Neutral mentions of Peec AI

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

For an ecommerce blog, the useful distinction is whether a tool merely tells you “ChatGPT mentioned your brand” or actually tells you which domains/pages ChatGPT, Perplexity, Gemini, etc. cited in their answers.

Tools worth looking at

• Ahrefs Brand Radar — probably the easiest place to start if you already use Ahrefs. It tracks ChatGPT, Gemini, Perplexity, Copilot and Google AI results, and specifically reports cited domains and cited pages, not just brand mentions. Ahrefs Ahrefs
• Profound — geared more toward serious/enterprise AI-search monitoring. It tracks citations down to the URL level across a broad set of AI engines, so you can investigate exactly which pages are being used as sources. Nick Lafferty
• Frase — a simpler option for content teams. Its AI Visibility Checker looks at ChatGPT, Perplexity and Gemini and reports citations, share of voice and related visibility metrics. Frase
• Searchable — particularly interesting if your goal is researching citation patterns across the web, rather than only monitoring your own brand. It publishes citation datasets for ChatGPT, Google AI Overviews and Perplexity and offers brand monitoring. Searchable
• Otterly.AI / Peec AI / Scrunch / similar GEO platforms — worth considering if you want ongoing prompt monitoring and competitor comparisons; the category has expanded considerably in 2026. Birdeye

For your specific ecommerce use case

I'd structure the tracking around questions such as:

“What are the best running shoes for flat feet?”
“Best gifts for a 10-year-old who likes science”
“Which [product category] is worth buying under $100?”

Then track, for each chatbot:

Ahrefs is particularly aligned with your wording because its current AI visibility reporting explicitly includes the top cited domains and top cited pages associated with AI responses. Ahrefs

One important caveat: these tools generally sample prompts and AI-generated responses rather than having omniscient access to every chatbot conversation. AI results can also vary by query, location, time, model and retrieval context, so citation tracking is best treated as a measurement sample rather than an exact census.

If you tell me roughly how many blog posts/products you have and your monthly budget (e.g. $0, <$100, $100–500, $500+), I can narrow this down to the most practical 2–3 tools for an ecommerce site.

For a local business website, you’ll want an AI visibility / GEO (Generative Engine Optimization) tracker that measures more than brand mentions: it should show whether ChatGPT, Gemini, Perplexity, Claude, and Google AI results cite your website, which competitors appear instead, and which prompts trigger the results. Citations Local Glyph

Here are the strongest options:

My shortlist by business type

Single-location local business (dentist, contractor, restaurant, salon, etc.)

Start with:

1. localglyph.com — because it is built around local queries and competitor comparisons. Local Glyph
2. otterly.ai — if you want broader AI assistant coverage. KITLabs

Multi-location business or marketing agency

Consider:

• citations.io for citation-level reporting. Citations
• semrush.com if you already manage SEO campaigns. Citation Hawk

If your main question is “Does ChatGPT recommend me?”

Look for these metrics:

• Citation rate: how often your domain appears as a source
• Mention rate: how often your business name appears
• Share of voice: your visibility versus competitors
• Prompt coverage: whether you appear for the questions customers actually ask
• Source gap analysis: which directories, reviews, articles, or pages AI systems rely on instead Citations Cite Ladder

For a typical local business, I would avoid tools that only give a single “AI score.” The useful output is the list of exact prompts where you were missing, who was cited instead, and what pages/sources those AI systems used. Cite Ladder

If you tell me your business type (e.g., HVAC, law firm, restaurant, ecommerce, medical, etc.) and whether you care more about ChatGPT, Google AI Overviews, or all assistants, I can narrow this to 2–3 choices.

Yes. For a local business, I’d prioritize tools that track actual AI answers and citations by location, not just generic “AI SEO” scores.

My shortlist for 2026

Independent 2026 comparisons similarly put Profound, Otterly, Scrunch, Ahrefs, ZipTie, Semrush and others among the leading AI-visibility platforms. TechnologyAdvice Citation Hawk

What I'd choose for a local business

Start with Otterly AI if you're managing one or a few locations.

The important thing isn't simply whether AI mentions your company. You want to measure:

• Citation rate: how often your website is actually cited
• Mention rate: how often the business is recommended/mentioned
• Share of voice: how often competitors appear instead
• Which pages get cited
• Which prompts produce citations
• Performance by AI platform
• Geographic variation — e.g. “best plumber in Columbus” versus “best plumber near me”
• Changes over time

That's particularly important for local businesses because visibility can differ dramatically between AI platforms. A recent local-business study found only 4.6% of recommended businesses were named by all four of ChatGPT, Gemini, Claude and Perplexity in its test set. Visibility Index

One thing I'd avoid

Don't buy a tool just because it gives you an “AI visibility score.” The useful underlying data is the actual prompt → AI response → mention/citation → cited URL → competitor chain.

