ChatGPT answers, unedited

If your goal is specifically “Which domains are AI answer engines citing when people ask product-related questions in my store’s category?”, I’d use an AI-search citation monitoring platform, rather than trying to infer this from Google Search Console or traditional SEO tools.

My shortlist

• scrunch.com — probably the closest match to your exact use case. It records the cited URLs from tracked prompts, lets you aggregate them by domain, and lets you break them down by AI platform, topic, prompt, competitor, etc. You can also drill from domain → individual URL → prompts that cited it. Scrunch Scrunch Help Center
• otterly.ai — particularly interesting for ecommerce because it tracks citations across multiple AI engines and also has AI Shopping Analytics, including how products surface in AI shopping results and which retailers are mentioned. Otterly Otterly AI
• tryprofound.com — better suited if you're building a more sophisticated enterprise AEO/SEO program. Its citation analysis includes citation share, citation coverage, source categories, platforms, topics, regions and other dimensions. Profound Profound Help Center

What I'd actually map

Don't just track “Does AI mention my store?” Build a dataset like:

Then aggregate it into something like:

Domain → number of citations → % of prompts cited → engines citing it → product categories → URLs being cited → competitors mentioned there.

That's considerably more useful than a simple AI visibility score. Scrunch, for example, explicitly supports domain- and URL-level citation analysis and tracks citation consistency across prompts. Scrunch

For an online store, I'd add one important layer

Separate your prompts into:

• Category discovery: “best X for…”
• Product comparison: “X vs Y”
• Attribute questions: “best X that is waterproof/lightweight/etc.”
• Price/value: “best X under $100”
• Retailer questions: “where should I buy X?”
• Specific product: “is [product] worth buying?”
• Shopping-intent queries: prompts that trigger product/shopping results

That lets you answer a much more actionable question:

“For the product categories where I make money, which third-party domains are AI engines repeatedly trusting instead of my site?”

That's where the data becomes useful for your AEO/content/PR strategy—you can identify, for example, that AI engines repeatedly cite a particular review site, Reddit, retailer, publisher, or comparison site for a category, and then investigate why.

If I were choosing just one for this particular job, I'd start with Scrunch. If AI shopping/product-card visibility is equally important, I'd put OtterlyAI into the evaluation too. Their capabilities overlap, but Otterly explicitly exposes shopping-result analytics. Otterly

If you tell me your ecommerce platform + product category + approximate number of SKUs, I can also suggest the data architecture for building this yourself (including the prompt set and the domain/citation dashboard).

If your goal is specifically mapping which domains AI answer engines cite for product-related questions, you want a tool that records:

• The exact prompts being tested (e.g. "best standing desk under $500")
• Which AI engine was queried (ChatGPT, Perplexity, Gemini, Claude, AI Overviews)
• Every cited domain and URL
• Which competitors appear alongside you
• Changes over time

For ecommerce brands, I'd prioritize tools like this:

These newer GEO platforms are built specifically around AI citations rather than traditional keyword rankings. They repeatedly ask buying-intent questions across major AI engines and record which domains and pages are cited. OnCited Citlyze RiseMore

If I ran an online store today

I'd combine three layers:

1. Traditional SEO

• Ahrefs or Semrush
• Google Search Console
• AI visibility

• OnCited or Citlyze
• Track 100–500 commercial prompts
• Custom monitoring

• Maintain your own prompt library
• Run weekly checks
• Store:

• cited domains
• cited URLs
• your appearance rate
• competitors
• answer text

This lets you answer questions like:

• Which review sites does ChatGPT trust?
• Which blogs does Perplexity cite?
• Does Gemini favor manufacturer pages or editorial reviews?
• Which comparison pages consistently win citations?

For product-related ecommerce questions

Instead of tracking generic keywords, organize prompts into buying stages:

• Best espresso machine under $500
• Is Brand A better than Brand B?
• Best running shoes for flat feet
• Where should I buy Product X?
• Product X review
• Product X alternatives
• Cheapest Product X
• Product X vs Product Y

You'll often find the same third-party domains repeatedly cited (review publishers, Reddit, YouTube, manufacturer sites, retailer product pages, and expert buying guides). Those recurring domains become targets for your content and digital PR strategy.

If you're a smaller store

A lightweight approach is:

• Ahrefs or Semrush for SEO
• One GEO platform (such as OnCited or Citlyze)
• A spreadsheet or database that logs:

• Prompt
• Engine
• Cited domains
• Your rank/mention
• Competitors
• Date

That combination gives you most of the visibility you'd need without investing in a large enterprise AI-monitoring platform.

If you're managing thousands of SKUs, I can also suggest a workflow that automatically maps AI citation patterns by product category (e.g., "coffee makers," "office chairs," "running shoes") and highlights which domains each answer engine consistently trusts.

If your goal is specifically to map which domains AI answer engines cite when shoppers ask product/category questions, I’d use an AI visibility / citation-monitoring platform, not ordinary rank tracking.

What I’d use

ahrefs.com is probably the most straightforward fit if you already use Ahrefs. It tracks AI answers across ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, Copilot and others, and lets you inspect cited domains and pages. It also supports custom prompts, so you can feed it the exact product questions your customers ask. Ahrefs Help Center Ahrefs

For example, you could track:

• “best running shoes for flat feet”
• “best [product category] under $100”
• “[product A] vs [product B]”
• “alternatives to [competitor]”
• “best [category] for [use case]”
• “is [product] worth it?”
• “[product category] reviews”
• “[product category] for beginners”

Then build a dataset like:

That distinction between mentions and citations matters: an AI can mention your product while citing someone else's site. Ahrefs explicitly separates those metrics and also records pages that were retrieved but not ultimately cited. Ahrefs Help Center

Another tool worth looking at

otterly.ai is more directly oriented around prompt-level AI search monitoring. It runs your prompt set across seven AI engines and records the answers, mentions, competitors and the URLs/domains cited in those answers. Otterly

So I'd think of the two roughly as:

• Ahrefs Brand Radar: better if you want to connect AI visibility with your existing SEO/search-demand data and discover which domains/pages are influencing AI answers. Ahrefs Ahrefs
• OtterlyAI: attractive if your primary job is monitoring a defined set of buyer prompts and their AI citations over time. Otterly

For an online store, I'd structure the analysis this way

Don't just measure “does AI cite my domain?”. Build a citation landscape:

1. Collect 100–500 high-intent product prompts across your major categories.
2. Run them across ChatGPT, Perplexity, Gemini, Google AI, etc.
3. Extract every cited URL.
4. Normalize URLs into domains.
5. Group domains into categories:

• publishers/reviews
• Reddit/forums
• retailers/marketplaces
• manufacturers/brands
• comparison sites
• affiliates
• your own domain
• Calculate citation frequency by domain × engine × product category.
• Separately track which specific pages are repeatedly cited.
• Compare that with your own pages and competitors' pages.

The really interesting output becomes something like:

For “best X” queries, 37% of citations come from review publishers, 22% from Reddit, 15% from retailers, 11% from manufacturers…

and then:

Domain X is cited 4.2× as often as our store for category Y, primarily because of these three URLs.

That tells you much more than an “AI visibility score.”

One caveat: AI-answer monitoring is inherently sampling-based. You can't observe every private ChatGPT conversation or every AI answer, so treat the resulting domain map as a representative measurement of your tracked prompts, not an absolute census. Ahrefs makes this limitation explicit. Ahrefs

If you tell me what platform your store is on (Shopify, WooCommerce, custom, etc.) and roughly how many product categories you have, I can lay out a concrete AI citation-tracking stack + spreadsheet/database schema + prompt set for doing this at scale.

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d use an AI citation/visibility tracker, not a traditional rank tracker.

My picks

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

It separates mentions from actual citations, shows the domains and individual pages being cited, and lets you track custom prompts across ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, and Copilot. Ahrefs Ahrefs Help Center

• semrush.com — best if you're already a Semrush user.

Its Prompt Tracking can show which domains/pages are cited for your tracked prompts, while its competitor reports let you see where competitors are winning. Semrush Semrush

• GetIntel — worth considering if citation data itself is the priority.

It focuses more narrowly on storing the actual cited-source lists from AI answers rather than trying to be a full SEO platform. GetIntel

How I'd set it up for an ecommerce store

Don't just track:

“Does ChatGPT mention my store?”

Track a prompt universe around your products:

Then build a dataset something like:

Prompt → AI engine → answer → cited domain → cited URL → your domain cited? → competitor cited? → citation frequency

The really valuable metric isn't simply “we were mentioned.” It's:

For the commercial questions that matter to our store, which domains are consistently being used as sources?

Ahrefs is particularly interesting here because it distinguishes “cited” pages from pages the AI retrieved but didn't actually cite. Ahrefs Help Center

The analysis I'd do afterward

Once you've collected the citations, aggregate them by domain:

Domain             Citations    % of answers
reddit.com             182          21.4%
youtube.com             96          11.3%
amazon.com              83           9.8%
yourcompetitor.com      61           7.2%
yourstore.com           14           1.6%

Then break those down by product category and prompt type.

That tells you something much more actionable than an AI visibility score: where answer engines are getting their product information from.

You can then ask, for example:

• Why is Reddit cited so heavily for this category?
• Which publishers/review sites are disproportionately cited?
• Which competitor product pages are getting cited?
• Are AI engines citing editorial content, reviews, retailers, forums, YouTube, or manufacturer pages?
• Which domains appear across multiple AI engines?
• What content do those frequently cited URLs contain?
• Which sources cite competitors but never cite us?

If you're building this for an online store, I'd start with Ahrefs Brand Radar + a custom prompt set. Its custom-prompt tracking is explicitly designed for focused questions, and it can monitor the major AI answer engines. Ahrefs Help Center

If you tell me what you sell + roughly how many products/categories you have, I can also lay out the exact AI citation-tracking schema/dashboard I'd use (including the prompts, fields, KPIs, and how to turn the citation data into an SEO/AEO content plan).

Prompt → AI engine → answer → cited domain → cited URL → your domain cited? → competitor cited? → citation frequency

The really valuable metric isn't simply “we were mentioned.” It's:

For the commercial questions that matter to our store, which domains are consistently being used as sources?

Ahrefs is particularly interesting here because it distinguishes “cited” pages from pages the AI retrieved but didn't actually cite. Ahrefs Help Center

The analysis I'd do afterward

Once you've collected the citations, aggregate them by domain:

Domain             Citations    % of answers
reddit.com             182          21.4%
youtube.com             96          11.3%
amazon.com              83           9.8%
yourcompetitor.com      61           7.2%
yourstore.com           14           1.6%

Then break those down by product category and prompt type.

That tells you something much more actionable than an AI visibility score: where answer engines are getting their product information from.

You can then ask, for example:

• Why is Reddit cited so heavily for this category?
• Which publishers/review sites are disproportionately cited?
• Which competitor product pages are getting cited?
• Are AI engines citing editorial content, reviews, retailers, forums, YouTube, or manufacturer pages?
• Which domains appear across multiple AI engines?
• What content do those frequently cited URLs contain?
• Which sources cite competitors but never cite us?

If you're building this for an online store, I'd start with Ahrefs Brand Radar + a custom prompt set. Its custom-prompt tracking is explicitly designed for focused questions, and it can monitor the major AI answer engines.

If your goal is specifically “which domains are AI answer engines citing when people ask product/category questions relevant to my store?”, I’d use an AI visibility/citation tracking platform, rather than trying to infer it from Google Search Console.

My first choice: Profound

tryprofound.com is probably the closest fit to what you're describing.

Its Answer Engine Insights tracks prompts across AI platforms and records the actual cited domains/pages. You can see:

• Top citation domains — e.g. Reddit, Wirecutter, CNET, competitor sites, retailers, blogs, etc.
• Top citation pages — the exact URLs AI is using.
• Citation share — how frequently each domain/page is cited.
• Citation sources by platform — so you can distinguish what ChatGPT vs. Gemini vs. Google AI Overviews, etc. are using.
• Competitor citation gaps — domains citing competitors but not you.
• Citation categories — owned, competitors, earned media, social, institutions, etc. Profound Help Center Profound

That's particularly useful for an ecommerce store because you can ask questions like:

“What are the best running shoes for flat feet under $150?”
“Which [product category] is best for beginners?”
“What should I buy for [use case]?”
“Compare Brand A vs Brand B.”

Then build a dataset of which domains get cited in the answers.

Profound also tracks citations at the individual URL level and lets you export the underlying data, which is useful if you want to build your own reporting/dashboard. Profound Profound Help Center

How I'd set it up for an online store

I wouldn't just track your brand name. I'd create a prompt set roughly like:

Then segment the results by:

AI engine → prompt → cited domain → cited URL → brand mentioned → competitor → product/category

The most valuable output isn't necessarily “is my store cited?”.

It's:

“For the questions that could generate revenue for me, which third-party websites are repeatedly being used as evidence by AI?”

Those domains become your AI citation/authority targets.

For example, you might discover:

Product category: Running shoes

AI citation share
────────────────────────
reddit.com             18%
runnersworld.com        14%
nytimes.com/wirecutter  11%
rei.com                  9%
competitor.com           8%
yourstore.com            2%

That immediately tells you something actionable: getting your store cited more often may require both better product/category content on your site and getting mentioned by the external sites AI already trusts.

Profound explicitly recommends using top-cited domains/pages this way—as a roadmap for both content and off-page outreach. Profound

Alternatives worth evaluating

I'd also look at the broader AI-search visibility tools, but I'd prioritize them based on your exact requirement:

• Profound — strongest fit if citation/domain intelligence is the central requirement.
• Semrush AI Visibility / AI-related tools — attractive if you already use Semrush and want AI visibility integrated with conventional SEO.
• Ahrefs — worth considering if your primary workflow is SEO/content and you want to add AI-search analysis rather than make AI citation tracking the centerpiece.
• Custom tracking — worthwhile if you have engineering resources and want complete control over the prompt corpus, raw responses, citations, and historical database.

One important distinction: don't confuse AI crawler analytics with citation tracking. Seeing GPTBot, OAI-SearchBot, etc. hit your store tells you that an AI system crawled your content; it does not tell you that your page was actually cited in an answer. What you want is the latter.

