ChatGPT answers, unedited

Yes. There’s now a fairly mature category of AI visibility / GEO (generative engine optimization) platforms that measure something close to “share of voice” across conversational assistants.

For an ecommerce site, I’d look at these:

• RivalSee — specifically tracks brand recommendations/share of voice across ChatGPT, Claude, Gemini, and Perplexity, with competitor comparisons. RivalSee
• CrowdReply — measures share of the AI conversation by brand, LLM, prompt category, and intent type, with daily prompt monitoring. CrowdReply
• SearchDock — tracks SOV across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews, including competitor and citation data. SearchDock
• SkuLift — more ecommerce-oriented; measures mentions/citations across ChatGPT, Claude, Perplexity, and Gemini. SkuLift
• Verity Score — explicitly positions itself around AI SOV for ecommerce and tracks ChatGPT, Perplexity, Gemini, Claude, and Mistral. Verity Score
• Orbilo — combines AI visibility and competitive SOV across ChatGPT, Claude, Perplexity, Gemini, and Grok. Orbilo

The important distinction

I'd be careful about treating all of these as equivalent. “AI share of voice” can mean several different things:

For ecommerce, I'd want all of those separated, rather than one blended “AI visibility score.” A brand could have 40% visibility overall while being 65% on ChatGPT and 5% on Gemini.

There is also a more fundamental issue: AI responses are non-deterministic, so a credible platform should run the same buyer-intent prompts multiple times and report an aggregate rather than treating one answer as ground truth. Verity Score, for example, explicitly recommends multiple runs per prompt and reporting a range. Verity Score

If you're thinking about this as a product/category

There actually seems to be an interesting gap between SEO rank tracking and digital shelf analytics.

The ideal ecommerce dashboard would let you enter a site and a competitive set, then show something like:

“When shoppers ask AI about products in your category, how much of the answer belongs to you?”

Across:

ChatGPT | Gemini | Claude | Perplexity | Google AI Mode | Amazon/Rufus | Walmart/Sparky

And then drill down:

Category → buyer intent → prompt → brand → product/SKU → mention position → citation → source influencing the answer.

Some platforms are getting there, but the commerce/product-level piece is less mature than general brand visibility. Current comparisons show many platforms tracking the major assistants, while substantially fewer support actual product-query/agent visibility. ecommerceguide.com

If you're asking because you're evaluating/building a platform like this, I can also map out the current vendors and identify what is genuinely differentiated vs. table stakes.

Yes. This category is emerging pretty quickly, usually called AI visibility, GEO (Generative Engine Optimization), or AI Share of Voice.

For an ecommerce site, I’d look at these:

For example, Zumi explicitly measures share of voice against competitors per AI engine, along with mention rate and position. www.zumihq.com Seerly similarly lets you see your share versus competitors and break it down by individual engine. seerly.app

If you're specifically asking about ecommerce products

That's where things get more interesting. Citely claims to track individual products/SKUs across shopping queries, e.g. whether a particular product gets recommended in ChatGPT versus Perplexity, and supports Shopify/WooCommerce/Amazon catalogs. citelyhq.com

There are also Shopify-specific approaches such as Verity Score, which measures AI share of voice across multiple assistants and is explicitly positioned around DTC/ecommerce. verityscore.io

What I'd want the dashboard to show

If you're evaluating this category, I wouldn't settle for a generic "AI visibility score." The useful metric is something like:

For 500 high-intent shopping prompts, what % of AI recommendations contain my brand/product vs. each competitor, broken down by assistant?

For example:

"Best running shoes for flat feet under $150"

Then drill into:

• Which products/SKUs are being recommended
• Which competitors are displacing you
• Your position in the answer (#1, #2, etc.)
• Which URLs AI cites when recommending competitors
• Which prompts have zero visibility
• Share of voice by category/product
• Change week-over-week
• ChatGPT vs. Gemini vs. Perplexity vs. Claude
• Ideally, shopping/agent surfaces, not just generic informational queries

That's substantially more useful than simply asking "Does ChatGPT mention my company?"

