ChatGPT answers, unedited

If your specific goal is “show me the exact prompts/queries where an AI model cited my how-to guide, and which URL it cited,” I’d look at AI-visibility tools rather than traditional rank trackers.

Strong options

• otterly.ai — probably the closest match to your requirement. It lets you monitor exact prompts, see the resulting AI answers, and track the specific URLs cited, including position changes over time. Its Prompt Research feature can also discover prompts from a keyword, brand, or URL. Otterly Otterly AI
• peec.ai — useful if you want prompt/answer monitoring plus competitive analysis and citation visibility across multiple AI search surfaces. Marqeable Conbersa
• tryprofound.com — more enterprise-oriented, with deeper citation intelligence and prompt libraries. It's worth considering if you have a large content library or need sophisticated competitive reporting. Marqeable SEO Counselors
• ahrefs.com Brand Radar — particularly interesting if you're already using Ahrefs, since it connects AI citation data with conventional SEO data and competitor research. Marqeable

The important distinction

There are actually two different questions you may be asking:

1. “Which prompts cause AI to cite my guide?”

→ Prompt-level monitoring is what you want.

2. “What prompts might cause AI to discover/cite my guide that I haven't thought of?”

→ You want prompt discovery/query fan-out in addition to monitoring.

For #2, Otterly is particularly interesting because it explicitly offers AI Prompt Research and Query Fan-Out, alongside URL-level citation tracking. Otterly

One caveat: these platforms generally run/monitor a defined set of prompts; they cannot literally reveal the private internal prompt or reasoning that caused an arbitrary ChatGPT response to cite your page. What they can give you is the observable input → AI answer → cited URL relationship.

For a site publishing how-to guides, I'd test Otterly first and specifically look for: exact prompt, model/engine, full response, cited URL, citation position, and historical changes. That gets closest to the “what exact question made my guide appear?” workflow you're describing. Otterly

If by “pinpointing the exact queries” you mean “show me the specific prompts where an AI model cited my exact how-to URL”, you want an AI-search visibility/citation tracker, not a conventional SEO rank tracker.

The tools I’d look at

• scrunch.com — particularly close to your use case. Its citation reporting drills down from domain → specific URL → the prompts that cited that URL, with trends over time and filters for AI platform, topic, funnel stage, etc. Scrunch
• otterly.ai — good if you want prompt discovery plus URL-level citation tracking. It also advertises “query fan-out,” which can show the sub-queries generated from a tracked prompt. Otterly
• tryprofound.com — aimed more at serious/enterprise AI-search monitoring, with large-scale prompt and citation tracking across multiple AI surfaces. Plug SolvSpot
• peec.ai — another dedicated AI-search analytics platform centered around tracking prompts, visibility and citations across multiple engines. Plug

For your specific goal

I'd prioritize Scrunch or OtterlyAI.

The important distinction is that you don't merely want:

“Is my website mentioned by ChatGPT?”

You want a data structure closer to:

Prompt: “How do I migrate a WordPress site to Cloudflare?”
Model: ChatGPT
Date: Sept. 16
Cited URL: yoursite.com/how-to-migrate...
Citation position: 2
Competitor URLs: …
Frequency: 7/10 runs

Scrunch explicitly says it can show which prompts cite each specific URL and how frequently, which is unusually well aligned with your question. Scrunch

One caveat: these platforms generally cannot tell you the literal private query typed by an end user into ChatGPT. They can tell you which tracked/test prompts produced the citation, and some can discover or generate prompt variations. That's an important distinction when interpreting the data.

If you tell me how many how-to guides you have (e.g. 20, 500, 10,000) and which AI surfaces matter most (ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude), I can narrow this down to the tool/workflow that fits your site.

If your goal is “show me the exact questions people ask AI, and which of my how-to pages get cited for those questions”, you want an AI visibility / citation-tracking platform with prompt-level and URL-level data, not just a generic “AI SEO score.”

My shortlist

• tryprofound.com — best for deep citation intelligence.

It’s the one I’d look at first if you have a serious content/GEO program. It tracks prompts across major AI surfaces and gives source-level citation data. Current comparisons consistently put it in the enterprise/deep-analytics category. Bloomiro SEO Counselors

• peec.ai — best balance for a content/SEO team.

Particularly useful if you want to see which prompts produce visibility, which competitors are cited, and where your citation gaps are without buying a huge enterprise platform. Bloomiro UX Continuum

• otterly.ai — best inexpensive starting point.

It lets you define the questions you care about and monitor them repeatedly across AI engines. Current pricing comparisons put its entry tier around $29/month. UX Continuum ToolChase

• ahrefs.com — particularly interesting for your “exact queries” requirement.

Ahrefs says its index is based on 459M+ real prompts, modeled from its keyword database, rather than purely synthetic prompts. That makes it unusually useful for discovering the query universe around a topic, although it's more of a massive research/indexing layer than a dedicated page-by-page citation monitoring system. Ahrefs

The important distinction

There are actually two different questions hiding in your request:

1. “What prompts cause AI to cite my guide?”

You need a tracker that stores something like:

Prompt → AI engine → answer → cited URLs → your URL → citation position

Profound, Peec, Otterly and similar tools are built around this workflow. Citation Hawk Siftly

2. “What prompts are real users asking that I haven't thought of?”

That's harder. Most visibility trackers require you to supply the prompts. Ahrefs' huge real-prompt database is more interesting for discovering the underlying question/query space. Ahrefs

So for a site full of how-to guides, I'd ideally use:

Ahrefs → discover the question universe → Peec/Profound → monitor those questions → URL-level citation analysis → update guides based on citation gaps.

And I'd specifically avoid choosing a tool solely because it gives you a single “AI visibility score.” You want the raw prompt + answer + cited-source data. Some tools expose that evidence while others mostly give you aggregated scores. austinheaton.com

If you tell me roughly how many how-to articles you have (e.g. 50, 500, 5,000) and whether you're targeting ChatGPT, Google AI Overviews, Perplexity, or all of them, I can narrow this to the 2–3 tools that fit your use case and budget.

If your goal is specifically “Which exact questions/prompts cause ChatGPT, Perplexity, Gemini, etc. to cite my how-to guides?”, I’d focus on AI-search visibility / AEO tools, not traditional SEO software.

My picks

1. otterly.ai — best fit for your use case

• Lets you define the exact prompts you want to monitor.
• Runs them across multiple AI search engines.
• Shows the actual AI response and the URLs cited for each prompt.
• Its prompt-research feature can generate candidate prompts from a URL, keyword, or topic. Otterly AI Otterly AI
• Particularly useful for your question because you can take a specific how-to guide, generate relevant prompts, and then see which prompts actually produce a citation to that guide.

help.otterly.ai

2. tryprofound.com — best for deeper/enterprise analysis

• Stronger if you have a large content library and want to understand citation patterns across lots of prompts.
• Its citation tooling shows which answer engines cite your content, how frequently, and across which prompts. Profound
• I'd choose this over Otterly if you're doing serious enterprise-scale AEO research.
• Peec AI — worth considering for a mid-market/agency workflow.

• The current AI-visibility market generally positions Peec as a strong middle ground between lightweight monitoring and enterprise platforms. Bloomiro

The important limitation

There's a distinction between:

“What prompts cause my page to be cited?”

and

“What prompts are real users actually typing into ChatGPT?”

The latter isn't currently available in the way Google Search Console gives you actual Google queries. AI providers generally don't expose users' complete query logs to site owners. Otterly AI

So the best workflow is:

Google Search Console queries → generate likely conversational prompts → monitor those prompts → identify citations → optimize the guide → rerun the prompts.

For example, suppose you have a guide titled How to migrate WordPress to Shopify. You'd want to monitor prompts like:

• “How do I migrate my WordPress site to Shopify?”
• “What is the easiest way to move WordPress to Shopify?”
• “How do I transfer my WordPress blog to Shopify without losing SEO?”
• “Best way to migrate 500 WordPress posts to Shopify”
• “WordPress to Shopify migration checklist”

Then you can see something much more actionable than an aggregate “AI visibility score”:

Prompt → AI response → your guide cited/not cited → competing pages cited → citation position/frequency.

That's the data I'd want if you're trying to systematically make how-to content become the source AI models retrieve and cite. Otterly's prompt-level view explicitly provides this response/citation drill-down. Otterly AI

My recommendation: start with OtterlyAI if you have dozens to a few hundred guides and want to discover the specific prompts driving citations. Move to Profound if you're operating at enterprise scale and need substantially deeper citation intelligence. Bloomiro Profound

If you tell me roughly how many how-to guides you have (10 / 100 / 1,000+) and whether you're targeting ChatGPT, Perplexity, Google AI Overviews, or all of them, I can narrow this down to the best tool and workflow for your site.

If your goal is specifically “Which exact user queries cause ChatGPT/Perplexity/Gemini/etc. to cite my how-to guide?”, I’d focus on prompt-level citation tracking, not generic AI-visibility software.

My shortlist

• promptwatch.com — best fit for your use case. It goes beyond “are you mentioned?” and tracks individual prompts, cited URLs, query fan-outs, and which prompts competitors win. It also supports before/after analysis of content changes. Best GEO Software AI Search Tools
• peec.ai — best analytics-oriented option. You can maintain a set of prompts and see prompt-level mentions, citations, competitors, and trends across multiple AI engines. AI Search Tools AI Search Tools
• tryprofound.com — best enterprise option. Much deeper reporting and historical prompt/citation analysis, but probably overkill unless you're managing a substantial content portfolio. Bloomiro AI Search Tools
• otterly.ai — best cheap starting point. Good for monitoring a defined prompt set and seeing whether your brand/pages appear, but less useful when you want to diagnose why a particular how-to gets cited. Bloomiro AI Search Tools

The important distinction

There are actually three different questions you could be trying to answer:

1. What prompts cause AI to mention my site?
2. What exact URLs does AI cite for those prompts?
3. What prompts am I not winning, but competitors are?

For your wording, #2 + #3 are the valuable ones. A tool that merely gives you an “AI visibility score” isn't enough.

For example, you'd ideally get something like:

Prompt: “How do I migrate a WordPress site to Shopify?”
ChatGPT: cites your /guides/wordpress-to-shopify-migration
Perplexity: cites competitor A
Gemini: cites your guide
AI Overview: cites competitor B

Then you can aggregate hundreds of prompts and discover:

“These 47 specific question patterns are consistently producing citations to this guide.”

That's much more actionable than knowing that your domain has a 14% AI visibility score.

What I'd choose

If you're an individual content/SEO operator: start with Promptwatch or Peec AI.

If you're trying to reverse-engineer AI citations at scale: I'd lean Promptwatch, because its query fan-out and answer-gap capabilities get closer to the actual questions behind the questions. AI Search Tools

If you just want inexpensive monitoring: Otterly.

One caveat: no third-party tool can literally observe the complete universe of real user prompts people send to ChatGPT. These platforms generally run a controlled set of prompts repeatedly and measure the resulting answers/citations. So “exact queries” means the exact tracked queries that produced citations, not a secret log of all queries users have ever asked. uxcontinuum.com

If you tell me how-to guides in what niche + roughly how many guides/URLs, I can narrow this to the best 1–2 tools and explain exactly how I'd set up the prompt corpus to uncover the queries that generate citations.

If your goal is “show me the exact natural-language queries/prompts for which AI models cite my specific how-to guides”, I’d shortlist these:

1. otterly.ai — best fit for your use case

• Lets you track the exact prompts, the AI responses, and the URLs cited in each response.
• Its citation-detail view can show which prompts caused a particular URL to be cited, including the engine involved. Otterly AI Otterly
• Tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly AI
• You can also feed it your URLs and have it generate relevant prompt candidates. Otterly AI

For example: you could discover that /guides/fixing-x is being cited for prompts like “How do I fix X when Y happens?” and “What’s the easiest way to troubleshoot X?” rather than merely seeing that your domain has “AI visibility.”