What I'd actually build

For an ecommerce business, I'd make the core dashboard:

AI Citation Intelligence

• 500–2,000 high-value product/category prompts
• ChatGPT
• Google AI Overviews / AI Mode
• Gemini
• Perplexity
• Claude where relevant
• Daily/weekly snapshots
• Cited domain
• Cited URL
• Citation frequency
• Your brand mention
• Competitor mentions
• Product mentioned
• Position in answer
• Citation share
• New/lost citations
• Domain category
• Citation gap vs competitors

That gives you a much more useful metric than generic “AI visibility”:

For commercially valuable questions, what sources are AI engines using to construct their recommendations—and where does my store fit into that source ecosystem?

If you tell me what kind of products your store sells + roughly how many SKUs/categories you have, I can also recommend the best tool/stack and a concrete prompt taxonomy for tracking your category.

If you tell me what kind of products your store sells + roughly how many SKUs/categories you have, I can also recommend the best tool/stack and a concrete prompt taxonomy for tracking your category.

Then segment the results by:

AI engine → prompt → cited domain → cited URL → brand mentioned → competitor → product/category

The most valuable output isn't necessarily “is my store cited?”.

It's:

“For the questions that could generate revenue for me, which third-party websites are repeatedly being used as evidence by AI?”

Those domains become your AI citation/authority targets.

For example, you might discover:

Product category: Running shoes

AI citation share
────────────────────────
reddit.com             18%
runnersworld.com        14%
nytimes.com/wirecutter  11%
rei.com                  9%
competitor.com           8%
yourstore.com            2%

That immediately tells you something actionable: getting your store cited more often may require both better product/category content on your site and getting mentioned by the external sites AI already trusts.

Profound explicitly recommends using top-cited domains/pages this way—as a roadmap for both content and off-page outreach.

Alternatives worth evaluating

I'd also look at the broader AI-search visibility tools, but I'd prioritize them based on your exact requirement:

If your goal is specifically “Which domains are AI answer engines citing when people ask product-related questions in my category?”, I’d use an AI visibility / citation-tracking platform, rather than trying to infer it from Google Search Console.

My top pick: Profound

tryprofound.com is probably the closest match to what you're describing.

Its citation analysis can show:

• Which domains AI engines cite for your tracked product/category prompts
• Which specific URLs get cited
• How often each domain is cited
• Your citation share vs. competitors
• Which sources are owned, competitor, earned media, social, PR, etc.
• Citation differences across ChatGPT, Perplexity, Google AI Overviews and other answer engines Profound Profound Help Center
• Which third-party publishers repeatedly influence answers in your category—useful for figuring out where you need reviews, comparisons, mentions, etc. Profound

For an online store, I'd structure your tracking around product-intent prompts, not just keywords.

For example, if you sell running shoes, track prompts like:

• “best running shoes for flat feet”
• “best running shoes under $150”
• “Nike Pegasus vs Brooks Ghost”
• “best shoes for marathon training”
• “where should I buy [product type] online?”
• “best [product category] for beginners”
• “[your product] alternatives”
• “is [your product] worth it?”

Then build a report roughly like:

The “your store vs. the domains that influence AI answers” distinction is particularly important. You don't necessarily need AI engines to cite your own product pages everywhere. If AI repeatedly cites a particular review site, Reddit thread, comparison site, retailer, or publication when answering questions in your category, getting your products/brand represented there may be the bigger opportunity.

Semrush is the other one I'd consider

semrush.com is attractive if you're already using Semrush for traditional SEO. Its AI Visibility tooling tracks mentions, citations, cited pages, AI visibility, and distribution by LLM, and lets you track custom prompts. Semrush Semrush

I'd choose:

• Profound → if AI citations and “what sources influence the answer?” are the primary question.
• Semrush → if you want AI visibility + conventional SEO in the same ecosystem.

What I would actually measure for an ecommerce store

Don't make “number of AI mentions” your primary KPI. I'd build an AI Product Visibility dashboard with:

1. Prompt
2. AI engine
3. Product/category
4. Brand mentioned?
5. Product recommended?
6. Position in answer
7. Cited?
8. Cited URL
9. Cited domain
10. Competitors mentioned
11. Competitor citation domains
12. Citation frequency
13. Citation share
14. Date

That lets you answer the much more actionable question:

“When someone asks an AI engine for a product like mine, which sources are shaping the recommendation—and what do I need to do to become part of that source set?”

That's essentially the emerging AI/AEO/GEO competitive intelligence problem. Profound's citation-share and top-citation-domain reporting is particularly well aligned with it. Profound Help Center Profound

If you tell me what your store sells and roughly how many products/categories you have, I can suggest the exact prompt set and a practical tracking stack (including a cheaper DIY option if you don't want to pay for Profound/Semrush).

If your goal is to map which domains AI answer engines cite when shoppers ask product-related questions, you want an AI citation tracking / answer engine optimization (AEO) tool, not a traditional SEO rank tracker. The key data you need is:

• Prompt → AI engine → answer → cited URLs → cited domains → whether the source supports you or competitors
• Domain citation frequency by product category
• “Citation gaps” (domains AI trusts that mention competitors but not you)
• Trends over time

Tools that are designed for this include:

• tryprofound.com — enterprise-focused; tracks cited sources, competitors, prompts, and source categories. Profound
• rankscale.ai — useful if you want domain-level citation share and comparisons across multiple answer engines. Rankscale.ai
• vercite.io — focuses on exact cited URLs/domains and competitor source overlap. Vercite
• trendos.com — specifically emphasizes “most cited domains” and source-type breakdowns. Trendos
• cited.cc — lighter-weight monitoring of when selected prompts produce citations involving your domain. Cited

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

A practical stack could be:

1. Citation tracker (one of the tools above)

→ discover the domains AI engines rely on.

2. Spreadsheet/database dashboard

Suggested columns:

• Product category
• Prompt
• Engine
• Date checked
• Cited domain
• Cited URL
• Source type
• Competitor mentioned?
• Your brand mentioned?
• Opportunity score
• SEO tools for validation

• Backlink analysis: find why those domains are trusted.
• Content analysis: compare pages that win citations.

The biggest mistake is tracking only “does AI mention my brand?” A domain can influence AI recommendations without ever naming you. The more valuable question is: “Which sources are shaping the answer, and how do we get into that source set?” Honeyb Vercite

If you have a large catalog (hundreds/thousands of SKUs), I’d also consider building a prompt library from your product taxonomy and running automated citation monitoring by category rather than by individual product.

If your goal is specifically “which domains are AI answer engines citing when people ask product/category questions relevant to my store?”, I’d look at AI-search citation tracking platforms, rather than traditional SEO rank trackers.

My picks

1. tryprofound.com — best for serious/enterprise analysis

• Tracks citations across ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude and other answer engines.
• Shows Top Citation Domains, individual cited URLs, citation share, competitor citations, and citation categories. Profound Profound Help Center
• Particularly useful for your question because you can identify something like: > “For best running shoes for beginners, AI engines repeatedly cite REI, Runner's World, Reddit, Amazon, Nike, etc., but almost never my store.”
• You can then build an outreach/content strategy around those domains.
• otterly.ai — best lighter-weight option

• Tracks ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini and Copilot.
• Its citation reports show the URL, domain, number of citations, whether your brand is mentioned on that page, domain category, and competitors. Otterly Otterly
• It also recently added citation trends and a way to see which prompts and engines are responsible for a URL's citations. Otterly

What I'd actually measure for an ecommerce store

Don't just track whether your domain gets cited. Build a dataset around:

The “your product mentioned but your site not cited” case is especially valuable. It tells you that AI knows about your product but is relying on someone else as the authority.

One important distinction

If you're trying to answer “what sites influence AI answers in my product category?”, Profound/Otterly are the right type of tool.

If you're trying to answer “which AI bots are actually crawling my store?”, that's a different measurement. Otterly now has an Agent Analytics feature that can connect AI-agent visits to the URLs appearing in its citation reports. Otterly

And if you're selling a large catalog, I'd prioritize prompt-level citation data over conventional keyword rankings. AI answers can cite different sources for the same underlying product question, and the useful insight is the recurring source ecosystem around your category.

If you tell me roughly how many products you have and whether you're on Shopify/WooCommerce/custom, I can recommend the best setup (including what prompts to track and how I'd structure the citation-domain report).

If your goal is specifically “Which domains are AI answer engines citing when people ask product/comparison/recommendation questions relevant to my store?”, I’d use an AI-visibility/citation platform, not a traditional SEO tool.

My shortlist

1. tryprofound.com — best for deep citation mapping

• Tracks the actual URLs/domains cited by answer engines.
• Lets you break citation share down by prompt, platform, topic, competitor, and source type.
• Particularly useful for discovering third-party domains that repeatedly influence answers about your products/category. Profound Profound Help Center
• I'd choose this if your objective is building a “who influences AI recommendations in my category?” map.
• otterly.ai — best if you're an ecommerce store

• It explicitly has AI Shopping Analytics, including which products/attributes/prices get surfaced and which retailers are mentioned.
• Its citation tracking records every cited URL and lets you compare your citations against competitors. Otterly
• It also tracks shopping-card results, which is especially relevant if you're selling physical products. Otterly
• scrunch.com — best for visualizing the citation ecosystem

• Its citation view can group results by domain or URL, then show which prompts and AI platforms produced those citations. Scrunch Help Center
• It also lets you distinguish owned, competitor, and third-party sources, which is useful for identifying PR/review sites you should pursue. Scrunch Help Center

What I'd actually build

For an online store, I'd create a dataset roughly like:

Then aggregate it into:

Domain → # citations → # prompts → engines → products/categories → competitors mentioned

That gives you a much more actionable picture than simply asking “Does ChatGPT mention my store?”

For example, you might discover:

rtings.com → 83 citations
reddit.com → 71
nytimes.com → 43
yourcompetitor.com → 38
yourstore.com → 11

Now you know where AI is getting its product knowledge, and consequently where your content/PR/review strategy should focus.

One particularly important point: don't restrict the analysis to domains that mention your brand. Recent Scrunch data says 87.2% of analyzed AI citations were third-party sources, versus 5.95% from brands' own sites. Scrunch So the valuable question is often “Which external sites are shaping the AI's answer about my category?”, not just “Who cites me?”

My recommendation

If you're choosing one tool, I'd start with OtterlyAI for an ecommerce store, because its combination of product/shopping tracking + prompt monitoring + citation tracking is closest to your use case. If your primary goal is deeper citation intelligence and mapping the source ecosystem, I'd lean Profound.

If you tell me what kind of products you sell + roughly how many SKUs, I can also suggest the exact prompt taxonomy I'd use to map your AI citations (e.g. “best X,” “X vs Y,” “alternatives to X,” “best X under $100,” “where to buy X,” etc.).

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask questions about products in my category?”, I’d use an AI-search visibility/citation platform, not traditional SEO software.

My picks

• Best overall: tryprofound.com — probably the strongest fit if you want to map the citation ecosystem. It tracks cited domains and URLs across prompts, lets you separate owned/competitor/earned-media sources, and shows citation share by platform, topic, and prompt. Profound Profound Knowledge Base
• Best for ecommerce/product-level analysis: peec.ai — particularly interesting for an online store because it has AI Shopping Analytics with SKU-level visibility, product placement, cited sources, attributes, prices, and where AI sends shoppers. Peec AI Peec AI
• Also consider Profound's Shopping product if your primary question is specifically “Are my SKUs appearing in ChatGPT Shopping, and what competitors/merchants are winning?” It tracks product visibility, SKU-level citations, shopping-triggering queries, attributes, and merchant/checkout presence. Profound

What I'd actually build for your store

I'd structure your tracking around commercial prompts, rather than just brand-name queries.

For example, if you sell running shoes, track questions like:

• “What are the best running shoes for flat feet?”
• “Best running shoes under $150”
• “Nike vs Brooks for long-distance running”
• “Best shoes for beginner marathon training”
• “What running shoes have the best cushioning?”
• “Where can I buy [specific product]?”
• “Best alternatives to [competitor product]”

Then create a dataset like:

The key metric isn't just “does AI mention my store?” It's citation share by domain: which websites repeatedly supply the information AI uses to answer buying questions in your category.

Profound explicitly provides Top Citation Domains/Pages and citation share, while Peec additionally categorizes sources and provides competitor citation-gap analysis. Profound Knowledge Base Peec AI

One particularly useful distinction

I'd track three separate things:

1. Brand/product mentions — does AI recommend your product?
2. Citations — which domains/URLs does AI use to substantiate the answer?
3. Shopping placement — does your actual SKU appear in AI shopping results, and where?

Those aren't the same thing. Peec, for example, distinguishes source usage/citations from brand mentions, while its shopping analytics goes down to SKU level. Peec AI Peec AI

If you're choosing one tool today, I'd start with Peec for a pure ecommerce use case, and Profound if your bigger objective is building an “AI citation map” for the entire category.

If you tell me what you sell + your approximate SKU count + whether you're on Shopify, I can lay out exactly how I'd set up the tracking, prompt taxonomy, and dashboard for your store.

If your goal is specifically “which domains are AI answer engines citing when people ask product-related questions?”, I’d use an AI visibility/citation tracker, not traditional SEO rank tracking.

My recommendation

Start with ahrefs.com if you already use Ahrefs, or want the broadest dataset.

It can track:

• ChatGPT, Perplexity, Gemini, Copilot, Google AI Overviews and AI Mode
• Which domains and individual pages get cited
• Your citation rate vs. competitors
• The exact prompts/questions producing the answers
• AI share of voice
• Custom buyer prompts, which is particularly useful for an ecommerce store
• The underlying search demand associated with prompts Ahrefs Help Center Ahrefs

For your use case, the really valuable report isn't just “does my store get mentioned?” It's:

For “best X,” “X vs Y,” “best X for [use case],” etc., which domains are AI engines citing, how frequently, and which pages are they citing?

Ahrefs specifically exposes top cited pages and domains, so you can build that map. Ahrefs Help Center

I'd structure your tracking like this

Then track something like:

AI engine → prompt → cited domain → cited URL → brand/product mentioned → competitor mentioned → citation frequency

That gives you a much more actionable picture than a generic “AI visibility score.”