For example, you want to be able to see something like:

“Best HVAC companies in Columbus”
ChatGPT → Your Business: #2 recommendation → cites /hvac-services/
Perplexity → Your Business: not mentioned
Gemini → Your Business: #4 recommendation → cites Yelp
Google AI Overview → not present

That tells you what to fix. A single score doesn't.

If you're already paying for local SEO software

If you already use BrightLocal, it's worth evaluating its AI visibility functionality rather than adding another subscription. Conversely, if you already use Ahrefs or Semrush, their AI modules may be the most economical option. Current comparisons specifically identify BrightLocal as a practical option for single-location businesses and Ahrefs/Semrush as logical choices for existing SEO-suite customers. Pleiades Consultancy TechnologyAdvice

If you tell me what type of local business you have, how many locations, and roughly what you'd like to spend per month, I can narrow this to the 2–3 best tools and compare their actual pricing, AI platforms, local/geographic tracking, and citation reporting.

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product questions about my store/category?”, you want an AI citation tracking / GEO (Generative Engine Optimization) tool, not a traditional SEO rank tracker.

The main options I’d evaluate:

For an online store, I would structure the measurement like this:

1. Build a prompt set around buying intent

Track prompts like:

• “best [product category]”
• “[product] alternatives”
• “[brand] vs [competitor]”
• “best [product] under $X”
• “where to buy [product]”
• “is [product] worth it”
• “best [use case] product”

The important unit is the prompt → AI answer → cited domains, not just your brand mention.

2. Export citations into a database

Create a table like:

Then group by:

• domain citation share
• product category
• AI engine
• competitor overlap
• URL type (review, marketplace, product page, forum)

3. Watch these domain categories

For ecommerce, the domains AI engines cite often fall into:

• Review publishers
• Reddit/community sites
• Marketplaces
• Manufacturer sites
• Retailers
• Comparison sites
• YouTube/blog content
• Your own product pages

The strategic question becomes: “What sources are shaping the AI answer before the shopper reaches checkout?”

My practical recommendation

For a small-to-medium store:

1. Start with Ahrefs Brand Radar if you already pay for Ahrefs. Ahrefs
2. Add a commerce-focused tracker like LLM Metrix or eCommerce Insights AI if you care about SKU-level visibility. LLM Metrix eCommerceInsights.AI
3. Keep your own spreadsheet/database of prompts and citations so you can analyze trends independently.

If you tell me your platform (Shopify, WooCommerce, Magento, custom) and approximate SKU count, I can suggest a more specific stack and data model.

The strategic question becomes: “What sources are shaping the AI answer before the shopper reaches checkout?”

My practical recommendation

For a small-to-medium store:

If your goal is specifically “Which academic papers, journals, university sites, and other domains are ChatGPT/Perplexity/etc. using as sources?”, I’d separate that from ordinary academic citation tracking. Traditional tools like Scite measure how papers cite one another; you want to measure how AI systems cite papers and domains.

What I’d shortlist

Current industry comparisons indicate that the important distinction is citation tracking vs. mention tracking: you want the actual URL/source that an AI answer used, rather than simply whether your press or author was named. SEORav Presenc AI

For a university press, I'd build the measurement around papers—not just your brand

For example, create a recurring prompt set such as:

• “What are the foundational works on [subject]?”
• “Which books/papers should I read to understand [topic]?”
• “What does the literature say about [research question]?”
• “Who are the leading scholars on [topic]?”
• “Recommend academic sources for teaching [course/topic].”
• Questions specifically designed around individual books, authors, journals, and research areas.

Then capture, for every AI response:

engine → prompt → cited URL → cited domain → paper/book → author → publisher → position in answer → frequency of citation → competing sources

That lets you answer much more useful questions such as:

“Our book is well indexed in Google, but when people ask AI about this subject, which other books and papers are being cited instead?”

There is good reason to measure this at the domain and URL level. Recent multi-platform academic research found that AI citations can be highly concentrated among a relatively small number of domains, while different AI systems can have substantially different source preferences. arXiv

My practical recommendation

For a university press, I'd consider a two-layer setup:

1. AI visibility/citation tracker — Profound, Semrush, Otterly, or a comparable specialist tool for monitoring what ChatGPT, Perplexity, Google AI surfaces, etc. actually cite.
2. Scholarly citation intelligence — Scite + Crossref/Semantic Scholar/OpenAlex-type bibliographic data for understanding conventional scholarly influence.