There are already platforms doing much of this; the market is just fragmented. A recent ecommerce-focused comparison identified 18 platforms covering some combination of AI visibility, share of voice, citations, product queries, and agent visibility. ecommerceguide.com

If you're considering building/buying one, I can also give you a competitive landscape of the ~10 leading AI Share-of-Voice platforms specifically for ecommerce, including pricing, assistants covered, Shopify integration, SKU-level tracking, and what each one is actually measuring.

Yes. There’s now a fairly mature category of AI visibility / GEO platforms that measure something very close to “share of voice” for an ecommerce brand across conversational assistants.

The most relevant options I found:

The closest match to what you're describing

Wildcard looks particularly ecommerce-oriented. It explicitly reports Share of Voice, competitor visibility, sentiment, and which products/brands are being surfaced by AI. Its positioning is essentially: which products does AI recommend, how often, and what can you do about it? wild-card.aitrucommerce.aimodelmention.io

Tru Commerce is even more interesting if you're thinking about agentic commerce, rather than just SEO/GEO. It lets brands track ChatGPT, Gemini, Perplexity, Rufus, Copilot and Claude, and reports metrics such as mention share, citation rank, top-5 presence and absence rate. trucommerce.ai

ModelMention is another direct fit: it specifically markets AI-search analytics to ecommerce brands and tracks visibility, position, share of voice and sentiment. modelmention.io

One important distinction

“AI share of voice” isn't quite standardized yet.

The better platforms generally calculate something like:

Your brand mentions / total relevant brand mentions across a defined prompt set

So, for example, you might track 500 buyer questions such as:

• “Best running shoes for flat feet”
• “What are good alternatives to Hoka?”
• “Best running shoes under $150”
• “Where should I buy trail running shoes?”
• “Compare Brooks Ghost vs Nike Pegasus”

Then run those prompts repeatedly across ChatGPT, Gemini, Claude, Perplexity, etc., identify the brands/products mentioned, and calculate your share relative to competitors.

That's important because AI responses are nondeterministic; a single query isn't a reliable ranking. Verity Score, for example, explicitly recommends multiple prompts and multiple runs per prompt when measuring AI share of voice. verityscore.io

If you're evaluating this as a product/category

I'd break the market into three buckets:

1. GEO/AI visibility analytics
Wildcard, ModelMention, AnswerMonk, CrowdReply, Verity Score
→ “How often does AI mention/recommend my brand vs competitors?”

2. Enterprise search intelligence
SERPrecon, Semrush and similar tools
→ “How does my visibility across traditional search + AI search change?”

3. Agentic commerce infrastructure
Tru Commerce
→ “What are AI agents actually recommending/buying, and can I influence the transaction?”

There's also increasing evidence that this is becoming a meaningful ecommerce channel rather than merely an SEO metric. Reuters reported in August 2026 that retailers are actively optimizing for ChatGPT/Gemini-driven shopping discovery, while Adobe data showed AI-referred visits producing substantially higher revenue per visit than traditional channels. www.reuters.com

If you're asking because you're considering building something in this space: I think there's still an interesting gap. Most products measure brand-level AI visibility, but the really valuable ecommerce version would be SKU-level share of voice × assistant × prompt intent × competitor × revenue attribution. That's a much more actionable metric than simply “your brand was mentioned 23% of the time.”

Yes. This is now a real category—usually called AI visibility, AI search visibility, GEO/AEO, or AI Share of Voice (SOV).

For an ecommerce site, I’d look at these:

For example, Zumi explicitly measures ecommerce-oriented metrics such as mention rate, share of voice, average position, and competitor performance across ChatGPT, Gemini, Perplexity, Claude, Copilot and Google AI surfaces. www.zumihq.com

Otterly is another strong fit: it tracks prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and shows brand mentions, competitor coverage, position and citations. otterly.ai

And this isn't just measuring "does ChatGPT mention my company?" The more useful systems calculate something closer to:

AI Share of Voice = your brand's share of mentions/recommendations among all brands appearing for relevant shopping prompts

So you can have something like:

"Best running shoes for flat feet"

That distinction is important because different assistants can have dramatically different visibility for the same brand. Recent research tracking hundreds of brands found substantial brand-level variation between ChatGPT, Gemini, Google AI Overviews and Perplexity. trysill.com

If you're specifically building this for an ecommerce brand

I'd prioritize Profound, Zumi, and Otterly.