Other tools I'd consider

• Profound — strongest choice if you're an enterprise ecommerce operation and want deep AI-search intelligence. It's considerably more expensive, but is built around large-scale AI visibility/citation analysis.
• Otterly.AI — good lower-cost option if you mainly want scheduled prompt monitoring and citation tracking.
• Peec AI — worth looking at for broader multi-engine monitoring and reporting.
• Semrush AI Toolkit — convenient if your SEO team already lives in Semrush.

Recent 2026 comparisons put the major options roughly into those buckets: enterprise/deep analytics (Profound), agency/team tracking (Peec), inexpensive monitoring (Otterly), and Ahrefs for large-scale AI visibility data. UX Continuum TechnologyAdvice

But there's one important distinction for an online store

I'd not only track whether your own domain is cited.

You want to build a “citation landscape”:

                    AI answer
                       │
        ┌──────────────┼──────────────┐
        ▼              ▼              ▼
   Your store      Review site     Reddit
        │              │              │
   product page    comparison       discussion
                       │
                 YouTube / media

For every commercial prompt, determine:

1. Which domains are being cited?
2. Which URLs on those domains?
3. How often does each domain appear?
4. Which competitors appear?
5. What claims are those sources providing to the AI?
6. Are the citations pointing to retailers, publishers, reviews, Reddit, manufacturers, etc.?

That last part is especially important. For product recommendations, the opportunity may not be “get my product page cited.” It might be “get my product reviewed/compared by the third-party sites that AI engines repeatedly trust.”

Ahrefs' current data, for example, shows how dominant third-party sources such as YouTube, Reddit, Wikipedia, Amazon and other large sites can be in AI citations. Ahrefs

If you tell me roughly what your store sells (e.g. supplements, furniture, apparel, electronics, specialty food), I can give you a concrete tracking schema—say 100–500 prompts—and the exact dashboard/columns I'd use to map your AI citation ecosystem.

Recent 2026 comparisons put the major options roughly into those buckets: enterprise/deep analytics (Profound), agency/team tracking (Peec), inexpensive monitoring (Otterly), and Ahrefs for large-scale AI visibility data.

But there's one important distinction for an online store

I'd not only track whether your own domain is cited.

You want to build a “citation landscape”:

If your goal is specifically to map which domains AI answer engines cite when shoppers ask product/category questions, I’d use a dedicated AI-search visibility platform rather than trying to build this from Google Search Console or GA4.

My picks

1. scrunch.com — best fit for your exact use case

• Tracks the actual URLs and domains cited in AI answers.
• Lets you group citations by domain or drill down to individual pages.
• Breaks them down by AI platform, prompt, topic, funnel stage, competitor, etc. Scrunch Scrunch Help Center
• Particularly useful for discovering third-party domains that repeatedly influence answers but don't mention your brand—e.g. review sites, publishers, Reddit, comparison sites, retailers, etc. Scrunch
• otterly.ai — best alternative

• Tracks citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude.
• Has a dedicated Website Citation Tracking view plus shopping analytics.
• You can see which URLs get cited, how often, and which competitors are being cited instead. Otterly
• Its newer citation reporting also lets you examine which prompts and engines produced each citation. Otterly

What I'd actually build

For an online store, don't just track:

"Does ChatGPT mention my store?"

Track a citation map like:

Then aggregate it into something like:

Citation Share by Domain

• reddit.com — 18%
• wirecutter.com — 12%
• yourstore.com — 9%
• competitor.com — 8%
• independentreviewsite.com — 7%
• other — 46%

That's much more actionable than an "AI visibility score."

One important distinction

I'd track three separate things:

• Mention share — how often your store/products are named in answers.
• Citation share — how often your pages are actually used as sources.
• Citation-source share — which other domains are shaping the answers.

The third one is especially interesting for ecommerce. Recent Scrunch data, for example, found that the overwhelming majority of AI citations in its dataset came from third-party sources rather than brands' own sites. Scrunch

That means your optimization strategy shouldn't just be "make my product pages more AI-readable." It should also be:

"Which 50 websites are repeatedly being trusted by AI for questions about my products, and how do I get my products represented accurately on those sites?"

If you tell me what you sell + roughly how many products you have, I can recommend a concrete tracking setup (prompts, engines, metrics, and dashboard structure) for your store.

If your goal is “which domains are AI answer engines citing when shoppers ask product questions?”, you want an AI visibility / AEO (answer engine optimization) citation tracker, not a traditional SEO rank tracker. These tools typically run a set of buyer prompts through engines like ChatGPT, Gemini, Perplexity, Claude, and Google AI surfaces, then extract cited domains and URLs. Citations Reputably

For an online store, I’d evaluate these options:

The dataset you actually want to build

Regardless of tool, I’d structure your map like this:

For product ecommerce, don’t just track “who cites me”

The more useful analysis is:

1. Citation share

• What percentage of AI answers cite your domain?
• What percentage cite competitors?
• Citation source map

• Which third-party domains repeatedly influence answers?
• Example: review sites, Reddit threads, comparison articles, marketplaces.
• Prompt clusters

Track questions like:

• “best [category]”
• “best [category] for [use case]”
• “[product A] vs [product B]”
• “is [product] worth it”
• “alternatives to [competitor]”
• Source gap analysis

Example:

• AI cites 15 review sites for your category.
• Your competitors appear on 10 of them.
• You appear on 2.
• Those 8 missing sources become outreach/content targets.

If you want to DIY it

A practical stack:

• Prompt database: Airtable / Google Sheets / Notion
• Answer collection: scheduled API runs where available, plus manual validation
• URL extraction: script that parses citations
• Dashboard: Looker Studio / Tableau / Metabase
• Analytics: GA4 with AI referral segmentation

For most stores, I’d start with a dedicated citation tracker rather than building from scratch, because the hard part is not storing domains — it’s consistently reproducing prompts across answer engines and capturing the cited sources. Triple Whale HubSpot Knowledge Base

A good first milestone: track 100–300 high-intent product prompts, then produce a ranked list of the top 50 domains AI trusts in your category and the top 20 domains where competitors appear but you don’t. That becomes an actionable GEO/AEO roadmap.

1. Citation share

• What percentage of AI answers cite your domain?
• What percentage cite competitors?
• Citation source map

• Which third-party domains repeatedly influence answers?
• Example: review sites, Reddit threads, comparison articles, marketplaces.
• Prompt clusters

Track questions like:

• “best [category]”
• “best [category] for [use case]”
• “[product A] vs [product B]”
• “is [product] worth it”
• “alternatives to [competitor]”
• Source gap analysis

Example:

• AI cites 15 review sites for your category.
• Your competitors appear on 10 of them.
• You appear on 2.
• Those 8 missing sources become outreach/content targets.

If you want to DIY it

A practical stack:

• Prompt database: Airtable / Google Sheets / Notion
• Answer collection: scheduled API runs where available, plus manual validation
• URL extraction: script that parses citations
• Dashboard: Looker Studio / Tableau / Metabase
• Analytics: GA4 with AI referral segmentation

For most stores, I’d start with a dedicated citation tracker rather than building from scratch, because the hard part is not storing domains — it’s consistently reproducing prompts across answer engines and capturing the cited sources.

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d use an AI citation/GEO monitoring platform, not a conventional SEO rank tracker.

My shortlist

For an online store, I'd probably start with OtterlyAI unless you're a large ecommerce operation where Profound's deeper analysis justifies the cost.

But here's the important part

Don't just track “Does AI mention my store?”

Build a dataset like:

Prompt
→ AI engine
→ answer
→ cited domain
→ cited URL
→ brand/product mentioned?
→ competitor mentioned?
→ product mentioned?
→ citation position
→ date

Then aggregate it into something like:

“Domains AI engines cite for my category”

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

In fact, current AI-search research increasingly distinguishes mentions from actual citations—a brand can be mentioned without being used as a source. Austin Heaton Machine Relations

I'd also segment your prompts

For an ecommerce store, I'd create 50–200 prompts across:

• Category discovery: “best running shoes for flat feet”
• Product comparison: “Nike Pegasus vs Brooks Ghost”
• Best-for: “best [product] under $150”
• Problem/solution: “what should I buy for…”
• Reviews: “is [product] worth it?”
• Retailer queries: “where can I buy [product]?”
• Alternatives: “best alternatives to [competitor]”
• Your products: “[product name] review”
• Competitor products: “[competitor] vs [your product]”

Then run those repeatedly rather than relying on one-off searches. AI answers aren't deterministic, so a single observation can be misleading.

The metric I'd care about most

I'd build a Citation Share by Domain metric:

Citation Share = citations from domain ÷ all citations observed for your target prompts

Then break it down by:

Engine × Product Category × Prompt Type × Domain × URL

That lets you answer questions like:

“For people asking AI about our $100–$200 hiking shoes, Reddit and OutdoorGearLab are generating 31% of citations, while our own site gets only 4%. Which pages on those sites are being cited, and what information are they providing that our product pages don't?”

That is the dataset I'd use to drive your AI-search strategy.

If you tell me what ecommerce platform you use (Shopify, WooCommerce, custom, etc.) and roughly how many products/categories you have, I can recommend the most practical setup—including whether I'd buy a tool or build the citation map yourself with an API.

I'd also segment your prompts

For an ecommerce store, I'd create 50–200 prompts across:

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d use an AI-search visibility platform, rather than trying to infer it from GA4 or traditional SEO tools.

My shortlist

• tryprofound.com — best for deep citation mapping. Its Answer Engine Insights has Top Citation Domains, Top Citation Pages, citation share, platform/topic/prompt breakdowns, and citation categorization. This is probably the closest match to the question you're asking. Profound Knowledge Base Profound
• otterly.ai — best if you're an ecommerce/marketing team that wants something easier to operate. It tracks citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude and Copilot, including the specific URLs/domains cited. It also has AI Shopping Analytics, which is particularly relevant for a store. Otterly Otterly
• peec.ai — strong alternative for source/citation intelligence. It reports the URLs and domains used by multiple AI engines and has a domain/URL gap analysis showing sources where competitors are cited but you aren't. Peec AI Peec AI

What I'd actually build for your store

Don't just track your brand name. Create a prompt set around the product questions customers are likely to ask AI:

• “Best [product category] for ___”
• “[Product A] vs [Product B]”
• “Best [product] under $100”
• “Where should I buy [product]?”
• “Best [product] for beginners/professionals/etc.”
• “[Category] alternatives to [competitor]”
• “Is [product] worth it?”
• “What are the best [category] brands?”

Then I'd make your dashboard essentially:

The domain-level view is especially valuable. For example, you might discover that AI answers for your category disproportionately cite Wirecutter, Reddit, specialist review sites, retailers, YouTube, etc. That tells you where your off-site authority/PR/content strategy should go—not merely what keywords to rank for.

Profound explicitly lets you classify sources into categories such as owned, competitor, earned media, PR, social, and institutional sources, while Otterly can show which URLs are being cited and whether your brand is mentioned on those pages. Profound Knowledge Base Otterly

My pick: start with Profound if citation/domain intelligence is the primary objective; start with OtterlyAI if you want citation tracking plus ecommerce/AI-shopping monitoring in a more general marketing workflow.

If you tell me what platform your store is on (Shopify, WooCommerce, BigCommerce, custom, etc.) and roughly how many products you have, I can recommend the best setup and exact prompt taxonomy I'd use.

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product-related questions?”, I’d use an AI-search citation monitoring platform, not traditional SEO software.

My picks

1. tryprofound.com — best for deep citation/source mapping

• Tracks citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, etc. Profound Profound
• Gives you Top Citation Domains and Top Citation Pages, so you can build a map of who AI engines trust in your product category. Profound Knowledge Base
• You can separate your domain, competitors, publishers, social sites, institutions, etc.
• Particularly good if you're trying to answer: “What sites do I need to get mentioned on if I want AI to recommend my products?”
• otterly.ai — best if you're an ecommerce operator

• Has explicit AI Shopping Analytics for products/retailers, alongside website citation tracking. Otterly
• Tracks the actual cited URLs and lets you see which prompts and engines produced those citations. Otterly
• Supports ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini, Claude and Copilot. Otterly
• I'd lean toward this if your primary question is “How are shoppers discovering/recommending products?”

What I'd actually map

Don't just track whether your store is cited. Build a dataset like:

Then aggregate it into:

AI citation landscape →

• Top 50 cited domains
• Citation share by domain
• Citation share by AI engine
• Citation share by product category
• Your URLs vs competitor URLs
• Publisher/review sites that repeatedly influence answers
• Questions where competitors are cited but you aren't
• Questions where nobody cites your category's authoritative sources

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

One important distinction

I'd specifically prioritize a tool that captures the actual citation URL, not merely brand mentions. AI engines can mention your brand while citing a completely different website. Profound explicitly exposes cited URLs and citation share; Otterly likewise provides cited URLs and lets you drill back to the prompts and engines that cited them. Profound Otterly

My recommendation: if you're building a serious AI-search intelligence system for an online store, start with Profound for the broader citation landscape, or OtterlyAI if product/shopping analytics is the central use case.

If you tell me what platform your store runs on (Shopify, WooCommerce, custom, etc.) and roughly how many products you have, I can also lay out the exact tracking architecture I'd use—including the prompt taxonomy, database schema, and dashboard to map these domains.

If your goal is “which domains are AI answer engines citing when shoppers ask product/category questions?”, you want an AI citation tracking / answer engine optimization (AEO) tool, not a normal SEO rank tracker. These tools run buyer prompts, collect AI answers, extract cited URLs, and aggregate them by domain. CitedSpy Profound

For an online store, I’d structure the stack like this:

Best-fit tools

1. Enterprise / serious ecommerce program

• tryprofound.com — strong for large brands; tracks which sources AI engines cite, competitor citation share, and source categories. Profound
• rankscale.ai — useful if you want dashboards around top cited domains, citation volume, categories, and competitor comparisons. Rankscale.ai

2. Lean teams that mainly need “who is AI citing?”

• citedspy.com — good for running product queries and seeing cited domains across major answer engines. CitedSpy CitedSpy
• usecite.ai — focuses on citation tracking across ChatGPT, Claude, Gemini, Perplexity, and Google AI surfaces. Cite AI
• trendos.com — built around identifying the sources AI trusts for customer queries. Trendos

What I would actually measure for an ecommerce store

Create a prompt library around your buying funnel:

Category discovery

Examples:

• “best running shoes for flat feet”
• “best espresso machines under $500”
• “top skincare brands for sensitive skin”

Track:

• Top cited domains
• Citation share by domain
• Which competitors appear
• Which review sites/listicles dominate

Product comparison

Examples:

• “Brand A vs Brand B”
• “best alternative to Product X”
• “is Product X worth it?”