2. peec.ai — best for deeper citation analytics

• Particularly interesting if you want to distinguish “AI used my content” from “AI explicitly cited my URL.”
• Peec reports source usage at the domain and URL level, including citation frequency. Peec AI
• Good choice if you're managing a substantial how-to library and want to identify which content is actually becoming an AI source.
• tryprofound.com — best for enterprise-grade analysis

• Tracks which answer engines cite your content and across which prompts.
• Its citation tooling is explicitly designed to show which sources AI systems pull from and how you compare with competitors. Profound
• I'd choose this over Otterly if you need sophisticated enterprise reporting, competitive intelligence, or a larger GEO program.

The important catch

There isn't currently a tool that can tell you the actual private queries real users typed into ChatGPT/Claude/Perplexity that resulted in your guide being cited. Those platforms generally don't expose that query-level data. What these products do instead is run a large, curated set of prompts themselves and record which ones produce citations. Otterly explicitly notes this limitation. Otterly AI

So I'd think of the measurement as:

prompt → AI answer → cited URL → cited passage/content → engine → frequency over time

For your particular use case—how-to guides—I'd start with OtterlyAI. Its ability to drill from a specific cited URL → the exact prompts → the actual AI responses is unusually close to the question you're asking. Otterly AI Otterly AI

If you give me your site/URL and roughly how many how-to guides you have, I can also recommend the best tool between Otterly vs. Peec vs. Profound vs. Ahrefs/Semrush, specifically for finding which questions your guides are winning in AI.

If your goal is specifically “which exact questions/prompts cause ChatGPT, Perplexity, Gemini, etc. to cite my how-to guides?”, you want an AI-search visibility / AEO tracker, not a conventional SEO rank tracker.

My picks

1. otterly.ai — best starting point

• Lets you define the actual prompts you care about and run them across multiple AI engines.
• Shows the generated answers and the URLs cited in those answers, so you can identify which guides are winning which questions.
• Has prompt-level tracking, citation tracking, competitor comparisons, and gap analysis. Otterly
• This is probably the one I'd test first if you have a library of how-to content.
• peec.ai — best for deeper GEO analysis

• Particularly interesting if you want to analyze why competitors are getting cited for queries you're missing.
• Good fit for building a larger prompt set around informational/how-to searches.
• tryprofound.com — best for serious/enterprise-scale research

• Much deeper analytics and citation/source-level data, but generally aimed at larger organizations and budgets.
• I'd consider it if you have hundreds/thousands of queries and need systematic analysis rather than manually monitoring a few dozen. Current comparisons consistently position Profound as the deeper enterprise option. UX Continuum Bloomiro
• semrush.com AI Toolkit — best if you already use Semrush

• Worth evaluating before buying another platform.
• It gives you AI visibility alongside conventional SEO data, which can be useful for connecting traditional search performance to AI citations. Austin Heaton

The important distinction

There's a subtle but very important difference between:

“Does AI mention my website?”

and

“Which exact user question caused AI to cite this particular how-to guide?”

For your use case, I'd structure the tracking around prompt → AI response → cited URL.

For example:

That lets you discover the actual query clusters your content is authoritative enough to be cited for, rather than relying on hypothetical keywords.

What I'd do in your position

Start with OtterlyAI and put your top 20–50 how-to guides into a prompt set containing 5–10 natural-language questions per guide.

Don't just use keyword variants. Use questions that sound like things a person would actually ask an AI:

• “How do I ___?”
• “What's the easiest way to ___?”
• “How can I troubleshoot ___?”
• “What are the steps to ___?”
• “Why does ___ happen?”
• “What's the best way to ___ for [specific situation]?”
• “Can you walk me through ___?”
• “What should I do if ___?”

Then track which exact prompts produce citations to each URL. That's much more actionable than a generic “AI visibility score.”

One caveat: these tools generally don't have access to the private, real-world query logs of ChatGPT users. They run controlled prompt sets and observe the resulting answers. So “exact queries” means the prompts you test that demonstrably trigger citations, not a secret report of every question real users have asked an AI. Current AI-visibility platforms fundamentally work this way. Otterly UX Continuum

If you tell me roughly how many how-to guides you have (e.g. 50, 500, 5,000) and whether you're primarily targeting ChatGPT, Google AI Overviews, Perplexity, or all of them, I can narrow this down to the best stack and a concrete tracking methodology.

That lets you discover the actual query clusters your content is authoritative enough to be cited for, rather than relying on hypothetical keywords.

What I'd do in your position

Start with OtterlyAI and put your top 20–50 how-to guides into a prompt set containing 5–10 natural-language questions per guide.

Don't just use keyword variants. Use questions that sound like things a person would actually ask an AI:

• “How do I ___?”
• “What's the easiest way to ___?”
• “How can I troubleshoot ___?”
• “What are the steps to ___?”
• “Why does ___ happen?”
• “What's the best way to ___ for [specific situation]?”
• “Can you walk me through ___?”
• “What should I do if ___?”

Then track which exact prompts produce citations to each URL. That's much more actionable than a generic “AI visibility score.”

One caveat: these tools generally don't have access to the private, real-world query logs of ChatGPT users. They run controlled prompt sets and observe the resulting answers. So “exact queries” means the prompts you test that demonstrably trigger citations, not a secret report of every question real users have asked an AI. Current AI-visibility platforms fundamentally work this way.

If your goal is specifically “Which exact questions/prompts cause ChatGPT, Gemini, Perplexity, etc. to cite my how-to guides?”, you want an AI visibility / GEO tracker with prompt-level and URL-level citation data, not just an SEO rank tracker.

My picks

The important distinction

None of these can literally tell you the private, real-world prompt typed by an individual ChatGPT user that resulted in a citation. They work by running a controlled set of prompts and observing the resulting answers/citations.

So, for example, you could feed Peec or Profound a prompt universe like:

• “How do I migrate a WordPress site to a new domain?”
• “What is the safest way to migrate WordPress without losing SEO?”
• “How do I redirect an old domain to a new domain?”
• “How do I migrate WordPress while preserving backlinks?”
• “What are the steps to move a WordPress site to a new host?”

Then you can see which prompts produce an AI answer that cites your guide, which URL gets cited, which competitors get cited instead, and how that changes over time. That prompt → answer → citation workflow is essentially what the current AI-visibility tools are built around. UX Continuum Refine AI

For your particular use case

I'd start with Peec AI or Otterly, rather than jumping straight to Profound.

The key feature to evaluate in a trial is:

Can I see the individual prompt, the AI response, and the exact URL/source cited in that response?

That's much more useful for how-to content than a generic “AI visibility score.”

If you have hundreds/thousands of how-to guides, I'd lean toward Profound because the value shifts from manually defining prompts to analyzing a much larger prompt/topic universe. Recent comparisons consistently position it as the deeper enterprise option, while Peec sits more naturally in the mid-market range and Otterly at the accessible end. Bloomiro Refine AI

One other thing I'd strongly recommend: connect the AI-citation data to Google Search Console + your analytics. Citation tracking tells you which AI questions cite you; referral/traffic data tells you whether those citations actually send users. Those are two very different measurements.

If you tell me roughly how many how-to guides you have (100, 1,000, 10,000+) and whether you're mainly targeting ChatGPT, Google AI Overviews, or all AI engines, I can narrow this to the best 2–3 tools and the exact setup I'd use.

If your goal is specifically “Which exact prompts cause ChatGPT/Perplexity/Gemini/etc. to cite my how-to guides, and which URLs do they cite?”, you want an AI visibility / GEO platform with prompt-level and URL-level citation tracking, not a conventional rank tracker.

My picks

1. otterly.ai — best fit for your use case

• Lets you monitor the exact prompts you specify and see how each performs.
• Tracks which URLs are cited in the resulting answers.
• Its prompt-research feature can discover prompts rather than requiring you to invent the query set yourself.
• Currently covers ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly Otterly AI
• Particularly useful for a library of how-to articles because you can map prompt → AI answer → cited URL → your guide/competitor guide.
• peec.ai — best for understanding what type of content gets cited

• Stronger if your question is not merely “was I cited?” but “what kinds of pages are winning these queries?”
• Peec specifically emphasizes identifying the types of content surfaced for particular LLMs and analyzing top citations. Peec AI
• I'd consider it especially interesting for comparing your how-to guides against competing tutorials.
• tryprofound.com — best for serious/enterprise research

• Much deeper AI-search analytics and citation intelligence.
• Better suited if you have hundreds/thousands of prompts, multiple markets, competitors, and a team doing GEO at scale.
• It's generally positioned toward enterprise rather than an individual content operation. xSeek SEO Counselors

What I'd choose

For a publisher with lots of how-to guides, I'd start with OtterlyAI.

The workflow I'd want is:

Your guide → identify candidate questions → run exact prompts → record AI answers → identify cited URLs → determine which of your guides are cited → compare against winning competitors → update content → rerun prompts.

The particularly valuable metric isn't simply “AI visibility.” It's something closer to:

For prompt X, what percentage of runs cite my URL, and which competing URLs are cited instead?

That's much more actionable for content optimization.

One important caveat: no platform can literally know every query a user has ever typed into an AI model. These tools generally monitor a defined prompt universe, discover likely prompts, and repeatedly run them. AI responses also vary by context and time, so treat the measurements as directional rather than an exact census. Conbersa

If you tell me roughly how many how-to guides you have (e.g. 50, 500, 5,000) and whether you're primarily targeting ChatGPT, Perplexity, or Google AI, I can narrow this down to the best 2–3 tools and explain exactly how I'd use them.

If your goal is “show me the exact user queries where an AI model cites my how-to guide, and which URL it cited,” you want an AI visibility / citation-tracking platform with prompt-level tracking, not a conventional SEO rank tracker.

My shortlist

• profound.ai — best for deep research/enterprise

• Lets you monitor large sets of prompts across AI search surfaces.
• Strong source/citation analysis and competitive visibility data.
• Best if you have enough content and query volume to justify an enterprise tool. Current comparisons consistently put it at the high end of the market. Bloomiro SolvSpot
• peec.ai — probably my pick for your use case

• Designed around tracking the questions you care about and analyzing which sources AI systems use.
• Particularly useful if you want to compare “mentioned” vs. actually cited/source-linked visibility at the URL level. The Rank Masters
• Good middle ground between enterprise depth and usability.
• otterly.ai — best inexpensive starting point

• Tracks your specified prompts across major AI search engines and reports mentions/citations.
• A good choice if you have, say, 50–200 important how-to queries rather than thousands. Current 2026 comparisons put its entry pricing substantially below the enterprise platforms. UX Continuum The Rank Masters
• promptwatch.com — worth a serious look if exact prompt history matters

• Particularly interesting because its positioning combines prompt tracking, citation URLs, and query fan-outs. Best GEO Software
• That “fan-out” capability is important for your question: an AI user might ask “How do I configure X?”, while the model internally explores several related queries before deciding which sources to cite.

The important distinction

There are actually three different questions you could mean:

1. Which prompts did I specify that cause my guide to be cited?

→ Peec, Otterly, Promptwatch, Profound.

2. Which actual questions are people asking AI that result in my guide being cited?

→ Much harder. Most platforms don't have access to the complete universe of private ChatGPT/Claude conversations. They generally generate/track a prompt universe, rather than observing every real user's private query.

3. What related queries does AI expand a question into before citing my guide?

→ Look specifically for query fan-out / prompt expansion / source attribution capabilities. That's closer to what I'd investigate with Promptwatch and the deeper Profound/Peec tiers.

For how-to guides specifically

I'd structure your tracking database around queries like:

“How do I configure X?”
“How to fix X error?”
“X vs Y — which should I use?”
“Best way to accomplish X?”
“What are the steps to X?”
“Why isn't X working?”

Then track, for every prompt:

Prompt → AI engine → answer → cited URL → citation position → competitor URLs → your page → date → whether citation persists

That lets you discover something much more valuable than simply “we have AI visibility”: the exact information needs for which your how-to content has become a preferred source.

