ChatGPT answers, unedited

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.