Track:

• Which pages AI uses as evidence
• Whether comparison/review sites influence the answer
• Whether your product pages are ever cited

Problem-solving queries

Examples:

• “how to fix dry skin”
• “how to choose a mattress”
• “what features matter in a laptop”

Track:

• Educational publishers AI trusts
• Forums/community sites cited
• Guides that influence product recommendations

The database I’d build (even if using a tool)

Then rank domains by:

• Citation frequency
• Number of prompts where they appear
• Number of engines citing them
• Whether they mention your brand
• Whether they influence purchase decisions

If you want a simple starting setup

For most ecommerce teams:

1. Pick 50–200 real shopper prompts.
2. Run them weekly in one citation tracker.
3. Export cited URLs.
4. Group by domain.
5. Build a “AI authority map”: - Tier 1: domains cited everywhere
6. Tier 2: niche reviewers/blogs
7. Tier 3: competitors’ owned content
8. Tier 4: missing opportunities

The key insight is that the domains AI cites are often not the same as the pages ranking highest in Google; citation tracking gives you the source ecosystem shaping AI recommendations. CitedSpy

If you tell me your store category (fashion, supplements, electronics, home, etc.) and which engines matter (ChatGPT, Perplexity, Gemini, Google AI Overviews), I can suggest a concrete tracking schema and prompt set.

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product-related questions?”, I’d use a dedicated AI visibility / citation-tracking platform, not just Google Search Console or traditional SEO software.

My shortlist

• tryprofound.com — best for serious competitive citation mapping.

It tracks citations across ChatGPT, Perplexity, Google AI Overviews and other answer engines, then lets you break citation share down by platform, topic, prompt, domain and page. You can also classify sources as owned, competitors, earned media, social, institutions, etc. Profound Profound Knowledge Base

• otterly.ai — probably the easiest starting point for an ecommerce team.

It tracks cited URLs/domains across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot and Claude. Its AI Shopping Analytics is particularly relevant to an online store because it tracks how products appear in AI shopping results, including attributes, prices and competing retailers. Otterly Otterly

What I'd actually map

Don't just track “Is my store mentioned?” Build a citation map around your product/category queries:

Then create a table like:

Domain → Citation count → % citation share → Engine → Product/category → Prompt → Competitor mentioned → Your store mentioned → Specific URL cited

That's much more actionable than a generic AI visibility score.

The important distinction

I'd separate three things:

1. AI mentions — “Does the answer recommend my brand?”
2. AI citations — “Does the answer actually link to my site/product page?”
3. Citation ecosystem — “Which other domains does AI rely on to make the recommendation?”

The third one is the really interesting piece for your question. For example, you might discover:

42% of answers for your category cite review publications
27% cite Reddit
18% cite retailers
11% cite manufacturers
2% cite your own domain

That tells you where the AI's product knowledge is coming from, and therefore where your SEO/content/PR/outreach effort should go.

Profound explicitly provides a Top Citation Domains view and citation relationships, while Otterly provides searchable cited URLs/domains and competitive citation analysis. Profound Knowledge Base Otterly

What I'd choose

If you're a smaller/mid-size ecommerce operation: start with OtterlyAI because its coverage and shopping-specific reporting map closely to what you're trying to understand. Otterly

If AI search is becoming a major acquisition channel and you want a sophisticated competitive-intelligence system: I'd evaluate Profound. Its citation-share and source categorization capabilities are particularly suited to building the domain-level map you're describing. Profound Profound Knowledge Base

One caveat: don't optimize around one AI engine. Citation patterns differ substantially between engines, and recent changes can shift which sources get cited. Business Insider

If you tell me what your store sells and roughly how many product/category pages you have, I can suggest a concrete AI citation-tracking stack + dashboard schema + 50–100 prompts to build the map.

What I'd choose

If you're a smaller/mid-size ecommerce operation: start with OtterlyAI because its coverage and shopping-specific reporting map closely to what you're trying to understand.

For an online store, you want an AI citation tracking / answer engine optimization (AEO) tool, not a normal SEO rank tracker. The thing to map is:

“When shoppers ask AI engines which product should I buy?, which domains and URLs do those engines cite?”

Citation tracking tools are designed for exactly this: they collect the cited URLs from AI answers, group them by domain, and show which sources influence recommendations. Profound CitedSpy

Tools I’d shortlist

For an ecommerce store, I would build the dashboard around these metrics

1. Citation share by domain

Example:

This tells you who is shaping AI recommendations.

2. Citation share by product category

Do not track only your brand name. Track buyer prompts:

• “best running shoes for flat feet”
• “best noise cancelling headphones under $300”
• “best espresso machine for beginners”
• “alternatives to [competitor]”
• “is [product] worth it?”

Then record:

• AI engine
• prompt
• answer
• cited domains
• cited URLs
• whether your product appeared
• whether your site was the source or just mentioned

3. Domain type breakdown

Classify citations:

• Review publishers
• Reddit/forums
• YouTube
• Retailers
• Manufacturer sites
• Blogs
• News/editorial
• Your own site

This tells you where to invest. For many ecommerce categories, the winning sources are often third-party reviews, comparisons, and community discussions rather than product pages alone. Linkeddit

If you want to build it yourself

A simple stack:

• Prompt database: Airtable / BigQuery / Postgres
• Scheduled runs: API calls or browser automation against AI engines
• Extraction: parse citations and URLs
• Enrichment: classify domains (publisher, retailer, forum, competitor)
• Dashboard: Looker Studio, Metabase, Tableau, or Power BI

Your core table should look like:

date
engine
prompt
product_category
answer_text
citation_url
citation_domain
domain_type
brand_mentioned?
product_mentioned?
competitor?

My practical recommendation

• Small store: start with Otterly.AI or Rankscale and track 100–300 high-intent shopping prompts. GetIntel Rankscale.ai
• Growing ecommerce brand: use Profound-style tooling because competitor citation analysis becomes the valuable part. Profound
• Large catalog (thousands of SKUs): build a custom pipeline so you can map citations by category, SKU, and margin.

The biggest mistake is measuring “does ChatGPT mention my brand?” The more actionable metric is “which domains are getting cited instead of me, and what content made them citation-worthy?” honeyb.ai

If your goal is specifically to map which domains AI answer engines cite for product-related questions, I’d use an AI visibility/citation tracking platform, not a traditional SEO tool.

My shortlist

• otterly.ai — best fit for a practical ecommerce setup. It tracks citations and mentions across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and lets you see the actual cited URLs/domains, citation trends, competitors, and shopping-result data. Otterly Otterly
• tryprofound.com — best for deeper competitive/source analysis. Its Citation dashboard ranks the domains and pages being cited, lets you classify sources (owned, competitor, media, social, etc.), and analyze citation share by engine/topic/prompt. Profound Profound Knowledge Base
• peec.ai — strong alternative, especially for source-gap analysis. It identifies the domains/URLs influencing AI answers and can show sources where competitors are cited but you aren't. It also has specific AI shopping/AI Mode visibility capabilities. Peec AI Peec AI

For an online store, I'd structure it like this

Don't just track:

"Is my store mentioned?"

Track the entire citation ecosystem for your product category.

For example, create prompt groups such as:

• "best running shoes for flat feet"
• "best running shoes under $150"
• "Nike vs Hoka for marathon training"
• "best [your product category] for beginners"
• "where should I buy [product]?"
• "best [product] alternatives to [competitor]"
• "is [product] worth it?"

Then build a table like:

The interesting metric isn't necessarily your own citation count. It's:

Which domains repeatedly get cited when AI answers questions that could lead to a purchase?

That tells you where AI systems are getting their product knowledge.

What I'd pick

If you're a typical ecommerce team and want to get this running quickly, start with OtterlyAI. Its citation reporting is explicitly designed around domains/URLs, prompts, engines, competitors, and AI shopping results. Otterly Otterly AI

If you're doing this as a serious GEO/AEO research project and want to answer questions like "Why is AI citing these 30 sites instead of us, and which ones should we pursue?", I'd lean toward Profound because its citation categorization and citation-relationship analysis are particularly useful for that. Profound Profound Knowledge Base

One important caveat: AI citations change substantially over time and across engines, so I'd collect the data longitudinally rather than treating one day's answers as the definitive source map. Recent research has shown substantial shifts in which sites AI systems cite. Business Insider

If you tell me what kind of products your store sells, I can also give you a concrete prompt taxonomy + citation-domain tracking schema I'd use to map your category.

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions relevant to my store?”, I’d use a dedicated AI-search visibility/citation platform, not Google Search Console or traditional SEO software.

My picks

1. otterly.ai — best fit for what you described

• Tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude.
• Lets you see every cited URL/domain, not just whether your brand was mentioned.
• You can break citations down by prompt and AI engine and compare against competitors.
• It also has AI shopping analytics, including which products/retailers AI surfaces. Otterly Otterly AI
• This is probably where I'd start for an online store.
• scrunch.com — particularly interesting for ecommerce

• Its Shopping product is explicitly designed around product-level AI visibility: which products appear, where they rank, how that changes, and which prompts drive visibility. Scrunch
• Its Citations view lets you group citations by domain or individual URL, then see which AI platforms are citing them. Scrunch Help Center
• It also has site mapping that connects your individual pages with citations, AI-agent traffic and referrals. Scrunch
• tryprofound.com — strongest for deeper enterprise-grade analysis

• Tracks which sources answer engines cite, citation frequency, competitors and source categories.
• Particularly useful if you want to turn the citation data into a content/PR/outreach strategy. Profound Profound Knowledge Base

What I'd actually build for your store

I'd structure the tracking around product-intent prompts, rather than simply tracking your brand name.

For example, if you sell running shoes:

Then I'd want a dataset like:

Prompt → AI engine → answer → cited URL → cited domain → source type → product mentioned → competitor mentioned → citation frequency

That lets you answer much more useful questions such as:

“For 500 high-intent shopping questions, which 50 domains are most frequently cited by AI?”

and:

“AI engines cite Runner's World 312 times for our category, but our store appears on only 4 of those pages.”

That's where the strategy gets interesting. Recent citation research suggests that third-party sources are disproportionately important: Scrunch reports that 87.2% of the citation events in its dataset came from third-party sources, versus 5.95% from brands' own sites. Scrunch

So I wouldn't just measure “Does ChatGPT cite my store?” I'd build a citation landscape showing:

• Top cited domains
• Top cited URLs
• Citation share by AI engine
• Citation share by product/category
• Competitor vs. your domain
• Which publishers/review sites are repeatedly cited
• Which Reddit/forums/media sites appear
• Which prompts produce citations
• Which of your product pages get cited
• Which high-value prompts have zero visibility for you

For an ecommerce store, I'd trial OtterlyAI and Scrunch side-by-side. Otterly looks stronger if your primary question is “map the citation ecosystem across AI engines,” while Scrunch is especially compelling if you want to connect that to “which individual products are winning AI shopping results.” Otterly Scrunch

If you tell me what you sell + roughly how many SKUs you have, I can also lay out the exact tracking schema and prompt set I'd use to build this as an AI citation map/dashboard.

That lets you answer much more useful questions such as:

“For 500 high-intent shopping questions, which 50 domains are most frequently cited by AI?”

and:

“AI engines cite Runner's World 312 times for our category, but our store appears on only 4 of those pages.”

That's where the strategy gets interesting. Recent citation research suggests that third-party sources are disproportionately important: Scrunch reports that 87.2% of the citation events in its dataset came from third-party sources, versus 5.95% from brands' own sites.

So I wouldn't just measure “Does ChatGPT cite my store?” I'd build a citation landscape showing:

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions relevant to my store?”, I’d use a dedicated AI-search visibility / GEO platform, rather than trying to reconstruct this from Google Search Console.

My top picks

1. tryprofound.com — best for deep citation/domain mapping

This is probably the strongest fit if your main question is “Who is AI citing, and why?” Profound tracks citation share, top citation domains and pages, and lets you categorize sources as owned, competitors, earned media, social, institutions, etc. Profound Profound Knowledge Base

For an online store, I'd build reports like:

• Product: best running shoes for flat feet
• Category: best running shoes under $150
• Comparison: Nike vs Hoka for walking
• Attribute: best waterproof hiking shoes
• Brand: best alternatives to [your brand]

Then map AI engine → prompt → cited domain → cited URL → product/brand mentioned.

2. otterly.ai — best practical/accessible option

Otterly explicitly tracks the URLs and domains cited in AI answers, including ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude and Copilot. It also has shopping analytics for seeing which products and retailers AI surfaces. Otterly Otterly

This is particularly interesting for ecommerce because it can answer not just “is my domain cited?”, but “which retailers/products are AI recommending when shoppers ask this question?” Otterly

3. Build your own dataset if you want maximum control.

For a sophisticated ecommerce team, I'd actually consider this alongside one of the above. Maintain a database with:

You can then calculate citation share by domain, citation share by product category, competitor citation overlap, and domains that consistently influence AI answers.

The metric I'd focus on

Don't make brand mentions your primary metric.

For ecommerce, I'd create a Citation Landscape:

For each high-value shopping prompt, what domains and URLs are being used as evidence by AI?

Then rank domains by:

Citation Share × Relevance × Commercial Intent

That gives you something much more actionable than an overall “AI visibility score.”

For example, you might discover:

"best trail running shoes"

REI                 24% of citations
Runner's World      18%
Reddit              14%
YourStore.com        6%
Wirecutter            5%
Amazon                4%
Competitor A          4%
...

That tells you something strategically useful: AI isn't necessarily getting its product knowledge from the sites that rank highest on Google.

And this is changing quickly—the recent volatility in which domains AI engines cite (including a substantial recent shift in Reddit citations) is a good reason to track the actual citation sources over time rather than assume today's source mix will persist. Business Insider Axios

What I'd choose

If you're a normal ecommerce/SEO team: start with OtterlyAI.