The combination is considerably more informative than either alone. You can distinguish:

“Researchers cite our book”
from
“AI systems retrieve and cite our book when answering researchers' questions.”

Those are increasingly different forms of discoverability.

One caution: don't treat an AI citation count as an equivalent to a scholarly citation count. AI answers are stochastic and depend heavily on the exact prompt, model, retrieval system, date, geography, and web index. A recent 2026 audit of AI citations illustrates why repeated, controlled prompt sampling is preferable to treating a single answer as definitive. arXiv

If you tell me roughly how many titles you publish (e.g. 500 vs. 10,000), your budget, and whether you want API/export access, I can narrow this to a concrete 2–3-tool stack and explain how I'd set up an AI-discoverability dashboard for the press.

If your enterprise content team specifically needs citation frequency + position/rank across multiple AI models, I’d shortlist Scrunch and Peec AI.

Best fits

• scrunch.com — strongest fit if citation intelligence is the centerpiece. It tracks cited URLs/domains, citation frequency and trends, brand presence, response position, share of voice, and competitor visibility. It currently supports ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok, and Meta AI. Scrunch Scrunch Help Center

• Particularly enterprise-oriented: SOC 2 Type II, SSO/RBAC, multi-brand/domain/region support, and API access. Scrunch
• Its citation view lets teams drill from domain → specific URL → prompt-level performance, which is useful for editorial/content teams trying to understand which pieces of content actually get cited. Scrunch Help Center
• peec.ai — arguably the cleaner fit if by "rank" you mean where your brand/content appears in an AI answer. It tracks visibility, average position, citation count/frequency, sentiment, and share of voice by model. Peec AI

• Covers ChatGPT, Gemini, Perplexity, Google AI Overviews, Google AI Mode, and Copilot, with additional models available on higher tiers. Peec AI
• It also distinguishes brand mentions from source citations, and exposes citation frequency at domain/URL level. Peec AI
• Daily tracking makes it useful for monitoring changes after publishing or updating content. Peec AI

How I'd choose

One important caveat: AI "rank" isn't equivalent to a Google SERP ranking. ChatGPT and other models don't necessarily return a fixed numbered list, so these platforms generally operationalize rank as things such as position in the generated answer, mention frequency, visibility, or average position. Peec explicitly makes this distinction. Peec AI Peec AI

For an enterprise content organization, I'd start with Scrunch if the core question is "What content and third-party sources are AI models citing, how often, and how is that changing?" I'd start with Peec if it's "How often are we mentioned and where do we appear relative to competitors across each model?"

If you tell me your approximate scale (e.g. 1,000 vs. 100,000 prompts/month, number of brands/domains, and whether you need API/BI integration), I can narrow this down further and include Profound, Otterly, Ahrefs Brand Radar, and other enterprise GEO platforms.

For an enterprise content team, the category you’re looking for is usually called AI visibility tracking, LLM visibility, GEO (Generative Engine Optimization) analytics, or AI citation monitoring. These platforms test prompts across AI assistants, track whether your brand/content is mentioned or cited, identify the cited sources, and often benchmark competitors. SEO Counselors Lighthouse

Here are the main platforms to evaluate:

For an enterprise content operation, I would shortlist based on workflow:

If you have a global content team and need governance/reporting:

• Profound
• AthenaHQ
• Semrush/Ahrefs if SEO operations already live there

Backtier SEO CounselorsIf your priority is “which pages are AI models citing, and why?”

• Profound
• Lighthouse-style AI visibility tools that store citation evidence and per-model breakdowns

Lighthouse LighthouseIf you want to build your own reporting layer:

• Trackee or another API-first provider

TrackeeBefore selecting, I’d check that the platform can answer these enterprise questions:

• Which prompts trigger citations for us?
• Which URLs are cited by ChatGPT vs Claude vs Gemini vs Perplexity?
• Citation frequency over time (weekly/monthly trend)?
• Citation share compared with competitors?
• Which content gaps explain lost visibility?
• Can we export data into Looker/Tableau/BI systems?
• Does it store the actual AI responses for auditability?

A practical enterprise stack is often:
AI visibility platform + existing SEO platform + content analytics + BI dashboard, rather than replacing SEO tooling entirely. Backtier Lighthouse

If you share your company size (startup, mid-market, Fortune 500), CMS (Adobe, Contentful, WordPress, etc.), and whether you care more about brand mentions or actual URL citations, I can narrow this to 2–3 options.

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 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.