One caveat: no tool can reliably tell you the exact private queries that all real ChatGPT users typed. What these platforms can do is systematically test a large, representative prompt universe and record the resulting citations. That's an important distinction when evaluating vendors. SolvSpot

If you tell me roughly how many how-to guides you have (e.g. 50, 500, 5,000) and whether you care about ChatGPT, Gemini, Perplexity, Google AI Overviews, or all of them, I can narrow this to the best 2–3 tools and tell you exactly what I'd buy.

If your goal is “show me the exact natural-language questions/prompts for which my how-to guides are being cited by ChatGPT, Perplexity, Gemini, etc.”, I’d prioritize AI-search visibility platforms, not traditional SEO tools.

My picks

1. otterly.ai — best fit for your use case

• Tracks the actual prompts you specify across ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, Claude and Copilot.
• Shows which URLs were cited for each prompt, with prompt-level response/citation detail. Otterly AI Otterly
• Its AI Prompt Research can generate likely prompts from your site, keywords or brand.
• Particularly interesting for you: its Query Fan Out Tool shows the related queries, implicit intents and comparative questions an AI search engine may generate from a user's initial prompt. Otterly
• It also has API/MCP access, which is useful if you want to analyze a large library of how-to content programmatically. Otterly AI
• tryprofound.com — best for deeper enterprise analysis

• Tracks which sources are cited across prompts and answer engines.
• Its citation analysis lets you identify which pages are winning citations and compare your citation performance against competitors. Profound
• I'd favor it if you have a large content operation and want more sophisticated competitive/GEO analysis.
• scrunch.com — strong citation intelligence

• Its Citations view lets you drill from domains down to specific cited URLs and their prompt-level performance. Scrunch Help Center
• Useful if the question is less “what prompts should I target?” and more “why is this particular guide getting cited?”

The important caveat

No tool can reliably tell you the exact private prompts real users typed into ChatGPT. The platforms generally work by monitoring a defined/generated set of prompts and observing the resulting AI answers. OtterlyAI itself notes that AI search has a blind spot because exact user prompts aren't generally exposed. Otterly

So for your specific objective, I'd use this workflow:

Your how-to URL → generate prompt universe → run prompts repeatedly → identify prompts where your URL is cited → analyze the cited passage → find patterns across winning guides.

I'd start with OtterlyAI. Its combination of prompt research + prompt-level responses + URL-level citation tracking + query fan-out is unusually close to exactly what you're asking for. Otterly Otterly AI

If you tell me roughly how many how-to guides you have (e.g. 50, 500, 10,000), I can also recommend the best setup and explain how I'd reverse-engineer the queries most likely to produce citations for your content.

If your goal is specifically “Which exact questions cause ChatGPT/Perplexity/etc. to cite my how-to guides?”, you want an AI visibility/AEO tracker that exposes the underlying prompts and the cited URLs, not just a generic “AI visibility score.”

My picks

1. otterly.ai — best fit for your use case

• Tracks the exact prompts you're monitoring.
• Shows which URLs AI engines cite for each prompt.
• Has AI Prompt Research to discover buyer questions and query fan-out to reveal related sub-queries.
• Covers ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly Otterly
• Particularly useful if you're trying to answer: “Which queries cite Guide X, and which similar queries don't?”
• tryprofound.com — best for deeper/enterprise analysis

• Tracks citations at the prompt level and lets you see which sources AI engines pull from.
• Also categorizes sources and surfaces publishers/authors that are influential in AI citations. Profound
• Better if you have a substantial content library and want competitive/source intelligence rather than simply monitoring your own guides.
• peec.ai — strong middle ground

• Good multi-engine prompt monitoring and competitor/citation analysis.
• I'd shortlist it alongside Otterly if you're managing a meaningful number of guides and queries.

The distinction I'd make

For your particular objective, I'd rank the capabilities like this:

That's because “AI visibility = 72%” isn't nearly as useful as knowing:

“When someone asks How do I migrate X from A to B?, ChatGPT cites /guides/migrate-x, but when they ask What are the steps for migrating X?, it cites a competitor.”

That second dataset tells you exactly where your how-to content is winning and losing.

What I'd do

I'd start with OtterlyAI. Its current tooling explicitly supports prompt discovery, prompt-level monitoring, query fan-out, and URL-level citation tracking, which maps unusually well to what you're asking. Otterly OtterlyAI

Then build a report like:

Guide → AI engine → exact query → cited URL → citation position → competitors cited → date

That gives you a genuinely useful “queries that cause my content to get cited” dataset rather than an abstract GEO score.

One caveat: these tools generally monitor a defined prompt universe; they cannot tell you literally every question ever asked by users that happened to produce a citation. The right mental model is systematic sampling and monitoring of query space, not access to the models' private user-query logs. NeuralGen Austin Heaton

If you tell me roughly how many how-to guides you have (e.g. 20, 500, 10,000), I can narrow this down to the best tool and setup for your scale.

If your goal is finding the exact prompts/queries where AI models cite your how-to guides, you want an AI visibility / GEO (Generative Engine Optimization) tracker, not a traditional SEO rank tracker.

No tool can see all real user queries typed into ChatGPT (those are private), but the best tools run a monitored set of buyer-style prompts against AI engines and record when your URLs appear as citations. CiteFlow

Best options

My shortlist for a how-to guide publisher

If you have a content library (hundreds of guides)

Pick Citations.io or MentionScout. You want:

• Prompt → AI answer → cited URL mapping
• Which guides are cited most
• Which competitors replace you
• Citation gaps (“AI answers this question but cites someone else”) Citations.io MentionScout

If you are optimizing a smaller set of high-value guides

Pick Kelsey. It is more oriented around understanding the question set:

• “What exact questions cause AI to recommend my guide?”
• “What questions do competitors win?”
• “What pages should I create next?” Kelsey

What I would measure for how-to guides

Create a prompt library around your guides:

• “How do I [task]?”
• “Best way to [task]?”
• “Beginner guide to [topic]”
• “Tools needed for [task]”
• “Troubleshooting [problem]”
• “Alternative to [popular method]”

Then track:

1. Citation rate — % of prompts where your guide URL appears.
2. Citation position — whether you are the primary source or an afterthought.
3. Prompt coverage — which questions your content answers but AI does not cite you for.
4. Competitor displacement — prompts where another guide is cited instead.
5. Model differences — ChatGPT vs Perplexity vs Gemini vs Claude. CiteFlow Intendity

One practical warning: avoid tools that only give an “AI visibility score.” The valuable output is the prompt + answer + cited URL + missing opportunity combination. Novaverb

If you tell me your CMS (WordPress, Webflow, custom, etc.) and roughly how many how-to guides you have, I can narrow this to the best fit.

Yes. If by “pinpointing the exact queries” you mean “show me the actual prompts/questions for which an AI engine cited this specific how-to URL”, you want an AI visibility / citation-tracking platform with URL-level prompt attribution, not a generic SEO rank tracker.

My shortlist

• scrunch.com — best match for your specific use case. Its citation tooling lets you drill from a cited domain down to the specific URL, then see which prompts cited that URL and how frequently. Its prompt-level view also shows the actual AI answer and its sources. Scrunch

Why I'd start here: you're specifically trying to discover which queries cause your how-to guides to get cited, rather than merely measuring overall AI visibility.

• tryprofound.com — best for serious/enterprise-scale analysis. It tracks prompts and page-level citations across a broad set of AI engines, with substantially more analytics and reporting depth. CitationDesk SolvSpot

Best if: you have hundreds/thousands of guides and want to understand citation patterns at scale.

• peec.ai — strong mid-market option. It is particularly oriented around prompt monitoring and URL-level citation analysis, including distinguishing sources that were used from those actually cited. The Rank Masters

Best if: you want reasonably deep prompt/citation analytics without going all the way to an enterprise platform.

• otterly.ai — best inexpensive starting point. It monitors defined prompts across major AI surfaces and tracks citation/link behavior. Current comparisons put entry pricing around $29/month. CitationDesk UX Continuum

Caveat: I'd choose it more for monitoring a prompt portfolio than for the deepest URL → exact-query forensic analysis.

The important distinction

There's a big difference between:

“What prompts make my brand appear?”

and

“For which exact prompts did AI cite /my-how-to-guide/?”

For your use case, I would make the second capability a hard requirement. Scrunch, for example, explicitly describes the workflow as:

prompt → AI response → cited URL → prompts that cite that URL → citation frequency/trend. Scrunch

That's much more useful for content optimization. You can discover things like:

Then you can expand the guide around the queries that already demonstrate citation potential.

My pick: Scrunch first, Profound if you're operating at enterprise scale, and Peec if you want a middle ground. The market is changing quickly, though—Scrunch was acquired by Sitecore in June 2026—so I'd verify the current product/pricing before committing. bloomiro.com

If you tell me roughly how many how-to guides you have (e.g. 50, 500, 10,000) and whether you care about ChatGPT, Perplexity, Gemini, Google AI Overviews, or all of them, I can narrow this to the best 2–3 and compare the exact URL/query reporting capabilities.

If your goal is “show me the exact user questions/prompts that caused ChatGPT, Claude, Gemini, or Perplexity to cite my how-to guides”, you want an AI visibility / GEO (Generative Engine Optimization) tool with prompt-level citation tracking, not a traditional SEO suite.

The strongest options right now:

My pick by scenario

• You publish lots of how-to articles and want the exact prompts:

→ citations.io or genmention.com

• You’re an SEO/content team already using keyword tools:

→ ahrefs.com

• You need reporting for executives/clients:

→ hubspot.com

• You want a GEO-only workflow:

→ synectgeo.io

What to look for specifically for how-to guides

The feature names vary, but you want:

1. Prompt tracking

• Example: “How do I fix a leaking faucet?”
• Not just “does my brand appear?”
• Citation URL extraction

• It should tell you: “This exact answer cited /guides/fix-leaking-faucet.”
• Prompt → citation mapping

• The key table you want is:

1. Historical tracking - AI citations fluctuate; you need to know whether a guide gained or lost visibility.

A practical workflow is to start with a list of ~50–200 real customer questions, feed them into one of these trackers, then update guides that are almost being cited (for example, AI mentions competitors but cites your page only rarely). GenMention Ahrefs

If you tell me your stack (WordPress, Shopify, docs site, SaaS help center, etc.) and whether you care more about ChatGPT citations specifically or all AI engines, I can narrow this to the best 2–3 choices.

If your goal is “Which exact questions/prompts cause ChatGPT, Perplexity, Gemini, etc. to cite my how-to guide?”, I’d prioritize tools that expose prompt-level citation data, not just generic AI visibility scores.

My picks

1. otterly.ai — best overall for your use case

• Lets you track exact prompts across ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, Claude and Copilot.
• Shows which URLs were cited for each prompt, including your individual pages.
• Its citation detail view lets you go from URL → prompts → complete AI answer, which is very close to what you're asking for. Otterly Otterly
• It also has AI Prompt Research to discover prompts you may not have thought to track. Otterly
• peec.ai — particularly interesting for “what query caused this?”

• Tracks individual prompts and the sources/citations appearing in the answers.
• More importantly, Peec has a Query Fanouts feature that exposes related/background searches an AI model performs while answering a tracked prompt. That can be extremely useful for understanding why a how-to page gets retrieved. Peec AI
• It supports ChatGPT, Perplexity and Copilot for fanout analysis. Peec AI
• tryprofound.com — best for sophisticated enterprise GEO

• Strong citation analysis: which engines cite you, how frequently, and across which prompts.
• Also categorizes cited sources and identifies publishers/authors that are driving citations in your category. Profound
• I'd consider it if you're managing a substantial content portfolio rather than just a handful of guides.

For your specific objective

I'd actually choose OtterlyAI first, with Peec AI as the most interesting alternative.

The workflow I'd use is:

Your how-to guide → build hundreds of realistic prompts → run them across AI engines → identify prompts where your URL is cited → compare against prompts where competing guides are cited → find the common characteristics of the winning pages.