If you're doing serious GEO/AEO strategy and want source-level competitive intelligence: choose Profound.

If you're a large store with data/engineering resources: use one of those for collection, export the citation data, and build your own AI Citation Domain Map in Looker Studio/BigQuery.

If you tell me what ecommerce platform you use (Shopify, WooCommerce, custom, etc.) and roughly how many products/categories you have, I can suggest the exact tracking architecture and the ~50–100 prompts I'd start monitoring.

If your goal is specifically “Which domains are AI answer engines citing when people ask product-related questions in my store’s category?”, I’d use a dedicated AI-search/GEO visibility platform, rather than trying to infer it from Google Analytics.

My pick: OtterlyAI

otterly.ai is probably the best fit for what you described.

It can track prompts across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot, and Claude, then show the actual URLs/domains cited in the answers. Its citation reporting lets you filter by domain, URL, engine, prompt, and date. Otterly Otterly

For an ecommerce store, I'd structure it around queries such as:

• “best [product category]”
• “[product] alternatives”
• “best [product] for [use case]”
• “[product A] vs [product B]”
• “where to buy [product]”
• “most reliable [product category]”
• “best [product category] under $X”
• “[product category] for beginners”
• “what should I look for when buying [product]?”

Then look at Top Citation Domains rather than just whether your own brand appears.

That gives you a dataset roughly like:

That is much more actionable than a generic “AI visibility score.” Otterly specifically exposes every cited URL, its domain, citation count, and whether your brand is mentioned on that source. Otterly Otterly

The other one I'd seriously consider: Profound

tryprofound.com is arguably the stronger choice if you want to turn this into a more sophisticated enterprise AEO/GEO program.

Its Citation Intelligence specifically provides Top Citation Domains, Top Citation Pages, citation share, citation categories, and citation relationships, and lets you break the data down by platform, topic, and prompt. Profound Profound Knowledge Base

One feature I particularly like for ecommerce is the ability to classify sources as owned, competitor, earned media, social, institutional, etc. That lets you answer not merely:

“Who is AI citing?”

but:

“Are AI engines getting their product information from retailers, publishers, Reddit, competitors, manufacturers, review sites, or our own product pages?”

That's the strategic question I'd care about.

What I'd choose

Small/mid-sized ecommerce team → OtterlyAI.
It's more directly oriented around prompt monitoring + citation/domain tracking, and it also has shopping analytics for seeing which products and retailers ChatGPT surfaces. Otterly

Larger SEO/content team → Profound.
I'd favor it if you want deeper analysis of citation share, source categories, competitive gaps, and content/outreach workflows. Profound Profound

One important distinction

Don't just track your domain's citations.

Build a dataset of all domains cited for commercial/product-intent prompts, because the really valuable insight is often:

“AI engines cite these 30 domains repeatedly when answering questions in our category, but our brand appears on only 4 of them.”

Those 30 domains become your AI influence map—potential review sites, comparison publishers, Reddit communities, retailers, manufacturers, editorial sites, etc.

If you tell me what you sell + roughly how many product categories/SKUs you have, I can also suggest the exact prompt taxonomy and dashboard/KPIs I'd use to map your AI citation landscape.

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d look at an AI visibility / GEO platform, not traditional SEO rank tracking.

My picks

1. tryprofound.com — best for citation-domain research

• Tracks citations across ChatGPT, Perplexity, Google AI Overviews and other answer engines.
• Gives you Top Citation Domains, Top Citation Pages, citation share, competitors, topics, prompts, and platforms. Profound Profound Knowledge Base
• Particularly useful if your question is: “For ‘best running shoes for X’ queries, what domains does AI consistently cite?”
• You can also segment citation sources into owned, competitors, earned media, social, institutions, etc. Profound Knowledge Base
• Profound also has SKU-level analysis for ChatGPT Shopping, which makes it interesting for an online store. Profound
• peec.ai — probably the strongest alternative for ecommerce

• Explicitly tracks the URLs and domains AI engines use and cite.
• Covers ChatGPT, Google AI Mode/Overviews, Gemini, Perplexity, Copilot and others. Peec
• Its source-gap analysis is especially useful: you can identify domains that cite your competitors but don't cite you. Peec
• It also has dedicated AI Shopping Analytics, including product visibility, win rate, position, quoted price and product attributes. Peec
• ahrefs.com — good if you already use Ahrefs

• Its Brand Radar distinguishes between pages that are actually cited and pages that AI merely retrieved/found. That's an important distinction for this use case. Ahrefs Help Center
• I'd choose it if you want AI citation data integrated with your existing SEO workflow rather than building a dedicated GEO stack.

What I'd actually build for an online store

Don't just track your domain's citations. Build a dataset like:

Then aggregate it into:

• Top cited domains by product category
• Top cited domains by AI engine
• Domains citing competitors but not you
• Your citation share vs. competitors
• Most-cited individual URLs
• Citation trends over time
• Commercial/transactional prompts specifically
• Product-level visibility and recommendation position

That last point matters: Peec's research specifically recommends separating commercial and transactional prompts, since those are much more relevant to product consideration and purchase intent. Peec

My recommendation

For an ecommerce store, I'd start with Peec AI if product-level/AI-shopping analytics is the priority, and Profound if your primary job is understanding the broader citation ecosystem and deciding which domains you need to get mentioned on.

If you're trying to answer something like “For my 500 most valuable product queries, what are the 100 domains AI trusts most, and where are my citation gaps?”, I'd lean Profound or Peec rather than Ahrefs. Both are much closer to that exact workflow. Profound Knowledge Base Peec

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d use a dedicated AI-search visibility platform rather than trying to infer it from Google Search Console or traditional SEO tools.

My picks

1. Profound — best for serious ecommerce/competitive analysis

This is probably my first choice if you're building an actual AI citation map.

Profound lets you track prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot and others, then see the specific URLs and domains cited, citation share, competitors, and source categories. www.tryprofound.com

For an online store, I'd structure it around prompts like:

• “best running shoes for flat feet”
• “best [product category] under $100”
• “[product type] for beginners”
• “[competitor] vs [your product]”
• “best [product category] for [use case]”
• “where should I buy [product]?”
• “[product] alternatives”
• “best brands for [category]”

Then build a dataset like:

The particularly useful thing is that Profound exposes Top Citation Domains, Top Citation Pages, Citation Share, and citation relationships, so you can identify not just who cites you, but which third-party sites are influencing AI answers in your category. help.tryprofound.com

2. OtterlyAI — best simpler/leaner option

OtterlyAI is worth looking at if you want something more straightforward. It tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude and Copilot, and specifically exposes every cited URL, citation frequency, domain, competitors, and whether your brand appears on the cited page. otterly.ai

It also has AI Shopping Analytics, which is particularly relevant for a store: it tracks products/retailers surfaced when buyers ask shopping questions. otterly.ai

What I'd actually build

Don't just track your domain's citations. That's too narrow.

I'd create an AI Citation Landscape with four layers:

Layer 1 — Buyer prompts
500–2,000 natural-language shopping questions across your important categories.

Layer 2 — Answer engines
ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, etc.

Layer 3 — Citation domains
For every answer, extract:

engine → prompt → cited URL → domain → page type → brand mentioned → competitor mentioned

Layer 4 — Opportunity scoring

Then rank domains by something like:

Opportunity = citation frequency × relevance × competitor presence × your absence

That gives you a much more actionable output than “our brand has 18% AI visibility.”

For example:

Reddit — 127 citations
43% of relevant answers
Your brand mentioned in only 8%
Competitor A mentioned in 31%
→ High-priority influence source

That tells your SEO/content/PR team where AI is getting its product knowledge, and therefore where you need to improve your own content or earn third-party coverage.

One important distinction

I'd separate “AI cites my store” from “AI cites a site that influences whether my store gets recommended.”

The second one is arguably more valuable.

If AI consistently cites Wirecutter, Reddit, specialist review sites, retailers, forums, etc. for your product category, those domains become your AI influence graph. Profound's citation categorization is designed for exactly this kind of analysis, including owned, competitor, earned media, social, institutional and other sources. help.tryprofound.com

So my short answer: start with Profound if you want the deepest mapping; use OtterlyAI if you want a simpler, more approachable implementation. For a product-heavy ecommerce site, I'd lean Profound + your own warehouse/dashboard once you know the dimensions you care about.

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product-related questions?”, I’d use a dedicated AI-search visibility platform rather than trying to build this from traditional SEO tools.

My top picks

1. tryprofound.com — best for serious ecommerce/AEO analysis

• Tracks citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok and others. Profound
• Gives you Top Citation Domains and Top Citation Pages, so you can answer “Which sites are influencing AI answers in my category?” Profound Knowledge Base
• Lets you categorize citations as owned, competitors, earned media, social, institutions, etc.
• Particularly interesting for a store because Profound has a Shopping Dashboard for product visibility and shopping environments. Profound Knowledge Base
• otterly.ai — best if you want straightforward citation/domain reporting

• Tracks the actual cited domains and URLs across AI search experiences.
• Its citation report lets you drill from a prompt → AI response → exact cited URL. Otterly AI
• You can export the data and build your own reporting.
• It also tracks shopping cards, which is useful for product queries. Otterly AI

What I'd actually map

For an online store, don't just track whether your domain gets cited. Build a matrix like:

Then aggregate it into something like:

Top domains cited for your category

• Your store — 18%
• Reddit — 12%
• Wirecutter — 9%
• Amazon — 8%
• Competitor A — 7%
• YouTube — 6%
• Specialist review site — 5%

That tells you something much more actionable than an ordinary “AI visibility score”: where AI is getting its product knowledge from and which third-party sources you need to earn mentions on.

This is increasingly important because citation patterns can move substantially over short periods; recent data, for example, showed Reddit's share of ChatGPT citations changing significantly within weeks. Axios

What I'd choose

If you're running a meaningful ecommerce operation: Profound.

If you mainly want a clean, cheaper-feeling citation/domain monitoring workflow: OtterlyAI.

And I'd structure your prompt set around actual shopping questions, not just your product keywords:

• “What are the best [product] for [use case]?”
• “[Product A] vs [Product B]”
• “Best [product] under $X”
• “Where can I buy [product]?”
• “Best [product] for [customer type]”
• “Is [your product] worth it?”
• “Alternatives to [competitor]”
• “Best brands for [category]”
• “What should I look for when buying [category]?”

That gives you a much better picture of the domains AI engines trust at each stage of the buying journey.

If you're running a meaningful ecommerce operation: Profound.

If you mainly want a clean, cheaper-feeling citation/domain monitoring workflow: OtterlyAI.

And I'd structure your prompt set around actual shopping questions, not just your product keywords:

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product questions in my category?”, I’d use an AI-search visibility/citation platform, not traditional SEO rank tracking.

My top picks

1. Peec AI — probably the best fit for your use case

Peec is particularly good if you want to build a dataset of domains and URLs cited for product/category prompts. It tracks sources and citations across ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot and others, and lets you distinguish between sources the model used and URLs it explicitly cited. peec.ai

For example, you could track prompts like:

• “best running shoes for flat feet”
• “best [your product category] under $100”
• “[product type] for beginners”
• “Brand A vs Brand B”
• “best alternatives to Brand A”
• “where should I buy [product]?”

Then analyze:

Prompt → AI engine → cited URL → domain → competitor/owned/UGC/editorial → citation frequency

That is much closer to the dataset you're describing.

2. Profound — best for a more enterprise/AEO workflow

Profound has particularly strong citation analysis. It can show citation share, cited domains, specific citation pages, competitors, prompts, platforms and regions. www.tryprofound.compeec.ai

Its citation categorization is also useful for ecommerce because it separates things such as owned sites, competitors, social, earned media, PR, institutions and other sources. help.tryprofound.com

What I'd actually build for an online store

I wouldn't just track “Does AI mention my store?”

I'd create a Citation Landscape with something like:

The really valuable metric is competitor citation gap:

“For the 500 product questions we care about, these 37 domains are repeatedly cited by AI, but our store/products aren't represented there.”

Peec explicitly provides domain/URL-level source analysis and gap analysis, while Profound provides citation-page and citation-domain analysis. www.tryprofound.compeec.ai

One important distinction

I'd track sources and citations separately.

A source can influence an AI answer without appearing as a visible citation. Peec explicitly distinguishes the two: sources are URLs accessed/used in generating the response, while citations are URLs explicitly referenced in the answer. peec.ai

For ecommerce, that's extremely useful because you can discover:

“AI is learning about my products from these 15 domains”

rather than merely:

“AI linked to my site 3 times.”

My recommendation

If you're an ecommerce/SEO team trying to understand where to get cited, I'd start with Peec AI.

If you're building a larger enterprise AEO program with extensive prompt, citation, competitive and workflow analysis, I'd evaluate Profound alongside it.

And I would not make traditional Google Search Console/GA4/SEMrush-style reporting the centerpiece. Those can tell you what happens after someone reaches your site, but they don't give you the AI citation graph you're trying to map.

If you tell me what kind of products you sell and roughly how many product/category pages you have, I can suggest the exact prompt taxonomy and dashboard I'd use to map your AI citation landscape.

If your goal is specifically “which domains are AI answer engines citing when people ask product-related questions?”, I’d use an AI visibility / citation-tracking platform, rather than trying to infer it from Google Analytics.

My picks

1. Profound — best if citation/domain mapping is the priority

Profound

Profound has a dedicated Top Citation Domains view that ranks the domains most frequently cited in AI answers, plus Top Citation Pages, citation share, platform breakdowns, and citation categories such as owned sites, competitors, earned media, social, and institutions. www.tryprofound.com

For an online store, I'd structure it around prompts like:

• “best [product category] for [use case]”
• “[product type] alternatives”
• “[product] vs [competitor]”
• “best [product] under $X”
• “where should I buy [product]?”
• “best brands for [category]”
• “is [your product] worth it?”
• “best [category] for [specific customer]”

Then look at domain → URL → prompt → engine.

That lets you answer questions like:

“For 200 product-discovery prompts, Reddit is cited 18%, Amazon 14%, Wirecutter 8%, competitor sites 7%, our store 3%.”

