA4, Plausible, PostHog)
• Server logs
• AI crawler detection (OpenAI, Anthropic, Google, Perplexity, etc.)
• Referral traffic from AI products
• Structured documentation sitemaps (LLMs.txt and related metadata where supported)

This tells you:

• Which documentation pages AI crawlers access
• Which pages receive visits originating from AI assistants
• Which pages are most likely to be used as grounding material

If you're building a serious AI documentation strategy

Many B2B companies now use a combination of:

• An AI visibility platform (Profound or Scrunch)
• Product analytics (PostHog or Amplitude)
• Search Console
• Traditional SEO tools (Ahrefs or Semrush)
• Documentation analytics (ReadMe, Mintlify Analytics, etc.)

That combination gives both "Was our documentation cited by AI?" and "Did that lead to users visiting or adopting our product?"

If your company publishes API or SDK documentation, I can also recommend tools specifically optimized for tracking citations of developer docs rather than general marketing content.

If your goal is measuring how often AI assistants (ChatGPT, Claude, Gemini, Perplexity, Copilot, etc.) cite or rely on your documentation, there isn't yet a single universal analytics platform because most AI assistants don't expose referral logs. Instead, companies typically combine a few types of tools.

The strongest options are:

For a B2B SaaS company with technical documentation, I'd also recommend instrumenting your docs themselves:

• Add server-side analytics to every documentation page.
• Track requests from AI crawlers such as:
  • OpenAI's GPTBot
  • Anthropic's ClaudeBot
  • PerplexityBot
  • Google-Extended
  • Bytespider (where relevant)
• Monitor whether llms.txt and structured documentation are being fetched.
• Use log analysis (Cloudflare, Fastly, Datadog, etc.) to see which documentation pages AI crawlers access most frequently.

It's important to distinguish two different metrics:

1. Crawler activity ("AI models read this page")
   • Measured from your web logs.
   • Doesn't prove the content was later used in responses.

2. Citation activity ("AI assistants referenced this page in an answer")
   • Measured by platforms like Profound or Scrunch AI.
   • This is the closest available metric to "our docs influenced AI answers."

If you're a developer platform

The most useful KPI dashboard usually includes:

• % of benchmark prompts where your company is mentioned
• % where your documentation is cited
• Which documentation pages are cited most
• Missing topics competitors are cited for
• Citation trend over time
• Share of voice versus competitors
• AI crawler traffic to docs

This combination gives both leading indicators (crawler access) and outcome metrics (actual AI citations).

If you're evaluating vendors today, Profound is generally regarded as the most mature enterprise platform for AI answer visibility, while Scrunch AI is particularly strong for technical documentation and developer-focused content.

If your goal is specifically measuring how often AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.) use your documentation as a source, you're looking for an emerging category often called AI visibility, LLM analytics, or Generative Engine Optimization (GEO).

Some of the better-known tools include:

If your company publishes technical documentation

The most useful metrics are usually:

• How often your docs are cited by AI assistants
• Which pages are cited most frequently
• Which competitors are cited instead
• The prompts that surface your documentation
• Citation share by model (ChatGPT vs Claude vs Gemini vs Perplexity)
• Changes in visibility over time

Some enterprise platforms also identify which exact documentation URL was referenced and whether the model quoted it, summarized it, or simply relied on it as a source.

If you're a developer company

If you have API docs or SDK documentation, I'd prioritize:

1. Profound
2. Scrunch AI
3. Peec AI

These tend to focus more on documentation quality, structured content, and technical knowledge rather than only marketing pages.

One important limitation: no external tool can directly observe every internal retrieval or training source used by an AI model. These platforms estimate usage by systematically querying multiple AI assistants at scale, recording responses, detecting citations or referenced URLs, and tracking trends over time. That makes them very useful for competitive benchmarking and optimization, but they don't provide a complete count of every time an AI model relied on your documentation.

If your objective is product analytics (e.g., "How many AI agents are actually reading our docs from our website?"), there are also observability tools that analyze crawler traffic, AI user agents, and retrieval requests—a somewhat different problem from tracking citations in AI-generated answers.

If your goal is specifically "How often do AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.) use our documentation as sources?", you're looking for an emerging category often called AI visibility, LLM analytics, or Generative Engine Optimization (GEO).

Here are the leading options:

If you have technical documentation

For companies with docs hosted on sites like:

• docs.company.com
• developer.company.com
• support.company.com

the better platforms will report metrics such as:

• How often your docs are cited
• Which pages are cited most
• Which AI assistants cite them
• Which prompts trigger citations
• Competitors cited instead of you
• Citation trends over time

This is similar to SEO tools like Ahrefs or Semrush, but for AI assistants.

If you want first-party measurement

Many companies also combine these tools with:

• Web analytics (GA4, Amplitude, Mixpanel)
• Server logs
• Referrer analysis
• AI crawler monitoring (e.g. OpenAI, Anthropic, Google crawler activity)

This won't tell you every time an assistant used your docs internally, but it will tell you when AI systems send traffic back via citations or links.

For a B2B SaaS company

A practical stack is:

• Profound if you're a larger enterprise with a significant budget.
• Scrunch AI if your business depends heavily on technical or developer documentation.
• Goodie if your focus is monitoring visibility across multiple AI assistants.
• Otterly.AI if you're looking for a more affordable way to start measuring AI search presence.

If you tell me:

• roughly how many documentation pages you have,
• whether you're selling to developers or enterprise buyers,
• and whether your docs are public (e.g. Docusaurus, Read the Docs, GitBook, Mintlify),

I can recommend the tool that's likely to provide the best value for your specific setup.

If your goal is specifically "How often do AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.) use our documentation as a source?", you're looking for a relatively new category of products often called LLM visibility, AI search analytics, or Generative Engine Optimization (GEO).

The market is evolving quickly, but here are the main options:

For a B2B company with technical documentation, I'd divide the problem into three layers:

1. AI visibility monitoring
   • Which AI assistants mention your company?
   • Which competitors appear instead?
   • What sources are cited?
   • Which prompts trigger your docs?

2. Documentation analytics
   • Which documentation pages are being crawled by AI bots?
   • Are your docs indexed?
   • Which pages are referenced most often?

3. Traffic attribution
   • How much traffic arrives from ChatGPT, Claude, Gemini, Perplexity, etc.?
   • Which docs lead to product signups?

One important limitation

No tool can see every ChatGPT or Claude response.

Most assistants do not expose complete analytics showing:

• "Your docs were cited 8,243 times this month."

That data isn't available publicly.

Instead, these tools typically:

• run thousands of representative prompts
• check whether your brand appears
• record citations
• monitor changes over time
• compare against competitors

So they're measuring visibility, not every real user conversation.

If your docs are public

If you publish docs like:

• docs.company.com
• developer.company.com
• API reference
• knowledge base

I'd recommend combining:

• an AI visibility platform (Profound or Scrunch AI)
• your web analytics (GA4 or similar)
• server logs to measure AI crawler activity
• Search Console/Bing Webmaster for indexing

Together, those provide a much more complete picture than any single tool.

If you're a developer tools or enterprise SaaS company (for example, API documentation or SDKs), I can also recommend the tools that engineering organizations are using specifically to optimize documentation for LLM citation rather than traditional SEO.