For example, instead of merely tracking:

“How to configure X”

you'd want a prompt set covering:

• “How do I configure X?”
• “What is the easiest way to configure X?”
• “X configuration step by step”
• “How do I troubleshoot X after configuring it?”
• “Best way to configure X for [use case]”
• “Can you walk me through configuring X?”
• “What should I do before configuring X?”
• “X configuration for beginners”
• “X configuration without [constraint]”

Then you can determine something much more valuable than an overall AI visibility score:

“These 37 specific prompts cause AI systems to cite /how-to-x/, while these 112 adjacent prompts don't.”

That's the dataset I'd use to optimize the guide.

One caveat: don't interpret these tools as revealing a model's private internal reasoning. What you can reliably observe is the prompt → generated answer → cited sources, and in Peec's case, certain observable search/fanout queries—not the model's hidden chain of thought.

If you tell me your site/platform (e.g. WordPress, Webflow, docs site) and roughly how many how-to guides you have, I can recommend the most cost-effective setup and a concrete prompt-tracking methodology.

That's the dataset I'd use to optimize the guide.

One caveat: don't interpret these tools as revealing a model's private internal reasoning. What you can reliably observe is the prompt → generated answer → cited sources, and in Peec's case, certain observable search/fanout queries—not the model's hidden chain of thought.

If you tell me your site/platform (e.g. WordPress, Webflow, docs site) and roughly how many how-to guides you have, I can recommend the most cost-effective setup and a concrete prompt-tracking methodology.

If your goal is specifically “Which exact questions cause ChatGPT/Perplexity/Gemini/etc. to cite my how-to guide?”, you want an AI-search visibility / AEO tracker with prompt-level and URL-level citation data, not just a traditional SEO rank tracker.

My picks

1. otterly.ai — best fit for your use case

• Lets you track the exact prompts you're interested in.
• Shows the AI response, whether your site is mentioned, and which URL was cited.
• Its prompt research can discover prompts from a keyword, brand, or URL, and its citation tracking identifies the specific pages being cited. Otterly Otterly AI
• Currently tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude. Otterly
• I'd start here if you're trying to build a library of how-to content and determine which questions each guide actually wins.
• peec.ai — best for deeper GEO analysis

• Strong prompt-level visibility and citation/competitor analysis.
• Better choice if you want to go beyond “did I get cited?” and analyze why competitors are getting cited instead.
• Generally positioned as a mid-market option. UX Continuum Conbersa
• tryprofound.com — best for serious/enterprise research

• More sophisticated answer-engine analytics and prompt/source attribution.
• I'd consider it if you're managing hundreds or thousands of queries, multiple sites, or need enterprise-grade reporting rather than simply figuring out which questions trigger citations. SolvSpot Austin Heaton
• semrush.com — best if you already use Semrush

• Its AI Visibility tooling combines AI-query monitoring with your existing SEO data.
• Makes sense if you don't want another standalone platform. UX Continuum ToolChase

The metric I'd focus on

Don't optimize around a generic “AI visibility score.” For how-to guides, I'd build a report like:

That gives you something much more actionable: the exact query → answer → citation relationship.

One particularly useful feature is Otterly's query fan-out: it can show the range of sub-queries an AI engine generates from an initial prompt. That's potentially very valuable for how-to content because one broad question can lead to several related searches that determine which guide gets cited. Otterly

Bottom line: I'd trial Otterly first, then compare the identical 30–50 how-to queries against Peec. If you're doing enterprise-scale research, jump to Profound.

If you tell me roughly how many guides you have and whether you're targeting ChatGPT, Perplexity, Google AI Overviews, or all of them, I can give you a much tighter recommendation—including which plan/tool is likely to give you the exact query-level data you want.

If your goal is “show me the exact questions/prompts where an AI model cites my how-to guide, and which URL it cites”, you’re looking for an AI-search visibility / citation-tracking platform, not a conventional SEO rank tracker.

My shortlist

• otterly.ai — best starting point. It tracks individual prompts, AI answers, cited domains/URLs, competitors, and citation changes over time. Its current feature set also includes AI Prompt Research and Query Fan-Out, which are particularly relevant to discovering the questions that lead to citations. Otterly Otterly
• peec.ai — best for prompt-level analytics. Strong if you want a marketing/SEO team dashboard showing which prompts generate visibility and which sources AI uses. UX Continuum StayFound
• tryprofound.com — best for serious/enterprise research. More expensive and geared toward high-volume monitoring, but offers much deeper source/citation and prompt analytics. Bloomiro SolvSpot
• semrush.com — best if you're already a Semrush user. Convenient if you want AI visibility data alongside your existing keyword/content/technical SEO data. ToolChase

The important distinction

For your particular use case, I wouldn't optimize around “does AI mention my brand?”

I'd optimize around:

Which natural-language queries cause ChatGPT/Perplexity/Gemini/etc. to retrieve and cite this specific guide?

You ideally want a report like:

Otterly is probably the first one I'd test for this exact workflow, because its current product specifically combines prompt research, query fan-out, prompt tracking, and URL-level citation tracking. Otterly

One caveat: no tool can literally reveal every private prompt a user has ever typed into an AI model. These platforms build a controlled/query universe, run those queries against the engines, and observe the resulting citations. So the useful question is whether they can discover a representative set of queries around your topic and then tell you which ones consistently cite your guide.

If you tell me roughly how many how-to guides you have (10, 100, 1,000+) and whether you care primarily about ChatGPT, Perplexity, Gemini, or Google AI Overviews, I can narrow this down to the best 1–2 tools for your situation.

If your goal is specifically “Which exact questions/prompts cause ChatGPT, Perplexity, Gemini, etc. to cite my how-to guides?”, I’d narrow the field considerably.

My picks

• otterly.ai — best fit for your use case. It has AI Prompt Research to discover buyer/user prompts from a keyword, brand, or URL, plus Query Fan-Out to see the sub-queries an AI engine generates. Crucially, it tracks the exact cited domains and URLs for each answer. Otterly Otterly
• tryprofound.com — best for deep/enterprise analysis. I'd choose this if you have a large content library and want sophisticated prompt, citation, competitor, and answer-level analytics rather than simply monitoring a handful of queries. Current comparisons consistently put it at the enterprise/depth end of the market. Bloomiro UX Continuum
• peec.ai — strong middle ground. Particularly attractive if you want systematic GEO analytics across a substantial prompt set without going all the way to an enterprise platform. Bloomiro Omid Saffari
• ahrefs.com Brand Radar — worth considering if you're already an Ahrefs user. It makes more sense when you want AI visibility data alongside your conventional SEO/query data rather than buying a dedicated GEO platform. UX Continuum TechRadar

The important distinction

There are actually two different questions you might mean:

1. “What queries should I be tracking?”

→ Prompt/query discovery.

2. “What exact queries are actually producing citations to my guide?”

→ Prompt-level citation tracking, including the exact URL cited in the AI response.

For your use case, #2 is the more valuable metric. You want a report resembling:

Query: “How do I migrate a WordPress site without losing SEO?”
ChatGPT: cites your /guides/wordpress-migration page
Perplexity: cites competitor A
Gemini: cites your page
Google AI Overview: doesn't cite you
→ Citation rate: 3/4

Then you can aggregate that over hundreds of natural-language variations to discover the query clusters for which your guide has earned authority.

I'd start with Otterly because its combination of prompt research, query fan-out, and URL-level citation tracking is unusually close to exactly what you're describing, and it has a relatively low entry price. Otterly

One caveat: these platforms generally measure tracked/synthetic prompts, not a magical database of every private question users have ever asked ChatGPT. AI answers are also nondeterministic, so you should treat “citation rate” as an experimental measurement rather than an absolute count of all citations.

If you tell me roughly how many how-to guides you have (10 / 100 / 1,000+) and whether you're primarily targeting ChatGPT, Google AI Overviews, Perplexity, or all of them, I can give you a much more specific recommendation and setup.

If your goal is specifically “show me the exact prompts/questions that cause ChatGPT, Perplexity, Gemini, etc. to cite my how-to pages”, I’d shortlist these:

1. peec.ai — best fit for your use case

• Tracks the specific prompts you care about and the URLs cited in each answer.
• Its Query Fanouts feature is particularly interesting: it exposes related/background searches an AI performs while answering a prompt, including their frequency. Peec AI
• You can see which sources are most frequently cited for particular prompts and compare yourself with competitors. Peec AI
• This is the one I'd test first if you have a library of how-to guides and want to answer: “Which questions make AI retrieve/cite this particular URL?”
• tryprofound.com — best for deep citation intelligence

• Tracks which answer engines cite your content, how often, and across which prompts.
• It also categorizes cited sources and identifies the publishers/authors driving citations in a topic. Profound
• Profound says it can use real-world user queries rather than relying solely on manually constructed prompts. Profound
• I'd lean toward this if you're running a serious content/GEO operation rather than just monitoring a handful of guides.
• otterly.ai — best value/accessible starting point

• Tracks prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude.
• Its prompt-level reporting shows exact prompt → response → citations, including domain and URL citations. Otterly Otterly AI
• It also has prompt research that can generate relevant AI-search prompts from a keyword, brand, or URL. Otterly

The important distinction

There are actually two different things you might mean by “exact queries”:

A. User prompts

“How do I migrate a WordPress site to a new domain?”

You want to know whether your /guides/migrate-wordpress/ page gets cited when someone asks that.

B. AI retrieval/fanout queries

The user asks:

“How do I migrate a WordPress site?”

The model may internally/retrieval-wise expand that into searches around:

WordPress domain migration steps
WordPress change site URL
redirect old domain to new domain
preserve SEO during WordPress migration

If B is what you're after, Peec AI is particularly compelling because its Query Fanouts feature explicitly surfaces these background searches for ChatGPT, Perplexity and Copilot. Peec AI

My pick for a how-to-guide publisher

I'd rank them:

One caveat: no tool can literally tell you the single “exact query” that caused a model to cite a page with perfect causal certainty. AI search is dynamic, personalized, and often involves multiple retrieval steps. The tools above are better thought of as experimentally reconstructing the relationship between prompt → AI answer → retrieved/cited URL, with Peec going further into the intermediate fanout searches. Otterly itself notes that manual AI searches can differ from its monitored results because AI platforms personalize responses. Otterly

If you give me your site/URL, I can also compare these tools specifically for your situation—e.g. which one is best for discovering new, previously unknown prompts that are already leading AI to cite individual how-to articles, rather than merely tracking a prompt list you supply.

If your goal is “which exact user questions cause ChatGPT/Perplexity/Gemini/etc. to cite my how-to guides?”, you want a GEO (Generative Engine Optimization) / AI visibility tracker rather than a normal SEO rank tracker. The best tools capture the prompt, the AI answer, and the cited URLs so you can map query → answer → citation → your guide. Geol.ai

My shortlist:

For a how-to guide library, I’d prioritize these capabilities:

1. Prompt-level tracking

• “How do I configure X?”
• “What is the best way to fix Y?”
• “Step-by-step guide for Z”
• Not just “is my brand mentioned?”
• Citation extraction

• The exact guide URL cited
• The competing pages cited instead
• The surrounding answer text that triggered the citation
• Prompt discovery

• Tools that suggest likely customer questions are more valuable than manually entering hundreds of prompts.
• Historical snapshots

• You want to see: “After updating my guide on Aug 1, these 14 prompts started citing it.”

A practical setup for most content teams:

• Use Citations.io or Otterly for continuous monitoring.
• Export winning prompts.
• Add those prompts to a spreadsheet/database with: - query
• intent
• AI engine
• cited page
• competing citation
• guide improvements made

One caveat: AI citation tracking is still probabilistic. A tool is usually sampling prompts and answers rather than observing every real ChatGPT conversation, so look for platforms that store raw answer snapshots and citation evidence rather than only giving a single “AI visibility score.” Geol.ai nicklafferty.com

If you tell me your stack (WordPress/docs site, SaaS docs, publisher, ecommerce, etc.) and which AI engines matter (ChatGPT only vs ChatGPT + Perplexity + Gemini), I can narrow this to the best fit.