That's much more actionable than simply knowing whether your brand was mentioned.

2. Peec AI — probably the strongest alternative for a marketer-friendly workflow

Peec AI

Peec explicitly tracks sources and citations at the URL/domain level across ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot and other engines. It also has citation gap analysis, showing sources where competitors are cited but you aren't. peec.ai

That gap analysis is particularly interesting for ecommerce because you can turn it into an outreach/content list:

What I'd actually build

For your store, I'd create a “AI Citation Landscape” rather than just an AI rank tracker.

Track these dimensions:

Prompt
→ “best running shoes for flat feet”

Answer engine
→ ChatGPT / Gemini / Perplexity / Google AI Mode / etc.

Cited domain
→ reddit.com / nytimes.com / yourstore.com / competitor.com

Cited URL
→ exact article/product/category page

Source type
→ retailer / review site / editorial / UGC / competitor / owned

Brand mentioned?
→ yes/no

Product mentioned?
→ which SKU/product

Position
→ where your product appears in the answer

Citation frequency
→ % of responses citing that domain

Competitor gap
→ domains citing competitors but not you

That gives you something much more useful than “our AI visibility score went from 21 to 24.”

One important distinction

Don't only track your own domain citations.

The really valuable dataset is:

“What sources does AI trust for my category?”

For example, if you discover that AI engines repeatedly cite:

• 35% specialist review sites
• 22% Reddit
• 15% major retailers
• 12% YouTube
• 9% comparison sites
• 7% manufacturers

…then you've learned where your ecommerce brand needs to earn presence, not merely how your own website is performing.

Profound specifically supports this kind of citation-source categorization and citation-share analysis. www.tryprofound.com

My recommendation: start with Profound if the primary job is mapping the citation ecosystem, and Peec AI if you want a particularly straightforward domain/URL citation + competitor-gap workflow. I'd trial both with the same 50–100 product prompts before committing.

If you tell me roughly what you sell and how many product/category pages you have, I can also suggest the exact prompt taxonomy and dashboard schema I'd use for your store.

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product-related questions?”, I’d use a dedicated AI-search visibility platform rather than trying to infer it from GA4 or traditional SEO tools.

My top picks

1. Scrunch — probably the best fit for an online store

Scrunch has a dedicated Shopping product and lets you track product-related prompts across AI platforms, competitors, and citations. Its citation reporting can be grouped by domain or URL, and you can see which third-party sites are repeatedly influencing AI answers. scrunch.comhelp.tryprofound.com

For example, you could monitor prompts like:

• “Best running shoes for concrete”
• “Best X under $100”
• “X vs Y”
• “Where should I buy X?”
• “Best [product category] for beginners”

Then get something like:

That is much closer to the dataset you're describing than conventional SEO rank tracking. Scrunch explicitly supports filtering citations by platform, topic, prompt, and citation owner. ai-cdn.scrunchai.com

2. Profound — strongest alternative

Profound's Answer Engine Insights has a particularly good citation-analysis model. It reports Top Citation Domains, Top Citation Pages, citation share, and citation relationships, and lets you break results down by platform, topic, and prompt. www.tryprofound.com

It's especially interesting if you're doing this as an AEO/SEO strategy, because you can distinguish:

• your own domains
• competitors
• earned media
• publishers
• social
• institutions
• other sources

That lets you answer not just “who gets cited?” but “what kinds of sites does AI trust for this product category?” www.tryprofound.com

What I'd actually build

For an ecommerce store, I'd make the core dataset:

Prompt → AI engine → products mentioned → citations → cited domain → cited URL → brand mentioned? → competitor mentioned? → position

Then aggregate it into:

1. Top cited domains by product category
2. Top cited URLs
3. Citation share by domain
4. Your citation share vs competitors
5. Domains that frequently cite competitors but not you
6. AI engine × domain matrix
7. Citation trends over time
8. Non-branded shopping prompts specifically

That last one is important. "best hiking boots" is much more strategically useful than "yourbrand hiking boots" because it tells you who is shaping the recommendation set before the shopper has decided on a brand.

Scrunch vs. Profound

My recommendation: start with Scrunch if your primary question is “which websites are influencing AI recommendations for our products?” Its shopping-specific tooling makes it particularly well aligned with an online store. scrunch.com

If you're building a more sophisticated AI-search intelligence program across SEO, PR, content, competitors, and multiple markets, I'd evaluate Profound alongside it. www.tryprofound.com

One important caveat: don't treat the resulting domain percentages as universal “AI authority scores.” They're measurements of the specific prompts and engines you're monitoring; different prompts can produce very different citation sets. Profound and Scrunch both essentially use prompt-driven monitoring for this reason. scrunch.comhelp.tryprofound.com

If you tell me what ecommerce platform you use (Shopify, WooCommerce, Magento, custom, etc.) and roughly how many products you have, I can suggest the most practical setup and the exact data model I'd use.

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d use a dedicated AI-search visibility/citation platform, rather than trying to infer it from Google Search Console.

My shortlist

1. Profound — best for serious competitive research

This is probably my first choice if you're building an actual AI-search measurement program. It lets you define your own product-related prompts and see:

• Top cited domains and individual URLs
• Citation share by domain
• Which competitors are being cited
• Citation performance by engine, topic, and prompt
• Categories such as owned, competitor, media, social, etc.
• Citation relationships between sources and answer engines www.tryprofound.comhelp.tryprofound.com

The particularly useful metric for your use case is Top Citation Domains: you can essentially build a leaderboard of “What websites are AI engines trusting to answer questions about my product category?” www.tryprofound.comhelp.tryprofound.com

2. OtterlyAI — best if you want something simpler / more accessible

Otterly is very strong for this exact workflow too. It tracks citations across ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini and Copilot, and lets you drill from a prompt into the actual cited URLs and domains. otterly.ai

It also supports CSV exports and has a Looker Studio connector, which is useful if you want to build your own reporting layer. otterly.ai

What I'd actually build for an online store

Don't just track your brand. Build a prompt universe around your products:

Then aggregate every citation into something like:

Domain → citations → % of citations → engines → prompts → products/categories

That gives you a much more actionable view than simply asking “Does ChatGPT mention my store?”

For example, you might discover:

Reddit → 18%
Wirecutter → 12%
Your competitor A → 9%
Amazon → 8%
YouTube → 7%
Your store → 2%

That immediately tells you that your AI visibility problem may be an off-site authority problem, rather than a product-page SEO problem.

Profound explicitly recommends using its top-cited-domain/page data this way: if competitors and third-party publishers dominate the citations, pursue an off-page strategy; if your own pages are appearing, optimize and protect those pages. www.tryprofound.com

One important distinction

I'd track three separate things:

1. Brand visibility — does the AI mention your store/product?
2. Citation share — does the AI actually cite your domain?
3. Citation ecosystem — which other domains are influencing the answer?

#3 is the interesting one for your question. It can reveal the websites you should potentially pursue for reviews, comparisons, listings, PR, affiliate coverage, Reddit/community presence, etc.

If I were choosing today:

• Profound if this is a strategic/enterprise project and you want deep competitive analysis.
• OtterlyAI if you're a smaller ecommerce team and want to get this running quickly with strong citation/domain reporting.

If you tell me what kind of store/products you sell and roughly how many SKUs, I can also lay out the exact tracking schema I'd use—including the prompts, domains, KPIs, and dashboard structure.

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product questions?”, I’d use an AI visibility/citation tracker, but I’d choose one that exposes the actual cited URLs/domains, not just whether your brand was mentioned.

My shortlist

Current 2026 comparisons generally put Otterly toward the lower-cost end, Peec in the mid-market/self-serve range, and Profound toward enterprise; pricing and capabilities change, so I'd verify before buying. www.aeolabs.ai

But here's the important part

For an online store, don't make “brand mentions” your primary metric.

I'd structure your measurement around:

Product query → AI engine → cited domains → cited URLs → product/brand mentioned → competitor cited → position/context

For example:

“What are the best noise-cancelling headphones under $300?”

You want to know:

• ChatGPT → RTINGS → specific review URL
• ChatGPT → Reddit → specific thread
• Perplexity → Wirecutter → specific article
• Gemini → your product page
• Google AI → Best Buy → product page
• etc.

This matters because recent research suggests a large proportion of citations in product-related answers come from third-party sources rather than the manufacturer's own site. One 2026 citation study found 79% of citations across Perplexity, Gemini and Claude pointed to third-party domains. bevisibleiq.com

So your real competitive question becomes:

“Which external websites are teaching AI engines to recommend my competitors' products instead of mine?”

That's considerably more useful than simply asking whether your store is mentioned.

What I'd build for your store

I'd start with 50–100 high-intent shopping prompts, grouped into:

1. Best-of: “best X for Y”
2. Comparison: “X vs Y”
3. Alternative: “alternatives to [competitor product]”
4. Problem/need: “best X for [use case]”
5. Budget: “best X under $100”
6. Specific product: “[product] review / is [product] worth it?”
7. Gift: “best X gift for…”
8. Category discovery: “what should I buy for…”

Then run them across ChatGPT, Perplexity, Gemini and Google AI surfaces and aggregate the citations by domain.

Your resulting dashboard should look something like:

That gives you a “citation ecosystem map”: not merely where you rank, but which sources AI considers authoritative in your category.

For your particular use case, I'd test eCommerceInsights.AI and LLMly first. The former is unusually focused on ecommerce/SKU-level citation tracking, while LLMly explicitly exposes top cited domains and URLs and is designed around citation analysis. ecommerceinsights.ai

One other useful distinction: track the cited URL, not just the domain. rtings.com being cited tells you something; knowing which RTINGS review is being cited tells you what type of evidence you need to compete with.

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d use an AI-search visibility platform rather than a traditional SEO rank tracker.

My shortlist

For your particular use case, I'd start with Peec AI or Profound.

The important distinction is that you don't just want to know “does my store appear in ChatGPT?” You want a dataset like:

Prompt                         Engine       Cited domain             Product/category
-------------------------------------------------------------------------------------
"best running shoes for..."    ChatGPT      runrepeat.com             Running shoes
"best espresso machines..."    Perplexity   wirecutter.com            Espresso machines
"best..."                      Google AIO   reddit.com                 ...
"X vs Y..."                    Gemini       yourstore.com              Product X

Then aggregate it into something like:

Domain → number of citations → % of prompts → engines → product categories → competitors cited alongside it

That's much more actionable because AI visibility is often driven by third-party sources, not your own domain. Peec, for example, separates source visibility from brand visibility and can show the domains/URLs AI systems use even when your brand isn't explicitly mentioned. peec.aidocs.peec.ai

What I'd actually build for an online store

Track 100–500 commercial prompts per product category, rather than arbitrary informational queries.

For each prompt, capture:

• AI engine/model
• exact prompt
• date/location
• products recommended
• brands mentioned
• every cited URL
• cited domain
• citation position
• whether your store was cited
• whether competitors were cited
• product/category
• sentiment/recommendation context

Then create a “Citation Landscape” dashboard:

Top cited domains

1. Wirecutter — 18.4%
2. Reddit — 14.1%
3. YouTube — 9.7%
4. Your store — 6.2%
5. Consumer Reports — 4.8%

…and drill down by product category + AI engine.

That's particularly important because citation behavior differs substantially between AI engines; recent research shows relatively little overlap in the domains cited by different engines. www.geosoftwarerankings.com

One thing I'd avoid

Don't make “AI visibility score” your primary KPI. It's useful for benchmarking, but for an ecommerce business I'd care much more about:

Citation Share → Product Recommendation Share → AI Referral Traffic → Revenue

In other words: Which sources are AI engines trusting to make shopping recommendations, and how do we get our products represented there?

If you tell me what ecommerce platform you use (Shopify, WooCommerce, custom, etc.) and roughly how many products/categories you have, I can recommend the best setup—including whether I'd buy Peec/Profound/Semrush or build the citation map yourself.

If your goal is specifically “which domains are AI answer engines citing when people ask product-related questions?”, I’d use a dedicated AI-search visibility/citation tracker, rather than trying to infer it from Google Analytics.

My picks

1. Peec AI — probably the best fit for your use case

Peec AI tracks the actual domains and URLs used as sources across ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot and others. It gives you domain-level metrics such as retrieval rate and citation rate, plus the prompts and actual AI chats behind individual citations. docs.peec.ai

For an online store, I'd structure your prompts around things like:

• “best [product category] for [use case]”
• “[product category] comparison”
• “best [product] under $100”
• “[brand] alternatives”
• “where to buy [product]”
• “[product A] vs [product B]”
• “best [product] for [audience]”

Then look at Top Sources → Domains and segment the results by commercial intent. Peec specifically supports intent tagging and source analysis. docs.peec.ai

2. Otterly AI — excellent alternative, especially for citation reporting

OtterlyAI has a particularly useful Citations Report: you can see cited URLs/domains, citation counts, which prompts generated them, which AI engine generated them, and whether your brand appears on the cited page. docs.peec.aiotterly.ai

It also has domain-ranking and citation-gap analysis, which is useful if you're asking:

“AI engines are constantly citing Reddit, Wirecutter, Amazon, G2, review sites, etc. Which of those sources should we be trying to get our products mentioned on?”

Otterly also supports monitoring shopping-card presence, which makes it particularly interesting for ecommerce. help.otterly.ai

What I'd actually build for your store

I'd make a dashboard with roughly:

The important distinction is brand visibility vs source visibility. You might have AI recommending your brand while citing somebody else's review, or your product page might be cited without the AI explicitly mentioning your brand. Peec explicitly separates those two concepts. docs.peec.ai

My recommendation

If you're an ecommerce operator/SEO team, I'd start with Peec AI.

If your primary question is “show me every domain and URL that AI is citing in my product category, and help me identify citation opportunities,” I'd give OtterlyAI a very close look because its citation/domain reporting is unusually aligned with that workflow. otterly.ai

If you tell me what you sell + roughly how many product categories you have, I can also suggest the exact prompt taxonomy and dashboard structure I'd use to measure AI citations for your store.

If your goal is specifically “which domains are AI answer engines citing when people ask product-related questions?”, I’d use a dedicated AI-search visibility platform rather than trying to reconstruct this from Google Search Console or traditional SEO tools.

My picks

1. Scrunch — best fit if you're an ecommerce/product business

Scrunch has a dedicated Shopping product for product-level AI search performance, plus citation monitoring. Its citation reporting can group results by domain or URL and show which domains are cited across tracked prompts, including ChatGPT, Perplexity, Google AI Overviews, and Gemini. helpcenter.scrunchai.com

For your use case, I'd want a dashboard roughly like:

Product → prompt → AI engine → cited domains → cited URLs → competitor/your brand → citation frequency

The ability to identify third-party domains that repeatedly get cited is particularly valuable because those become your potential review, editorial, affiliate, PR, or partnership targets. Scrunch explicitly supports citation trends and segmentation of sources. scrunch.com

2. Profound — best for deeper competitive/citation research

Profound is probably my choice if you're building a more serious AEO/AI-search intelligence program. Its Citation dashboard gives you Top Citation Domains, Top Citation Pages, citation share, platform-level breakdowns, and relationships between cited sources. help.tryprofound.comwww.tryprofound.com

It also supports major consumer answer engines including ChatGPT, Perplexity, Claude, Google AI Overviews/AI Mode, Gemini, Copilot, Amazon Rufus, Meta AI, Grok, and others. www.tryprofound.com

For an online store, this is especially useful for questions such as:

• “best running shoes for flat feet”
• “best [product category] under $100”
• “[product A] vs [product B]”
• “best [category] for beginners”
• “where should I buy [product]?”
• “best alternatives to [competitor]”

You can then see which publishers, retailers, review sites, Reddit pages, etc. are getting cited instead of you.

What I'd actually track

Don't just measure “is my store cited?”

Build a dataset around:

The particularly important metric is citation share: not merely “did someone cite us?” but what percentage of the citations in our category belong to our domain versus competitors and third parties. Profound explicitly supports this metric. www.tryprofound.com

One important distinction

I'd separate “domains AI cites” from “domains that mention my product.”

For example, you might discover:

AI answer: “Best hiking boots…”

Cited: reddit.com, outdoorgearlab.com, rei.com, yourstore.com

That's much more actionable than knowing your own page was cited. You can identify that OutdoorGearLab and Reddit are influential sources for this product category, then investigate why and whether you can legitimately earn coverage there.

What I'd choose

If you're an ecommerce team starting this now: Scrunch.

If you're doing sophisticated competitive AEO research / managing lots of products and prompts: Profound.

And I'd make domain-level citation mapping the core output—not just an AI visibility score. The latter tells you whether you're visible; the former tells you who is shaping the AI's answer and where you have an opportunity to influence the source ecosystem. www.tryprofound.com

If you tell me roughly how many products/SKUs you have and which AI engines matter most (ChatGPT, Gemini, Perplexity, Google AI, Amazon Rufus, etc.), I can recommend the most sensible setup and metrics for your store.

If your goal is specifically to map which domains AI answer engines cite when people ask product-related questions about your category, I’d use a dedicated AI-search/GEO citation tracker, rather than trying to infer it from Google Search Console or traditional SEO tools.

My top picks

1. Profound — best for serious analysis

This is probably what I’d choose for an online store if you want to build an actual “AI citation map”.

It lets you:

• Define product/category prompts such as “best running shoes for flat feet”, “best X under $100”, “X vs Y”, etc.
• Track answers across ChatGPT, Google AI Overviews, Perplexity and other answer engines.
• See the top citation domains and individual URLs.
• Separate citations into owned, competitor, media, social, institutional, etc.
• Compare your citation share with competitors.
• See which domains are repeatedly cited across particular topics/prompts. www.tryprofound.comhelp.tryprofound.comhelp.otterly.ai

The particularly useful metric for your use case is Top Citation Domains: essentially, “Which websites does AI trust to answer questions in my product category?” www.tryprofound.comhelp.tryprofound.comhelp.otterly.ai

2. OtterlyAI — best if you want something more straightforward

Otterly is especially interesting for ecommerce because its prompt-level reporting includes domain citations, competitors, AI engine, and even shopping-card presence. help.otterly.ai

Its citation report lets you filter cited URLs by domain and see which sources are gaining or losing citations. It also shows the prompts and engines associated with a particular citation. otterly.ai

What I'd actually build

For your store, I'd structure the tracking around product-intent prompt clusters, rather than simply tracking your brand name.

For example:

Then I'd create a dataset like:

AI engine → prompt → cited URL → cited domain → brand mentioned? → competitor mentioned? → citation frequency → product/category → source type

That gives you a much more useful picture than simply asking “Does ChatGPT mention my store?”

The important insight

Don't just measure your domain's citations.

You want to discover the citation ecosystem around your category.

For example, you might discover that AI answers about your products disproportionately cite:

• Wirecutter
• Reddit
• specialist review sites
• major retailers
• comparison sites
• YouTube
• manufacturers
• niche blogs

That tells you where you need to get mentioned, not merely where you need to publish more content. Otterly's recent citation analysis, for example, explicitly emphasizes third-party URLs and identifying highly cited sources where your brand isn't mentioned. otterly.ai

My recommendation: start with Profound if you're building a serious ecommerce AI-search measurement program; start with OtterlyAI if you want a simpler, more focused citation-monitoring workflow.

If you tell me what kind of products your store sells and roughly how many SKUs/categories you have, I can also suggest the exact prompt taxonomy and dashboard structure I'd use to map your AI citation landscape.

For an online store, you probably want an AI citation intelligence stack rather than a normal SEO rank tracker. The thing you’re trying to measure is:

“When someone asks ChatGPT / Perplexity / Gemini / AI Overviews a product-buying question, which domains are being cited, and where does my store appear (or fail to appear)?”

AI citation tracking is still an emerging category, but several tools are built around this workflow. www.techradar.com

Best options by use case

www.techradar.com

For a product catalog, I’d build the data model around prompts → engines → cited domains → products.

Example:

Then calculate:

1. Citation share

your_store_citations / total citations

Example:

• 1,000 tracked product prompts
• AI engines produced 5,000 citations
• Your domain appeared 75 times

Citation share = 1.5%

2. Competitor citation gap

Track:

• yourstore.com
• amazon.com
• walmart.com
• bestbuy.com
• niche review sites
• Reddit/forums

AI answers often cite a different set of sources than traditional search rankings, so you need source-level tracking, not just keyword position tracking. arxiv.org

3. Domain graph

I’d export citations into a database and visualize:

                ChatGPT
                   |
        -------------------------
        |           |           |
   reddit.com   nytimes.com  yourstore.com
        |                       |
   product reviews        product pages

                Perplexity
                   |
        -------------------------
        |           |           |
   amazon.com  youtube.com  forums

Useful tools:

• Database: PostgreSQL / BigQuery
• Dashboard: Looker Studio, Tableau, Metabase
• Graph view: Neo4j or Gephi (if you want “who cites whom” maps)
• Collection: APIs where available, or scheduled prompt runs

For an ecommerce store, I’d track these prompt buckets

1. Category discovery
2. “best X”
3. “top X brands”
4. “X alternatives”

2. Comparison
3. “Brand A vs Brand B”
4. “is Brand A worth it”

3. Transactional
4. “where to buy X”
5. “best price for X”

4. Problem-based
5. “best X for people with Y problem”

5. Product-specific
6. “reviews of Product Model Z”

The biggest mistake is only tracking whether your brand is mentioned. The more valuable question is:

“Which third-party domains are teaching AI engines what products to recommend?” substack-post-media.s3.us-east-1.amazonaws.com

If you’re running a Shopify/Magento/WooCommerce store, I’d usually start with Semrush/Ahrefs + a custom citation warehouse, because you’ll eventually want product-level attribution (“which SKU pages are winning AI visibility?”), not just brand mentions.

If your goal is specifically to map which domains AI answer engines cite for product-related questions, I’d use a dedicated AI-search visibility platform rather than trying to infer it from Google Search Console.

My shortlist

1. Profound — best for serious citation mapping

This is probably the closest match to what you're describing. Profound tracks the sources cited across answer engines and lets you break citation share down by platform, prompt, topic, domain, and URL. It also categorizes sources as owned, competitors, earned media, social, etc. www.tryprofound.com

For an ecommerce store, I'd want a report like:

That lets you answer the much more useful question: "Who is AI trusting to answer questions that could lead to a purchase?"

2. OtterlyAI — best/easiest starting point

Otterly is particularly interesting for your use case because it explicitly tracks domain and URL citations, including citation position and changes over time. It supports ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini, Copilot and Claude. It also provides CSV exports and a Looker Studio connector. otterly.ai

I'd choose this if you're trying to build a repeatable weekly/monthly "AI citation landscape" dashboard without building much infrastructure yourself.

The important part: don't just track your own brand

For product-related queries, I'd build a citation-domain map around your category.

For example, if you sell espresso equipment, your prompt set might include:

• "best espresso machine under $1,000"
• "best espresso machine for beginners"
• "Breville vs DeLonghi"
• "best espresso machine for small kitchens"
• "best espresso grinder for..."
• "where should I buy..."
• "[specific product] alternatives"
• "[specific product] reviews"
• "is [product] worth it?"

Then collect every cited URL and roll it up:

Domain → number of citations → % citation share → engines citing it → product/category → prompts

This distinction matters because research suggests AI answer engines can have substantially different citation pools rather than one universal set of "authoritative" domains. arxiv.org

What I'd actually build

If this were my store, I'd have four dashboards:

1. Citation Share

Which domains are AI engines citing most frequently for my product category?

2. Competitor Citation Gap

Which domains/URLs cite competitors but never cite us?

3. Product Citation Map

Which specific product pages are getting cited—and which aren't?

4. Engine × Domain Matrix

                    ChatGPT   Perplexity   Google AI   Gemini
Reddit                 18%        24%          21%        9%
YouTube                12%         8%          17%       14%
YourStore.com            6%         4%           8%       11%
Competitor A            14%        11%          10%       9%
Wirecutter              9%         7%           6%        5%
Amazon                  7%        13%          11%        8%
...

That becomes much more actionable than a generic "AI visibility score."

My recommendation

Start with OtterlyAI if you want something you can deploy quickly and export into your own reporting.

Use Profound if citation intelligence is going to become a serious part of your SEO/content strategy and you want deeper competitive/source analysis.

And I'd avoid treating "AI visibility" as one universal metric. Track citations at the prompt × engine × URL level first, then aggregate them into domain-level patterns. That's the dataset you'll eventually want for deciding where your store needs to earn mentions/citations. otterly.aiwww.tryprofound.com

If you tell me what you sell + roughly how many products/categories you have, I can also lay out the exact prompt taxonomy + database schema + dashboard I'd use to map your AI citation landscape.

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d use an AI visibility/AEO tracker that exposes citation-level data, rather than a traditional SEO rank tracker.

My shortlist

For an online store, I'd start with OtterlyAI or Peec AI. Otterly looks particularly well aligned with your exact question because it exposes the actual cited links rather than merely saying “your brand was mentioned.” otterly.ai

But here's the important part

Don't just track your domain.

Build a dataset like:

Prompt
    ↓
AI engine
    ↓
Answer
    ↓
Every cited URL
    ↓
Domain
    ↓
Source type
    ↓
Competitor/product mentioned

For example:

Then aggregate domain → citation count.

That gives you something much more strategically useful:

“For 500 product-intent questions in our category, these are the 50 domains AI engines actually trust.”

That's essentially your AI citation landscape.

And you should break it down by engine, because the source pools aren't interchangeable. Recent research finds substantial differences in which domains get cited across ChatGPT, Gemini, Perplexity and other generative search systems. arxiv.orgarxiv.org

The metrics I'd actually track

For an ecommerce store, I'd create a dashboard with:

• Citation share by domain
• Citation share by AI engine
• Your domain vs. competitors
• Product-page citations
• Editorial/content-page citations
• Third-party citations
• Citation frequency per prompt
• Unique domains citing you
• Domains repeatedly citing competitors but never you
• Prompt → cited URL → product conversion/traffic, where measurable

The last one is particularly valuable. You're ultimately trying to identify which external sources influence AI recommendations, so you can decide whether to pursue reviews, comparisons, PR, retailer listings, communities, etc.

There's also an important measurement caveat: AI answers aren't deterministic. Repeated identical queries can produce different citations, so I'd run each important prompt multiple times and measure citation frequency/distribution, rather than treating one answer as ground truth. arxiv.orgarxiv.org

If you tell me roughly how many products you have and whether you're Shopify/WooCommerce/custom, I can recommend a concrete setup—including the prompt dataset, tools, database schema, and dashboard I'd use to map your AI citation competitors.

If your goal is specifically “Which domains are AI answer engines citing when people ask product/category questions?”, I’d use an AI-search citation monitoring platform, not traditional SEO rank tracking.

My picks

1. Scrunch — probably the best fit for your exact question

urlScrunch AI Search Monitoringturn0search4

Its citation reporting is unusually aligned with what you want: it can group citations by domain or individual URL, show which domains are cited most often, and distinguish your brand, competitors, publishers, social sources, etc. helpcenter.scrunchai.com

For an online store, I'd build a prompt set such as:

• “Best [product category] for [use case]”
• “[Product category] alternatives to [competitor]”
• “Best [product] under $100”
• “[Product A] vs [Product B]”
• “Where should I buy [product]?”
• “What are the most reliable [product category] brands?”
• “Best [product] for [customer type]”

Then look at Top Cited Domains across those prompts. That gives you a map of the sites influencing AI answers in your market.

2. OtterlyAI — best if you want broader engine coverage + easier competitive tracking

urlOtterlyAIturn0search5

It currently monitors ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini, Claude and Copilot, and its citation reports let you analyze cited URLs/domains and whether your brand is mentioned on those sources. help.otterly.ai

I'd choose this if you want to answer:

“What domains are AI engines citing for my category, and where do my competitors appear but I don't?”

That's a little more actionable than simply counting citations.

What I'd actually build

For an ecommerce store, I'd make a Citation Influence Map rather than just an AI visibility dashboard:

Then segment the domains into:

Earned-media opportunities

• product reviews
• editorial publications
• comparison sites
• industry publications

Community

• Reddit
• forums
• social platforms

Retail/product databases

• retailers
• marketplaces
• shopping aggregators

Competitor-owned

• competitor product pages
• competitor buying guides

Your own

• product pages
• category pages
• buying guides

That distinction matters because the domain that gets cited isn't necessarily the page you need to optimize. You want to know why the AI engine is citing that domain and what information it is extracting from it.