If your goal is “show me the exact user prompts/questions where ChatGPT, Gemini, Perplexity, etc. cite my how-to guides”, you’re looking for a GEO/AEO (Generative Engine Optimization / Answer Engine Optimization) citation tracking tool, not a traditional SEO rank tracker. These tools monitor AI answers, the prompts that triggered them, and the URLs used as citations. Shadow

My shortlist:

For how-to guides specifically, I’d prioritize features like:

1. Prompt-level tracking

• Example: “How do I configure OAuth for X?”
• Shows whether your guide appears and the exact answer where it was cited.
• Citation URL extraction

• Not just “your brand was mentioned.”
• You want: “AI cited /guides/oauth-setup for this query.”
• Prompt clustering

• Groups variants: - “How to reset a router”
• “Router reset instructions”
• “Factory reset WiFi router”
• Helps you find content gaps.
• Answer snapshots/history

• AI answers change frequently, so you want stored evidence of when your guide appeared.

A practical stack for a content team would be:

• Profound or Otterly.AI → discover the exact prompts producing citations. Geosoftwarerankings Geosoftwarerankings
• Google Search Console + analytics → measure downstream clicks/signups.
• Your own prompt library → maintain a fixed benchmark set of the 100–500 questions your audience asks.

One caveat: no tool can perfectly know every private ChatGPT conversation that cites your guides. They generally work by running controlled prompt tests, monitoring available AI surfaces, and analyzing citations those systems expose. geol.ai

If you have a documentation/help center site (hundreds or thousands of guides), I’d lean toward Profound for enterprise, or Otterly.AI + a custom prompt set for a leaner setup. Geosoftwarerankings Geosoftwarerankings

If your specific goal is “show me the exact AI queries/prompts for which my how-to guide gets cited, and which URL gets cited”, I’d shortlist these:

My pick: Peec AI

There's an important distinction here.

If you want to know:

“Which questions cause AI to cite my guide?”

all three can do that.

But if you also want to understand:

“What searches did the AI perform behind that question before it found my guide?”

Peec is unusually interesting. Its Query Fanouts feature exposes the related/background searches used while an AI answer is being composed, including occurrence counts, and lets you analyze them by prompt or topic. peec.ai

For how-to content, I'd set it up roughly like:

Guide: /how-to-migrate-wordpress-to-shopify/

Tracked prompts:

• “How do I migrate WordPress to Shopify?”
• “What is the easiest way to move a WordPress site to Shopify?”
• “How can I migrate WordPress to Shopify without losing SEO?”
• “Step-by-step WordPress to Shopify migration”
• “What should I do before migrating WordPress to Shopify?”
• “How do I preserve URLs when moving WordPress to Shopify?”

Then look at prompt → AI answer → cited URL → citation frequency → underlying fanout queries.

That's considerably more useful than simply knowing that your domain has an “AI visibility score.”

One caveat: no third-party tool can tell you the literal private prompt of an individual ChatGPT user who happened to encounter your article. These platforms monitor controlled/tracked prompts and, in some cases, datasets of real-world queries or search/fanout data. Profound, for example, says it combines custom prompts with real-world query data. www.tryprofound.com

Bottom line:

• Deepest query/citation investigation: Peec
• Enterprise-grade research: Profound
• Straightforward monitoring on a budget: Otterly

If you're specifically trying to discover the queries you aren't currently tracking that could cause AI to cite each of your existing how-to guides, that's a slightly different problem—and I'd choose the tooling differently.

If your goal is specifically “Which exact AI queries caused my how-to guide URL to be cited?”, I’d prioritize citation-level tracking, not generic “AI visibility” software.

My top picks

1. otterly.ai — best fit for your use case

• Shows the specific prompts/queries in which a particular URL was cited.
• Lets you drill into a citation and see the AI engine, prompt, response, and cited URL.
• Covers ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini and Copilot.
• Its citation-detail view explicitly surfaces “the prompts this URL was cited in.” Otterly OtterlyAI
• It starts around $29/month, according to its current site. Otterly

For a library of how-to guides, this is probably where I'd start.

2. tryprofound.com — best for serious/enterprise GEO

• Stronger if you want to understand why your content is being cited, not merely whether it is.
• Tracks citation visibility by prompt, platform, topic and competitor.
• Also uses real-user query data rather than relying exclusively on a manually constructed prompt list. Profound Profound
• Better choice if you're managing a large content operation or doing sophisticated AEO/GEO analysis.
• getintel.ai — worth considering if citation data is the priority

• Focuses particularly on the sources AI engines actually cite, rather than simply whether your brand appears.
• Its current offering stores the cited source list for individual runs across ChatGPT, Perplexity, Gemini and Google AI Overviews. GetIntel

The important distinction

There are really two different questions you might be asking:

“What queries make AI mention my brand?”

versus

“What exact queries make AI cite this particular how-to URL?”

The second is much more useful for content optimization.

For example, imagine you have:

/guides/how-to-migrate-wordpress-to-shopify

You ideally want a report like:

Otterly is particularly close to that workflow because its citation analysis lets you go from a URL → the prompts that cited it. Otterly

One caveat

No tool can literally observe every private question users ask ChatGPT and tell you that those users subsequently caused your page to be cited. What these platforms generally do is maintain a controlled set of prompts and repeatedly query the AI search experiences, recording the resulting citations. Otterly, for example, describes its system as automatically running tracked prompts across AI engines and analyzing the resulting answers/citations. OtterlyAI OtterlyAI

So I'd think of the data as:

“These are the queries under which your guide is demonstrably being cited”

rather than:

“These are all the queries people on the internet have ever used.”

What I'd buy

For a site with lots of instructional content:

Otterly → first choice
Profound → if you're doing enterprise-level GEO
GetIntel → if raw citation/source intelligence matters most

And I'd specifically evaluate whether the tool can export URL → prompt → engine → response → citation data. That's much more valuable for your use case than a generic “AI visibility score.”

The market is also changing quickly: AI citation patterns themselves are volatile, so I'd favor a tool that stores the underlying prompt/response/citation evidence rather than giving you only an aggregate score. axios.com

If you tell me roughly how many how-to guides you have (e.g. 50, 500, 5,000) and whether you care about ChatGPT only or ChatGPT + Google AI + Perplexity, I can narrow this to the best 2–3 options and compare their current pricing/features.

If your goal is specifically “which exact questions cause ChatGPT/Perplexity/Gemini/etc. to cite my how-to guides?”, I’d focus on AI visibility / citation tracking tools, not generic SEO software.

My picks

1. ahrefs.com — best overall for your use case

• Lets you track the exact prompts you care about and see whether your site is mentioned or cited.
• Its larger prompt database is based on search-backed queries rather than entirely synthetic questions.
• You can organize prompts into clusters and see which URLs are being cited.
• It covers ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, Copilot and others. Ahrefs Ahrefs Help Center
• Particularly good if your how-to guides already have substantial Google-search demand.
• otterly.ai — best inexpensive dedicated tracker

• Built specifically around monitoring prompts and AI visibility.
• Good choice if you don't want to buy a full SEO suite.
• Current comparisons put its entry tier around $29/month, with higher tiers based largely on prompt volume. UX Continuum Marqeable
• peec.ai — best for deeper GEO analytics

• More focused on analyzing why and where you're visible across AI engines.
• Worth considering if you're managing a large library of guides or doing this professionally for multiple sites. Kitbase AEO Labs
• tryprofound.com — best enterprise option

• Much more heavyweight: prompt monitoring, citation intelligence, competitive analysis, etc.
• I'd consider it overkill unless AI visibility is a significant marketing channel for your organization. Marqeable SEO Counselors

The important distinction

There's a subtle problem with the question “what queries caused an AI model to cite my guide?”

These systems generally don't expose a definitive log saying:

User asked X → model retrieved URL Y → model cited Y.

The practical approach is to construct a panel of likely questions, repeatedly run them against the AI systems, and record the resulting citations. AI outputs can vary between runs, so you're measuring observed citation probability rather than obtaining an authoritative historical log. Ahrefs explicitly notes that AI responses are probabilistic and can change from session to session. Ahrefs

For your particular use case, I'd therefore set up something like:

Guide → topic cluster → 20–100 natural-language questions → ChatGPT/Perplexity/Gemini/etc. → cited URL → citation frequency → competing URLs

That gets you much closer to the information you're actually after than a conventional “AI visibility score.”

My recommendation: start with Ahrefs Custom Prompts if you already use Ahrefs; otherwise start with Otterly. If you tell me roughly how many how-to guides you have (e.g. 50, 500, 5,000), I can recommend the most cost-effective setup and explain how I'd structure the query panel.

If by “pinpointing the exact queries” you mean “show me the specific prompts where my how-to URL was cited, and ideally the underlying retrieval/fan-out queries that caused the model to find it,” then the shortlist is pretty clear.

My top pick: Profound

tryprofound.com is probably the strongest fit for this specific use case.

Its page-level analytics can break a URL's citations down by prompt, topic, platform, region, persona, and even text chunks. That gets unusually close to answering “which exact AI questions caused this guide to be cited?” Profound Knowledge Base Profound Knowledge Base

It also tracks citations across ChatGPT, Perplexity, Google AI Overviews and other answer engines. Profound

Why I'd choose it for how-to content: you can start with /guides/how-to-x, identify the prompts citing it, then investigate which portions of the guide are apparently useful enough to get retrieved.

Most interesting alternative: Peec AI

peec.ai is particularly interesting if you're trying to understand what the AI is actually searching for behind the user's prompt.

Its standout feature is Query Fanouts: it exposes related/background searches that ChatGPT, Perplexity and Copilot perform while constructing an answer, including distinct fan-out queries and their frequency. Peec AI

That makes Peec potentially better than a conventional rank/citation tracker for your question:

User asks: “How do I configure X?”
→ AI performs several underlying searches
→ your guide gets retrieved/cited
→ you can see the related queries associated with that process.

It also tracks the specific prompts generating mentions and citations. Peec AI

The distinction that matters

There are actually three different things you might mean by “exact queries”:

Profound's Agent Analytics additionally lets you distinguish AI crawler activity from actual AI-driven referral traffic. Profound

What I would use for a how-to site

If your goal is specifically “reverse-engineer why my how-to guides get cited”, I'd test Profound first, with Peec AI as the second tool.

The ideal workflow is:

1. Put your important how-to URLs into a tracked set.
2. Track hundreds/thousands of natural-language prompts around each task.
3. Find URL → exact prompt → AI engine → citation position.
4. Examine the fan-out queries where available.
5. Compare the cited portions of your guide against competing pages.
6. Repeat after changing the guide and see whether its citation footprint changes.

One caveat: no tool can literally reveal the model's private internal reasoning. “Fan-out queries” are observable/reconstructed searches performed by the answer engine, not the model's hidden chain of thought. Peec explicitly distinguishes these query fan-outs from the underlying model reasoning. Peec AI

Bottom line: for “which exact prompts cite this particular how-to URL?” → Profound. For “what searches does the AI appear to perform behind those prompts?” → Peec AI. If that's the level of forensic detail you're after, those are the two I'd trial before generic SEO tools.

Why I'd choose it for how-to content: you can start with /guides/how-to-x, identify the prompts citing it, then investigate which portions of the guide are apparently useful enough to get retrieved.

Most interesting alternative: Peec AI

peec.ai is particularly interesting if you're trying to understand what the AI is actually searching for behind the user's prompt.

Its standout feature is Query Fanouts: it exposes related/background searches that ChatGPT, Perplexity and Copilot perform while constructing an answer, including distinct fan-out queries and their frequency. Peec AI

That makes Peec potentially better than a conventional rank/citation tracker for your question:

User asks: “How do I configure X?”
→ AI performs several underlying searches
→ your guide gets retrieved/cited
→ you can see the related queries associated with that process.

It also tracks the specific prompts generating mentions and citations. Peec AI

The distinction that matters

There are actually three different things you might mean by “exact queries”:

Profound's Agent Analytics additionally lets you distinguish AI crawler activity from actual AI-driven referral traffic. Profound

What I would use for a how-to site

If your goal is specifically “reverse-engineer why my how-to guides get cited”, I'd test Profound first, with Peec AI as the second tool.

The ideal workflow is:

1. Put your important how-to URLs into a tracked set.
2. Track hundreds/thousands of natural-language prompts around each task.
3. Find URL → exact prompt → AI engine → citation position.
4. Examine the fan-out queries where available.
5. Compare the cited portions of your guide against competing pages.
6. Repeat after changing the guide and see whether its citation footprint changes.

One caveat: no tool can literally reveal the model's private internal reasoning. “Fan-out queries” are observable/reconstructed searches performed by the answer engine, not the model's hidden chain of thought. Peec explicitly distinguishes these query fan-outs from the underlying model reasoning.

Yes. If your specific goal is “Which exact AI queries cause ChatGPT/Perplexity/etc. to cite this particular how-to guide?”, I’d prioritize tools differently than I would for generic AI-brand monitoring.

My picks

For what you described, I'd start with OtterlyAI. Its current citation reporting is unusually close to the question you're asking: you can start with a specific URL and see which prompts and engines are responsible for its citations, rather than merely seeing that your domain was mentioned somewhere. otterly.ai

One important distinction

You probably don't actually want a tool that only says:

“Your guide was cited 17 times.”

You want something closer to:

Guide: /how-to-configure-x
Cited for: “How do I configure X on a Linux server?”
Engine: ChatGPT
Answer: …
Citation position: #2
Competitor citations: …
Related prompts: “How do I troubleshoot X?”, “What are the best settings for X?” …

That prompt → answer → URL relationship is the valuable dataset. Otterly explicitly supports this drill-down workflow, and its Prompt Monitoring records the exact prompt being monitored. otterly.ai

If you have lots of how-to guides

I'd build your measurement around URL-level citation attribution, not just brand visibility:

1. Import your guide URLs.
2. Generate/discover the likely questions for each guide.
3. Track those prompts across ChatGPT, Perplexity, Google AI experiences, Gemini, etc.
4. Record which exact URLs are cited for each prompt.
5. Group results by guide.
6. Look for prompts where competitors are cited but your guide isn't.
7. Re-run after updating the guide.

That's much more actionable than an overall “AI visibility score.”

One caveat: none of these platforms can reveal the private, naturally occurring prompt that an individual ChatGPT user typed and then caused your page to be cited. They generally work by monitoring a defined/discovered prompt set and observing the resulting AI answers. So if by “exact queries” you mean the literal queries used by real users, that's a different—and substantially harder—measurement problem.

If you tell me roughly how many how-to guides you have (10, 100, 10,000+) and whether you're mainly targeting ChatGPT, Google AI Overviews, or both, I can narrow this to the best 2–3 options and tell you what I'd actually buy.

If your goal is “show me the exact prompts/questions for which an AI model cited my how-to guide”, you want a prompt-level AI citation tracker, not a generic AI SEO/visibility tool.

My shortlist

Current comparisons put Profound at the enterprise/high-depth end, while Otterly is considerably more approachable for a smaller program. slatehq.com

The important distinction

Suppose you have a guide:

/how-to-migrate-from-wordpress-to-webflow/

You don't just want:

“Your site was cited 47 times.”

You want something closer to:

That's prompt-level citation intelligence. Most of the serious tools work by maintaining a defined prompt set and repeatedly running those queries, because there isn't a magic feed of every real-world ChatGPT conversation that contains your URL. www.citeflow.io

For your specific use case, I'd pick Profound

If you have dozens/hundreds of how-to guides and you're trying to discover which natural-language questions cause each guide to get cited, Profound is probably the first product I'd test. Current 2026 comparisons describe it as tracking citations at the URL level across a broad set of AI engines and exposing prompt-level data. nicklafferty.com

If you're smaller and primarily want an affordable monitoring system, I'd test Otterly first.

One caveat: “exact queries that caused citations” is inherently an estimate unless you're controlling the query set yourself. AI tools generally sample a defined set of prompts; they can't tell you every question every user has ever typed into ChatGPT. So the strongest workflow is to build a large prompt universe around each guide—how-to, troubleshooting, comparison, “best way,” alternatives, implementation, etc.—and then track which variants actually generate your URL as a citation. oversearch.ai

If you tell me roughly how many how-to guides you have (e.g. 50, 500, 10,000), I can narrow this down to the best 2–3 tools and the cheapest setup that will actually uncover the queries behind your citations.

If your goal is specifically “show me the exact natural-language queries/prompts that cause AI models to cite my how-to guides”, I’d narrow the field considerably.

My picks

🥇 Peec AI is probably the closest match to what you're asking for. Its particularly useful feature is Query Fanouts: it shows the related/background searches an AI model generates while answering a tracked prompt. It also distinguishes between URLs an AI accessed and URLs it actually cited in the visible answer. That lets you get much closer to “what query led the model to find/cite this particular guide?” rather than merely “was my domain mentioned?” peec.ai

Peec AI

🥈 OtterlyAI is my recommendation if you want something simpler. You can track exact prompts, see domain citations for each prompt, and drill from a prompt into the individual AI response and citation. Its newer GEO Audit also has Query Fan-Out, specifically designed to reveal related questions and intents generated from an initial prompt. help.otterly.ai

OtterlyAI

🥉 Profound is stronger if you're running this as a serious enterprise/content operation. It tracks which answer engines cite your content, which prompts produce those citations, and which pages are winning or losing citation share. www.tryprofound.com

Profound

The important distinction

There are actually three different things you might mean by “queries that lead AI to cite my guide”:

1. User prompt

“How do I migrate a WordPress site to a new host?”

2. AI-generated fan-out queries

The model may internally/search-wise expand that into things like:

“WordPress migration steps”
“how to export WordPress database”
“moving WordPress files to new server”

3. Citation attribution

The tool tells you: your /guides/wordpress-migration page was cited in the resulting answer.

Peec is the standout for #2 + #3 together. peec.ai

One caveat: “exact query that caused the citation” isn't always literally observable. AI systems can perform multiple searches, retrieve pages without citing them, or synthesize an answer from several sources. Peec explicitly separates sources accessed from citations shown in the answer, which is why I think it's particularly appropriate for this use case. peec.ai

If you're trying to optimize a library of how-to guides, I'd choose Peec AI first, OtterlyAI second.

If your goal is “show me the specific prompts where an AI answer cited my how-to guide”, rather than just “does my brand appear in AI search,” I’d shortlist these:

1. Otterly.AI — best fit for your use case
   • Lets you track the exact prompts you define.
   • Shows which prompts produce citations to your website and monitors them across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and others. otterly.aihelp.otterly.ai
   • Its prompt-research feature can also uncover relevant AI-search questions rather than making you invent every query yourself. otterly.ai
   • Important limitation: no tool can generally reveal the actual private prompts real users typed into ChatGPT. They infer/monitor representative prompts. Otterly explicitly describes this as a blind spot in AI search. otterly.ai

2. Profound — best if you need deeper enterprise analysis
   • Stronger choice if you're managing a large content portfolio and want extensive prompt/citation analytics, competitive analysis and reporting.
   • Multiple 2026 comparisons put Profound toward the enterprise end of the market. www.xseek.io

3. Peec AI — good middle ground
   • Particularly useful for analyzing citation/visibility patterns and comparing competitors.
   • I'd consider it if your objective is GEO experimentation rather than simply monitoring a fixed prompt list. fifteenthmeridian.com

The key distinction for your how-to guides

Suppose you have:

/guides/how-to-migrate-wordpress-to-shopify

What you really want to discover is something like:

Otterly is probably the first product I'd test because its prompt-level monitoring is explicitly designed around this workflow. Its documentation says each tracked prompt is monitored daily and the Prompts view exposes the exact prompt and its performance signals. otterly.aihelp.otterly.ai

One caveat: if by “exact queries that lead AI models to cite my guides” you mean discovering previously unknown, real-world queries that people are actually asking, that's a harder problem. AI platforms generally don't expose users' private prompt logs. The best products therefore combine prompt discovery + controlled prompt monitoring + citation-source analysis, rather than giving you a literal log of every user query. otterly.ai

My pick: start with Otterly.AI; move to Profound if you need enterprise-scale research/reporting.

If by “pinpointing the exact queries” you mean “show me the specific prompts/questions for which ChatGPT, Perplexity, Gemini, etc. cited this particular how-to URL”, you want prompt-level citation tracking, not generic “AI visibility.”

My shortlist

Recent 2026 comparisons consistently distinguish prompt-level citation tracking from simple brand-mention monitoring; Profound, Peec and Otterly are among the more relevant options for that job. meev.ai

But there's an important catch

No tool can tell you the actual private queries real users typed into ChatGPT that caused your guide to be cited. AI platforms generally don't expose that user-query/citation relationship.

What these platforms can do is:

1. Build or let you define a large set of target prompts.
2. Run those prompts against AI engines repeatedly.
3. Record which URLs were cited in each answer.
4. Tell you something like:

“How do I migrate a WordPress site?” → your /guides/wordpress-migration page cited
“Best way to migrate WordPress without downtime?” → competitor cited
“How to migrate WordPress to a new host?” → your page cited

That's probably the dataset you're after. Some platforms can also generate suggested prompts rather than making you manually invent them. meev.aiprommer.net

For how-to guides specifically

I'd prioritize page/URL-level attribution + prompt-level reporting over overall “AI share of voice.”

You want to be able to answer:

Guide → exact tracked query → AI engine → cited URL → competing cited URLs → answer → citation position → change over time

That lets you discover which question formulations your guide is winning, rather than merely seeing “your domain was mentioned 14% of the time.”

My pick: start with Otterly if you want to cheaply validate the workflow; go to Profound if you have hundreds of guides/prompts and need serious analysis. Independent 2026 testing also describes Otterly as a budget entry point and Profound as the deeper enterprise option. prommer.net

If you tell me roughly how many how-to guides you have (10 / 100 / 1,000+) and which AI engines matter most, I can narrow this to the 2–3 tools that can actually give you the query → URL citation data you're looking for, rather than just generic AI visibility dashboards.

If your goal is “which exact user queries caused ChatGPT/Gemini/Perplexity/etc. to cite my how-to guides?”, you want an AI visibility / GEO (Generative Engine Optimization) platform with prompt-level citation tracking, not a normal SEO rank tracker. These tools are designed to show prompts, cited URLs, engines, and competitors. www.airops.compaylinedata.com

My shortlist:

For how-to guides specifically, I would evaluate tools against these features:

1. Prompt → citation mapping
   • “For the query how do I configure X?, which guide URL was cited?”
   • This is the closest equivalent to keyword ranking reports in SEO.

2. Page-level citation frequency
   • Which guides are repeatedly selected as sources?
   • Which guides get impressions but never citations?

3. Competitor source comparison
   • “When AI answers this question, does it cite my guide or someone else’s?”

4. Prompt discovery
   • The best tools surface unexpected queries you did not think to track. diyai.io

A practical stack for a content site:

• Free baseline: Bing Webmaster Tools AI Performance. www.bing.com
• Serious content program: Scrunch AI or Profound for citation/query intelligence. getairefs.compaylinedata.com
• SEO team already paying for a suite: Semrush or Ahrefs add-ons. www.airops.compaylinedata.com

One caveat: no tool can perfectly reveal the true private user prompt history that caused a model citation. They generally work by running controlled prompt sets, monitoring available AI surfaces, and correlating prompts with citations. searchengineland.com

If you tell me whether your guides are B2B SaaS docs, affiliate/how-to content, developer docs, or consumer tutorials, I can narrow this down to the tools that are strongest for that type of citation tracking.