One important ecommerce wrinkle

Don't treat AI product recommendations/shopping surfaces as identical to ordinary AI-answer citations. Product discovery is increasingly becoming its own channel, with product feeds, structured product data, retailer information and other signals playing a role. Recent reporting also shows AI-referred ecommerce traffic can be unusually valuable. www.reuters.com

So I'd track two datasets:

1. Informational/commercial answers → Which domains influence the answer?
2. Product/shopping queries → Which products/retailers actually get recommended?

If you're starting today, I'd test Scrunch and Otterly against ~100–300 real product questions and compare their raw citation exports. For your particular use case, I'd lean Scrunch for the citation-domain mapping and Otterly for broader ongoing monitoring/competitive reporting.

If you want to map which domains AI answer engines cite when answering product-related questions about your online store, you’re essentially looking for an AI visibility / answer engine optimization (AEO) monitoring stack. The right tool depends on whether you want competitor research, your own citation tracking, or a full analytics pipeline.

Best purpose-built tools

If you want to build your own citation map

For an ecommerce store, I’d typically build a dataset like:

A simple workflow:

1. Create a product-question query set
   • “best [product category]”
   • “[product] vs [competitor]”
   • “is [product] worth it?”
   • “best [product] under $X”
   • “where to buy [category]”

2. Run them regularly through AI engines
   • ChatGPT
   • Perplexity
   • Google AI Overviews / Gemini
   • Claude (if relevant to your audience)

3. Extract citations
   • Manually for a small set (50–200 queries)
   • Use browser automation/API workflows for scale

4. Analyze domain frequency

Example output:

   Domain              Citations   Share
   reddit.com              84        22%
   nytimes.com             41        11%
   competitor.com          36         9%
   yourstore.com            8         2%

For ecommerce specifically, I’d prioritize tracking:

• Product review sites
• Marketplaces
• Forums/community sites
• Manufacturer pages
• Retailers
• Comparison articles
• Your own product/category pages

AI systems often cite trusted third-party sources, not just the brand selling the product, so the goal is usually not only “get my domain cited,” but also “understand which sources influence AI recommendations and earn presence there.”

If you’re doing this for a store with hundreds/thousands of SKUs, I’d lean toward a tool like Profound or Peec AI. If you have a smaller catalog and want a custom competitive map, a spreadsheet + automated query runner can work well.

If you mean tracking which websites/domains AI answer engines cite when answering questions about products you sell, I’d use a combination of AI visibility tracking + your own citation dataset, rather than traditional SEO rank tracking.

Best setup

What I would actually build

For an online store, create a dataset where each row is an AI answer citation:

date
answer_engine
model
prompt
product/category
your_brand_mentioned
your_domain_cited
cited_domain
cited_url
citation_position
competitor_mentioned
source_type

Then aggregate it into metrics such as:

• Citation share by domain — what % of answers cite Amazon, Reddit, Wirecutter, manufacturer sites, review sites, etc.
• Citation share by answer engine — ChatGPT vs Google AI Overviews/AI Mode vs Perplexity, etc.
• Citation share by product category
• Your domain citation rate
• Competitor citation rate
• Most frequently cited URLs
• Newly emerging citation domains
• Citation overlap — domains cited by multiple AI engines
• Prompt-level visibility — which questions produce citations to your site

The important distinction is domain citation share ≠ traditional search visibility. A site can rank poorly in Google but be disproportionately influential in AI answers.

If you want a tool rather than building it

I'd evaluate platforms specifically on whether they let you export the underlying cited URLs, not merely give you an "AI visibility score." The raw citation data is what lets you build the domain map you're describing.

If you tell me which AI answer engines you care about (e.g. ChatGPT, Gemini, Perplexity, Google AI Overviews) and roughly how many product/purchase-intent questions you want to track, I can recommend the most suitable tools and/or sketch the exact database/dashboard architecture.

If your goal is specifically to map which domains AI answer engines cite for product-related questions in your ecommerce niche, you need a tool focused on AI citation tracking (often called GEO or AEO) rather than traditional SEO.

The capabilities to look for are:

• Run the same prompts across ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews.
• Capture every cited URL and domain.
• Show which domains are cited most often.
• Compare your store against competitors.
• Track changes over time rather than one-off snapshots.

Here are the strongest options today:

If I were auditing an online store

I'd create around 100–300 real buyer prompts, such as:

• best wireless gaming mouse under $100
• best standing desk for small apartments
• best espresso machine for beginners
• is Brand X worth it?
• Brand A vs Brand B
• best organic dog food

Then I'd run them weekly and export:

• every cited domain
• citation frequency
• engine (ChatGPT vs Gemini vs Perplexity)
• prompt category
• position in the answer

That quickly reveals patterns like:

This is much more actionable than simply knowing whether your brand was mentioned.

For ecommerce, I'd also measure

• Citation share by product category
• Citation share by AI engine
• "Best X" prompts
• "X vs Y" prompts
• Review queries
• Buying guide queries
• Problem/solution queries

Those segments often produce very different citation sources. Research and industry observations consistently show that different AI engines rely on substantially different source pools, so it's worth tracking each engine separately rather than treating "AI search" as one channel. arxiv.org

If you don't want another SaaS subscription

You can build your own tracker using Python or an automation platform like n8n:

1. Store your list of prompts.
2. Query multiple AI engines on a schedule.
3. Extract all cited URLs.
4. Normalize them to domains.
5. Aggregate by domain, prompt, category, and engine.
6. Visualize trends in a BI tool such as Looker Studio or Power BI.

This approach gives you complete ownership of the raw citation data, which is especially useful if you're monitoring hundreds or thousands of product-related queries across multiple categories.

If your goal is to understand which websites AI answer engines (ChatGPT, Gemini, Claude, Perplexity, AI Overviews, etc.) cite when answering product-related questions, you'll likely need a combination of AI monitoring and citation analysis tools. No single tool covers every model perfectly.

Here's how I'd categorize the options:

If your specific question is:

"What domains are AI engines citing for my products?"

I'd shortlist these.

1. Otterly.AI (one of the better fits)

Tracks prompts across AI engines and records:

• cited domains
• frequency of citations
• competitors cited
• changes over time
• visibility by prompt

Useful if you're an ecommerce business wanting to know why competitors appear instead of you.

2. Profound

More enterprise-focused.

It monitors:

• brand mentions
• citation sources
• competitive comparisons
• prompt coverage
• changes in AI answers over time

Popular among larger consumer brands.

3. Peec AI

Strong if you want dashboards showing:

• which domains each AI engine references
• citation share
• prompt clusters
• rankings within AI-generated answers

For ecommerce specifically

I'd test prompts like:

• best ergonomic office chair
• best waterproof hiking boots
• best espresso machine under $500
• is Brand X worth buying?
• Brand X vs Brand Y
• alternatives to Brand X
• where to buy Product X

Then collect for each engine:

• domains cited
• retailer links
• review sites
• forums
• manufacturer sites
• YouTube channels

After a few hundred prompts you'll usually discover patterns like:

• Reddit is cited 35%
• Wirecutter 18%
• Tom's Hardware 12%
• Manufacturer docs 10%
• YouTube creators 8%

Those patterns tell you where AI systems are sourcing information.

If you want complete coverage

Many companies build an internal monitoring system that:

1. Runs thousands of product prompts.
2. Queries multiple AI models.
3. Extracts every cited URL.
4. Normalizes to root domains.
5. Tracks citation frequency over time.
6. Compares against competitors.

This approach gives you much deeper insight than any single dashboard because you control the prompts and can focus on your own catalog.

Recommendation by business size

• Small ecommerce store: Otterly.AI
• Growing DTC brand: Peec AI
• Mid-market or enterprise: Profound
• SEO team already using Ahrefs or Semrush: Add their AI visibility features, but don't rely on them alone for citation mapping.
• Research-heavy or agency use: Build your own prompt-testing and citation extraction pipeline alongside a monitoring platform.

If your goal is to map the entire citation graph—for example, "which domains influence AI answers for every product category I sell?"—a custom pipeline is usually the most comprehensive solution, since it lets you analyze thousands of prompts across multiple AI engines and identify the recurring source domains that shape their answers.

If your goal is to understand which websites AI answer engines (ChatGPT, Gemini, Claude, Perplexity, etc.) are using as sources for product-related questions, you'll typically need a combination of AI visibility tools and your own monitoring.

Here are the strongest options:

If you're trying to answer questions like:

• "When someone asks 'best ergonomic office chair under $300,' which domains does ChatGPT cite?"
• "Which review sites are AI answers pulling from?"
• "Which competitors get mentioned alongside my products?"

these platforms are designed specifically for that.

If you want to build your own citation map

Many ecommerce teams also create their own dataset by:

1. Creating 100–500 important product-related prompts.
2. Running those prompts across:
   • ChatGPT
   • Gemini
   • Perplexity
   • Claude
3. Recording:
   • cited domains
   • linked pages
   • brands mentioned
   • products recommended
   • whether your store appears
4. Aggregating the results to see which domains appear most often.

This often reveals patterns such as:

From there, you can prioritize where to improve your presence or earn citations.

For a Shopify or DTC brand

The most useful metrics are usually:

• Share of AI answers mentioning your brand
• Domains most frequently cited by AI
• Competitors appearing alongside your products
• Products AI recommends instead of yours
• Missing informational content (buying guides, comparisons, FAQs)
• Citation trends over time after publishing new content

These insights help identify opportunities to increase the likelihood that AI systems surface your products or content in relevant answers.

If your store has hundreds or thousands of SKUs, I can also suggest a scalable workflow for automatically mapping AI citations across your entire product catalog rather than checking prompts one by one.

If your goal is to understand which websites AI answer engines (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.) rely on when answering product questions about your store, there are a few categories of tools. No single tool gives a complete picture because each AI system uses different retrieval methods.

Here's how I'd break it down:

Best dedicated platforms

Profound

• Probably the most mature enterprise AI search analytics platform.
• Tracks prompts across major AI engines.
• Shows:
  • cited domains
  • citation frequency
  • competitor mentions
  • prompt coverage
  • changes over time

Best if AI search is becoming an important acquisition channel.

Peec AI

• Built specifically for AI visibility.
• Good dashboard for:
  • brand mentions
  • cited websites
  • competitive analysis
  • product/category prompts

Often easier to use than enterprise tools.

Goodie AI
Focuses on:

• prompt monitoring
• source attribution
• brand presence
• citation tracking

Good for ecommerce brands wanting ongoing monitoring.

Otterly.AI
Less focused on citations themselves and more on:

• whether your brand appears
• ranking in AI answers
• prompt monitoring

Useful alongside another citation-focused platform.

SEO tools that complement them

AI engines frequently draw from pages that already have strong authority.

Use:

• Ahrefs
• Semrush
• Similarweb

to identify:

• review sites
• comparison articles
• forums
• editorial publications

that rank well for your products. Those are often the same domains AI systems cite.

If you're willing to build your own tracker

Many ecommerce teams now automate this.

Typical workflow:

1. Create 500–5,000 product-related prompts.
2. Run them daily against:
   • ChatGPT
   • Perplexity
   • Gemini
   • Claude
3. Save:
   • answer text
   • outbound links
   • cited domains
4. Aggregate:
   • citation share
   • domain frequency
   • competitor mentions
   • changes over time

This gives you metrics like:

That kind of dataset is often more actionable than a traditional SEO rank report because it shows which publishers AI systems consistently trust for your product category.

My recommendation

For a typical online store:

• Small business: Peec AI or Goodie AI.
• Mid-size ecommerce: Profound, combined with Ahrefs or Semrush.
• Large catalog (10,000+ products): Build an internal prompt-monitoring pipeline using APIs from multiple AI providers, then layer a visualization tool like Looker Studio or Tableau on top. This gives you the most complete view of citation patterns and lets you monitor exactly the product questions that matter to your business.

If your goal is to understand which websites AI answer engines (ChatGPT, Gemini, Perplexity, Claude, AI Overviews, etc.) cite when answering product-related questions, you're looking at a relatively new category of AI visibility or LLM analytics tools.

The best options depend on whether you want competitive research, monitoring, or your own store's performance.

For ecommerce specifically

If you sell products online, I'd focus on tools that answer questions like:

• Which domains does ChatGPT reference for "best wireless earbuds under $100"?
• Which retailers get cited most often?
• Which review sites influence AI answers?
• How often does my store appear?
• Which pages should I improve to increase AI citations?

A practical workflow

1. Create a list of 50–200 high-intent questions, for example:
   • Best ergonomic office chair
   • Best running shoes for flat feet
   • Best coffee grinder under $200
   • Is Brand X worth buying?
   • Product A vs Product B

2. Run them across:
   • ChatGPT
   • Google AI Overviews
   • Gemini
   • Perplexity
   • Claude (where applicable)

3. Record:
   • Domains cited
   • Products mentioned
   • Ranking/order
   • Whether your site appears

4. Group citations into categories:
   • Manufacturer
   • Retailer
   • Editorial review
   • Reddit/forums
   • YouTube
   • Independent blogs

You'll quickly identify which domains consistently influence AI-generated recommendations in your niche.

If you already use SEO tools

Traditional backlink tools won't tell you which sources LLMs cite. Instead, combine them with AI visibility tools:

• Use AI visibility software to identify the domains AI systems reference.
• Use SEO tools to understand why those domains are authoritative (backlinks, topical authority, structured data, content depth).

If you're building your own dashboard

Many ecommerce teams build internal monitoring that:

• Sends hundreds of prompts daily to multiple AI systems.
• Extracts cited URLs and domains.
• Tracks citation frequency over time.
• Alerts when competitors gain visibility or when your own domain drops.
• Segments results by product category and buying intent.

This approach provides a historical view of AI citation trends rather than relying on occasional manual checks.

If your store has thousands of products, an automated dashboard is often more scalable than relying solely on commercial tools. It can reveal which product pages, buying guides, or third-party reviews are driving AI citations and where there are opportunities to improve your content.