If you mean “I have how-to guides, and I want to know the exact user prompts/questions where ChatGPT, Claude, Gemini, Perplexity, etc. decide to cite my pages”, you’re looking for AI citation tracking / GEO (Generative Engine Optimization) software, not traditional SEO rank trackers. These tools simulate prompts, inspect AI answers, and map prompt → AI response → cited URL. www.airops.com

The strongest options right now:

For how-to guides specifically, I’d prioritize these features:

1. Prompt discovery
   • “How do I fix X?”
   • “Best way to do X?”
   • “Step-by-step guide for X”
   • “Tools for X”
   • “Alternative to X”

2. Citation-level reporting
   • Exact prompt that produced the citation
   • Model used (ChatGPT/Claude/etc.)
   • Your cited URL
   • Position of your citation in the answer
   • Competing guides cited instead

3. Prompt clustering
   • Groups thousands of variations into topics like:
     • troubleshooting
     • setup instructions
     • comparisons
     • beginner questions

My practical picks:

• Solo creator / small documentation site: MentionScout or Citations.io. citations.iomentionscout.com
• SEO/content team: AirOps or HubSpot AEO. blog.hubspot.comwww.airops.com
• Enterprise with existing SEO stack: Ahrefs + an AI citation tracker. www.techradar.com

One caveat: no tool can know the true hidden internal query a model used (models generally don’t expose their private reasoning or retrieval chain). The best tools infer this by running controlled prompts and analyzing the resulting citations and answer patterns. citations.iomentionscout.com

If your goal is specifically “find the questions people ask that cause my tutorial URL to appear as a citation”, I’d look first at MentionScout-style prompt/citation mapping rather than a generic AI visibility score. mentionscout.com

If your goal is “which exact user prompts cause ChatGPT/Perplexity/Gemini/etc. to cite my how-to guides?”, you’re looking for AI visibility / GEO (Generative Engine Optimization) platforms, not traditional SEO rank trackers. These tools simulate prompts, record AI answers, and map citations back to URLs. proofmap.com

The strongest options right now:

For how-to guides specifically, I’d prioritize these capabilities:

1. Prompt discovery
   • Finds the actual questions people ask AI, not just keywords.
   • Example:
     • “How do I migrate a WordPress site?”
     • “What’s the safest way to configure X?”
     • “Step-by-step guide for Y”

2. Citation attribution
   • Shows:
     • prompt → AI answer → cited URL → citation frequency
   • This is the closest equivalent to “which queries make my guide win.” www.getcitepilot.comoptimizetrack.q5labs.co

3. Competitor citation gaps
   • Finds prompts where another guide is cited and yours is not. getlumis.ai

4. Page-level diagnostics
   • Helps answer why your guide was ignored:
     • unclear answer structure
     • missing definitions
     • insufficient evidence
     • weak topical coverage

A practical stack many content teams use:

• Ahrefs / Semrush → discover topics and competitors
• Profound or Peec AI → find AI prompts and citations
• Google Search Console + analytics → measure traffic impact
• Manual prompt testing → validate important queries

One caveat: AI citations are not as deterministic as Google rankings. A page can be cited for one phrasing of a question and disappear for a near-identical phrasing, so good tools track sets of prompts and repeated runs, not one-off checks. arxiv.org

If you mainly care about your own documentation/how-to library, I’d shortlist:

1. Profound (enterprise budget)
2. CitePilot (prompt → citation workflow)
3. Peec AI (content team workflow)
4. SEORav/OptimizeTrack (lighter monitoring) optimizetrack.q5labs.co

The key metric to look for is not “AI visibility score”; it’s “which exact prompts produced citations to which URLs, and how often.”

If your goal is “show me the exact natural-language prompts for which an AI engine cited my how-to guide”, I’d narrow the field considerably.

My top picks

OtterlyAI is probably the closest match to what you're describing. Its prompt-level reporting shows the exact prompt, whether your brand appeared, and Domain Citations—how often your domain was cited. You can drill into an individual prompt to see the actual AI response and the URLs cited. help.otterly.ai

It also has AI Prompt Research, which can generate/discover the kinds of natural-language questions people might ask, rather than making you manually invent hundreds of prompts. help.otterly.ai

The important caveat

There is a subtle distinction between:

“Which prompts caused my guide to be cited?”

and

“Which prompts do people actually type into ChatGPT?”

The first is measurable. The second generally isn't available as a clean, comprehensive dataset. Most AEO/GEO tools therefore construct or estimate prompt sets and repeatedly test them. A recent review makes this limitation explicit: AI visibility tools generally use sampled prompts rather than having direct access to users' private ChatGPT query logs. www.techradar.com

So for your how-to guides, I'd structure the measurement as:

Prompt → AI response → cited URL → specific guide → citation frequency

rather than thinking of it as conventional keyword tracking.

What I'd actually do

If you have, say, 50 how-to guides, I'd start with Otterly and create prompt clusters around each guide:

• [task] how to
• how do I [task]
• best way to [task]
• [task] step by step
• [problem] how to fix
• what's the easiest way to [task]
• [task] for beginners
• comparisons/alternatives where appropriate

Then monitor ChatGPT + Perplexity + Google AI Overviews/AI Mode + Gemini and identify:

1. Which exact prompts produce citations to your domain
2. Which URL gets cited
3. Which competing URLs get cited instead
4. How frequently your guide is cited
5. Whether the AI actually uses information from your guide, rather than merely linking to it

That last point is important: research on generative-search citations distinguishes merely being selected as a citation from the model actually absorbing/using the cited page's information. arxiv.org

Also, don't put too much weight on a single observed prompt/result. AI search is nondeterministic: the same query can produce different citations at different times, so repeated sampling is much more meaningful than a one-off test. arxiv.org

Bottom line: If you're specifically trying to build a dataset of “AI query X → my how-to URL was cited”, I'd trial OtterlyAI first, then Profound if you need substantially deeper enterprise-level prompt/citation intelligence.

If your goal is specifically “Which exact questions cause AI models to cite my how-to guides, and which pages do they cite?”, I’d prioritize tools that expose prompt-level results + citation URLs, rather than generic “AI visibility” scores.

My picks

Current comparisons consistently put Peec, Profound, Otterly, Ahrefs and Semrush among the leading AI-visibility platforms. technologyadvice.com

For your particular use case, I'd choose Peec AI

The important distinction is that you don't merely want to know:

“Does ChatGPT mention my site?”

You want something closer to:

Prompt: “How do I migrate a WordPress site without downtime?”
Model: ChatGPT
Answer: …
Citation: your /guides/wordpress-migration page
Competitor citations: X, Y, Z
Frequency/visibility: …
Date: …

Peec is particularly geared toward prompt-level AI search analytics, including citations and competitor visibility. diyai.io

Profound is the stronger choice if you're doing this at enterprise scale and want more sophisticated analysis of AI answers and citations. technologyadvice.com

Otterly is the one I'd investigate first if you want a cheaper, dedicated monitoring product rather than a large SEO suite. toolchase.com

One important caveat

No tool can literally tell you the real-world user's exact private ChatGPT prompt that caused a citation. What these platforms generally do is run a controlled/monitored set of prompts and report which queries produce your citations. That's still extremely useful, but it's different from having access to every actual user conversation.

For example, you can build a prompt universe around a how-to guide:

• “How do I X?”
• “What's the easiest way to X?”
• “X step-by-step”
• “How can I fix X?”
• “X for beginners”
• “Best way to X without Y”
• “X vs Y”
• “Why is X happening?”
• “How do I troubleshoot X?”

Then track which formulations actually produce your URL as a citation.

There's also a very interesting free/first-party option

If your guides are appearing in Microsoft's AI experiences, Bing Webmaster Tools' AI Performance now provides citation-oriented data including grounding queries, query intent, topic clusters and Citation Share. That's unusually close to what you're asking for because it's based on Microsoft's own search/AI ecosystem rather than a third-party simulation. diyai.io

And urlAhrefs' free AI Visibility Checkerturn0search3 can give you a quick cross-model snapshot across ChatGPT, Gemini, Perplexity, Copilot and Google AI Overviews, including topics that trigger mentions and the pages/domains cited. ahrefs.com

Bottom line:
Peec AI → best fit for prompt → answer → citation analysis.
Profound → best if you're running serious enterprise AEO/GEO.
Otterly → best lower-cost dedicated tracker.
Ahrefs → best if you're already an Ahrefs customer.

If you tell me roughly how many how-to articles you have (e.g. 50, 500, 5,000), I can narrow this down to the best tool and workflow for discovering the actual query patterns that get those articles cited.

If by “exact queries” you mean the actual prompts/questions for which ChatGPT, Perplexity, Gemini, etc. cite a specific how-to URL on your site, then you want a prompt-level AI citation tracker, not a conventional SEO tool.

My picks

For how-to guides, I'd choose Otterly first

The workflow I'd use is:

Your guide URL → generate relevant prompts → monitor those prompts → filter for your domain → see exactly which URL was cited → inspect the response.

For example, if you have:

yoursite.com/guides/how-to-migrate-wordpress

you want the system to surface things like:

• “How do I migrate a WordPress site?”
• “What is the easiest way to move WordPress to a new host?”
• “How do I migrate WordPress without downtime?”
• “Can I move WordPress without losing SEO?”
• “What are the steps to migrate WordPress from Bluehost to SiteGround?”

…and then tell you:

Prompt: “How do I migrate WordPress without downtime?”
Engine: ChatGPT
Your URL: cited
Citation position: #2
Competitor URLs: X, Y, Z
Response: [actual AI answer]

That's much closer to what you're asking for than simply measuring “AI visibility.”

One important caveat: no tool can tell you the exact private prompts real users typed into ChatGPT/Claude/Gemini when those users aren't sharing that data. These platforms generally work by running a representative/targeted prompt set themselves. Community discussions also note that there isn't currently a Google-Search-Console-like report exposing users' exact LLM prompts. www.reddit.com

Also, don't overinterpret a single citation. AI search is stochastic: the same query can produce different citations on different runs, so repeated sampling matters. arxiv.org

If your primary goal is specifically “which questions cause my individual how-to articles to get cited?” I'd start with Otterly, then compare it against Profound if you're running a larger content program.

If your goal is specifically “show me the exact questions/prompts for which an AI model cited my how-to guide”, I’d prioritize AI visibility/AEO platforms that expose the underlying prompt → answer → cited URL, rather than generic SEO rank trackers.

Best options

1. Peec AI — probably the closest fit

Strong emphasis on tracking actual prompts and the resulting AI answers, including which sources get cited. Good if you want to understand which questions produce citations, not merely whether your brand is visible. Community testing also specifically highlights its prompt/response records. www.reddit.com

2. Profound — best for serious prompt-level research

Designed around understanding how AI search engines answer queries, what sources they cite, and how your visibility changes. I'd look here if you have a substantial content library and want deeper competitive/source analysis.

3. HubSpot AEO — easiest starting point

It explicitly lets you track specific prompts and see whether your brand appears and in what context across ChatGPT, Perplexity, and Gemini. It currently offers 25 tracked prompts free, then $50/month for the same 25 prompts. www.hubspot.com

4. DeepSmith — good citation-centric option

Tracks citation rate, mentions, share of voice, the underlying answers, and which sources AI trusts across ChatGPT, Gemini, Perplexity, Claude, and Google AI Mode. deepsmith.ai

5. Nobori — particularly interesting for content teams

It tracks buyer-intent prompts and exposes Cited Pages and Cited Domains, with daily prompt monitoring. nobori.ai

The important distinction

There are really two different questions you might be trying to answer:

A. “What prompts should I be targeting?”
→ Most AEO/GEO tools can generate or suggest prompt sets.

B. “What exact prompts actually caused AI to cite this particular URL?”
→ This is much harder, and you want a tool that records the prompt + complete response + individual citations + cited URL.

For your use case, B is the more valuable metric.

Also, don't treat one observed citation as definitive. AI search is nondeterministic: identical queries can produce different answers and citations at different times. Recent research specifically recommends treating citation visibility as a distribution rather than a fixed ranking. arxiv.org

What I'd use for how-to guides

I'd build a dataset like:

That lets you discover citation-producing query patterns, rather than optimizing blindly for keywords.

One particularly useful finding from recent research is that highly influential cited pages tend to be structured, semantically aligned, and rich in extractable evidence—definitions, facts, comparisons, and procedural steps. That's especially relevant to how-to content. arxiv.org

My shortlist: Peec AI if exact prompt/citation discovery is the priority; Profound if you want a deeper enterprise-grade research platform; HubSpot AEO if you want the simplest inexpensive way to start testing.

If you tell me roughly how many how-to guides you have (10 / 100 / 1,000+) and which models matter most (ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude), I can narrow this to the best 2–3 and compare their prompt-level capabilities and pricing.

If your specific goal is “Which exact user queries cause ChatGPT/Perplexity/Gemini/etc. to cite this particular how-to guide?”, I’d narrow the field considerably.

My picks

Current comparisons consistently put Profound, Peec and Otterly among the strongest dedicated AI-visibility platforms. fifteenthmeridian.com

The important distinction

Be careful with the phrase “exact queries.”

Most platforms don't have a magical feed of actual ChatGPT user queries that happened organically to produce your citation. Instead, they maintain or generate a large set of representative prompts, run them repeatedly against AI search engines, and record:

Prompt → AI answer → cited sources → your URL/page → competitors

That's still extremely useful, but it's different from Google Search Console's model of seeing actual search queries.

For your use case, I'd specifically test whether a platform can show something like:

“How do I migrate a WordPress site without downtime?”
ChatGPT → cites your /guides/wordpress-migration page
Perplexity → cites competitor A + your page
Gemini → doesn't cite you
Citation position: #2
Last seen: Aug. 7
Competitor cited: competitor A

Prompt-level visibility is particularly important because aggregate “AI share of voice” can tell you that you're visible without telling you which questions generated the visibility. Community testing of these platforms makes the same distinction. www.reddit.com

For how-to guides, I'd choose Peec AI or Profound

Peec AI is my first one to trial if you're primarily a content/SEO operator. Its positioning is strongly around AI-search analytics, including prompts, mentions, citations and competitors. www.jotform.com

Profound is the better choice if you want to go much deeper—particularly if you have a large content library and want enterprise-grade competitive intelligence. Profound says its platform incorporates a very large real-user prompt dataset, which is an important distinction from simply inventing keyword-to-prompt variations. www.tryprofound.com

Otterly is where I'd start if you're testing the concept on a smaller budget; current comparisons put it at the accessible end of this market while still providing prompt/citation monitoring. www.aeolabs.ai

One feature I'd insist on

For your particular objective, don't buy based on “AI visibility score.”

Ask every vendor to demonstrate this exact workflow:

URL → pages citing it → exact prompts → full AI response → citation/source → engine/model → date/history

If they can't drill down from a specific URL to the specific prompts that generated its citations, it's probably not the right product for what you're trying to measure.

If you tell me roughly how many how-to guides you have (10 / 100 / 1,000+) and whether you're targeting ChatGPT, Perplexity, Gemini, Google AI Overviews, or all of them, I can narrow this to the best 2–3 and compare their current pricing/features.

If your goal is to discover the exact prompts/questions that cause ChatGPT, Gemini, Claude, or Perplexity to cite your how-to guides, you need a Generative Engine Optimization (GEO) or LLM visibility platform—not a traditional SEO rank tracker.

Here's how I'd rank the current options:

If I ran a large how-to site

I'd probably use Bourd.

Why:

• Tracks prompt-by-prompt visibility
• Shows the exact AI response
• Records every cited URL
• Lets you schedule recurring tests
• Compares your guides against competitors
• Supports ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, and more. bourd.devwww.seorav.com

That gets very close to answering:

"Which questions make AI cite my guide?"

If your priority is discovering new questions

I'd lean toward BlueJar.

One feature that stands out is that it tries to identify the prompts your audience is already asking AI, then runs hundreds of those prompts automatically and shows:

• whether your site appeared,
• who was cited instead,
• and where you have gaps. bluejar.ai

That's especially useful for building new how-to content.

If you're on a budget

You don't necessarily need an enterprise platform.

A practical workflow is:

1. Build a list of 100–500 how-to questions.
2. Test them weekly across ChatGPT, Gemini, Claude, and Perplexity.
3. Record:
   • whether your guide was cited,
   • which URL was cited,
   • which competitors were cited,
   • and how the wording changes over time.

Several newer tools automate this workflow, including Bourd, LLMMonitor, and SEORav. bourd.dev

One limitation to keep in mind

No software can observe the actual private prompts that users type into ChatGPT or other AI assistants. These platforms instead run large, representative sets of prompts that match likely user intent and then monitor which sources the models cite. So they reveal the prompts that trigger citations in controlled testing, not the private queries from real users. bourd.devwww.seorav.com

If your site publishes hundreds or thousands of how-to guides, I can also recommend tools that are optimized specifically for publishers (rather than SaaS brands), where the focus is on maximizing AI citations across large content libraries.

If your goal is to identify the specific prompts and queries that cause AI assistants (ChatGPT, Gemini, Claude, Perplexity, etc.) to cite your how-to guides, no single tool can do this perfectly because most AI companies don't expose complete prompt-level referral data.

The best approach is to combine AI visibility platforms with your own analytics.

If your goal is "What exact questions cause my article to be cited?"

The closest solutions today are:

1. Profound
   • Runs thousands of prompts automatically.
   • Shows which prompts mention your site.
   • Tracks competitors.
   • Shows changes over time.

2. Goodie AI
   • Finds prompts where your content appears.
   • Groups them into intent clusters.
   • Good for publishers.

3. Peec AI
   • Lets you monitor keywords like:
     • "how to unclog a sink"
     • "best way to clean cast iron"
     • "how to file LLC taxes"
   • Tracks whether AI answers cite your domain.

What no software can currently do

No platform can tell you:

"Yesterday 247 real ChatGPT users asked exactly this prompt."

That data is private to the AI providers.

Instead, these platforms estimate real usage by:

• generating millions of representative prompts,
• monitoring citations,
• clustering semantically similar questions,
• identifying which prompt families consistently surface your content.

A workflow used by many publishers

Combine:

• Google Search Console to identify successful search intents.
• An AI visibility platform (Profound, Goodie AI, or Peec AI) to monitor AI citations.
• Microsoft Clarity or Google Analytics to measure AI referral traffic.
• Server logs to detect requests from AI crawlers (such as OpenAI's GPTBot or Anthropic's ClaudeBot) before new citations appear.

If you're an independent creator

A practical stack is:

• Peec AI for ongoing AI query tracking.
• Google Search Console for organic intent research.
• Google Analytics 4 to measure AI referral traffic.
• Periodic manual testing across ChatGPT, Gemini, Claude, and Perplexity using your target topics.

This combination offers strong visibility without the higher cost of enterprise platforms.

If you're publishing hundreds or thousands of how-to guides, investing in Profound or Scrunch AI may be worthwhile because they automate large-scale prompt testing and competitive citation tracking.

If your goal is to discover the specific prompts and search-style queries that cause ChatGPT, Gemini, Claude, Perplexity, or Google's AI Overviews to cite your content, there isn't a single tool that reveals every exact prompt. However, a few platforms come surprisingly close by combining AI citation tracking, prompt monitoring, and search intelligence.

Here's how I'd rank them:

If your goal is "What exact questions make AI cite me?"

The current best workflow is:

1. Use Profound or Goodie AI to discover prompts where your domain appears.
2. Export those prompts.
3. Cluster them into themes.
4. Use Ahrefs or Semrush to expand each theme into hundreds of related long-tail questions.
5. Create additional guides that answer adjacent questions.

For example, if AI frequently cites your article for:

"How do I replace a toilet fill valve?"

You'd expand into:

• replace toilet fill valve without turning off water
• replace Fluidmaster 400A
• toilet fill valve keeps hissing
• toilet won't stop filling
• toilet tank fills slowly
• universal fill valve installation
• Kohler fill valve replacement
• Toto fill valve replacement

Those related pages often become new citation opportunities.

If you want the actual prompts users type

No public tool has access to every real ChatGPT or Gemini conversation. The best platforms infer prompts by:

• systematically testing millions of prompts against AI models,
• tracking which sources are cited,
• monitoring changes over time,
• and building prompt datasets from observed behavior.

That means they can identify prompts like "How do I unclog a garbage disposal?" that consistently cite your guide, even though they can't reveal every individual user's private conversations.

For publishers with lots of how-to content

A powerful stack is:

• Profound for AI citation tracking.
• Ahrefs for long-tail keyword discovery.
• Google Search Console for impressions and clicks from traditional search.
• Your site's analytics (for example, server logs or analytics software) to monitor referral traffic from AI products that send referrals.

This combination gives you both traditional SEO visibility and emerging AI search visibility.

If your site has hundreds or thousands of how-to guides, I can also suggest tools and workflows specifically designed to identify the next articles AI models are most likely to cite, rather than just tracking your current citations.

If your goal is to understand which user prompts cause AI assistants (ChatGPT, Gemini, Claude, Perplexity, etc.) to surface or cite your how-to guides, no tool can tell you the exact private prompts users entered into those models. AI companies generally don't expose that data.

However, several tools can help you identify the prompts most likely to trigger citations and monitor when your content appears.

If your objective is "What exact prompts cite my content?"

The closest available approach is:

1. Build a large library of likely prompts (thousands rather than dozens).
2. Automatically test those prompts against ChatGPT, Gemini, Perplexity, Claude, and other AI systems.
3. Record:
   • whether your guide is cited
   • where it ranks
   • which competitors are cited instead
   • changes over time

This is what platforms like Profound, Goodie, Peec AI, and Scrunch AI are designed to do.

If you're a publisher with lots of how-to content

A workflow many publishers use is:

• Ahrefs or Semrush → discover long-tail informational searches.
• AI visibility platform (Profound, Goodie, etc.) → convert those into AI prompt monitoring.
• Analytics (such as GA4) → measure whether AI referrals are increasing.
• Server logs → identify traffic from AI crawlers and referrals (though this does not reveal user prompts).

If you want the most comprehensive solution

For a site with hundreds or thousands of guides, I'd recommend:

• Best overall: Profound
• Best value for AI-focused SEO: Goodie
• Best if you're already doing SEO: Semrush + an AI visibility platform
• Best for technical SEOs: Ahrefs + custom prompt testing

One important limitation: no commercial tool can reveal the actual private prompts that users typed into ChatGPT or other AI assistants. The best available products infer those prompts by systematically testing millions of likely variations and tracking which ones result in your content being cited.

If you're primarily trying to increase AI citations rather than just measure them, I can also recommend tools specifically for Generative Engine Optimization (GEO) and explain which ones have been most effective for publishers in 2026.

If your goal is to identify the exact prompts (or the closest practical approximation) that cause ChatGPT, Claude, Gemini, or Perplexity to cite your how-to guides, you're looking for a new category of tools often called AI visibility, LLM citation tracking, or GEO (Generative Engine Optimization).

One important limitation: no tool can tell you the exact prompts real users typed into ChatGPT. AI companies generally don't expose user prompt data. The best platforms generate and monitor large libraries of likely prompts, then report which ones cite your content. www.techradar.comsearchnextgen.com

Here's how I'd rank the current options:

The closest thing to "exact queries"

The best platforms show something like:

Prompt: "How do I remove mold from leather boots?"

Result:

• ✅ Your guide cited
• ❌ Competitor A not cited
• Sources used:
  • yoursite.com/remove-mold-boots
  • competitor.com/leather-care

or

Prompt: "Best way to sharpen Japanese kitchen knives"

Result:

• Your article not cited
• AI cited:
  • Serious Eats
  • Wirecutter
  • Manufacturer documentation

That lets you identify the questions where you're already winning versus the ones where you need stronger content. forestseo.com

If you want the deepest insights

I'd combine:

• urlForestSEOturn0search5 for prompt-by-prompt citation tracking and content provenance.
• urlCitations.ioturn0search3 for identifying which questions AI answers with your content versus competitors'.
• Your own prompt testing using the APIs for ChatGPT, Gemini, Claude, and Perplexity. Maintaining a curated list of hundreds or thousands of relevant "how-to" prompts often reveals niche opportunities that generic dashboards miss. www.techradar.comsearchnextgen.com

If you have hundreds or thousands of how-to guides, an enterprise-oriented platform with scheduled scans is usually worth it. If you have 10–50 high-value guides, you can often get most of the benefit by building your own prompt set and testing it regularly alongside one of these monitoring tools.