• Profound → best if you're an enterprise/large ecommerce organization and want deep competitive intelligence.
• Zumi → particularly compelling if you care about products/SKUs, retail queries, category visibility and citations.
• Otterly → probably the easiest place to start if you mainly want a dashboard showing "where do we appear vs. competitors across AI?"

There are also newer tools specifically positioning themselves around ecommerce/DTC. For example, Anagram's current positioning is explicitly around Shopify/DTC teams and turning AI visibility data into actionable content improvements. www.anagram.ai

One caveat: "share of voice" isn't yet a standardized metric. Different vendors define and calculate it differently—some count mentions, some weight position, some count citations, and some incorporate sentiment. otterly.aitrysill.comwww.anagram.aiverityscore.io So I would compare the underlying methodology before comparing SOV numbers between vendors.

If you're asking because you want to build/buy a platform for your ecommerce business, I can also break down exactly what the best AI-commerce SOV dashboard should measure (prompts → assistants → products → citations → competitors → conversions) and which of these platforms gets closest.

Yes. This is becoming a real category—usually called AI Search Visibility, Generative Engine Optimization (GEO), or AI Share of Voice.

For an ecommerce site, I’d shortlist these:

The one I'd look at first: Profound

Profound is probably closest to the thing you're describing. Its Answer Engine Insights explicitly measures Share of Voice and lets you break it down by LLM, topic, geography, competitors, etc. It queries the actual consumer-facing AI experiences rather than simply relying on model APIs. help.tryprofound.com

For example, you could configure prompts like:

• "best running shoes for marathon training"
• "where should I buy a wedding guest dress?"
• "best alternatives to Nike Pegasus"
• "best gifts for a 30-year-old woman under $100"
• "which retailers have the best selection of linen shirts?"

Then measure something like:

Nike — 31% AI SOV
Adidas — 24%
Hoka — 18%
Your brand — 7%

…and see that separately for ChatGPT vs Gemini vs Perplexity vs Claude, as well as which prompts/categories are driving the difference.

Profound also now has a Shopping Analysis product specifically focused on how products surface in AI shopping/commerce conversations, including placement, product attributes, images and competitive positioning. www.tryprofound.com

ZUMI is especially interesting if you're a retailer

ZUMI's product-visibility offering is more explicitly ecommerce-oriented. It reports mention rate, share of voice and average position, and breaks visibility down by engines including ChatGPT, Gemini, Perplexity, Claude, Copilot and AI Overviews. www.zumihq.com

One important distinction

There are actually two different things you might mean by "AI share of voice":

1. Brand/category SOV — When consumers ask AI for recommendations, how often does my brand/product appear versus competitors?
2. Traffic/agent SOV — How much AI-driven traffic/crawling activity is actually reaching my site?

Platforms like Profound and Otterly are strongest on #1. Otterly, for example, can also analyze AI-agent visits to your site and break them down by engine. www.zumihq.comhelp.otterly.ai

For an ecommerce company, I'd actually want both:
AI recommendation SOV → AI citations → AI referral traffic → conversion/revenue.

If you're evaluating this because you're considering building or buying such a platform, I can also map out the current landscape and tell you which platforms actually have product-level ecommerce SOV versus just generic brand visibility.

Yes. This is now a real category, usually called AI visibility, AI search visibility, or GEO (Generative Engine Optimization). Several platforms specifically measure share of voice (SoV) against competitors across conversational AI assistants.

For an ecommerce site, I’d look at these:

For example, Brandofy explicitly tracks brands and products across ChatGPT, Gemini, Perplexity and Google's AI surfaces and reports share of voice, mentions, visibility, position and sources. brandofy.ai

Seerly is particularly close to what you're describing: it runs live prompts, breaks visibility down by engine, and shows category-level and per-engine share of voice versus competitors. seerly.app

CrowdReply calculates SoV by brand × LLM × prompt category × intent, which is useful if you want to answer questions like "What's our share of AI recommendations for running shoes?" rather than just "How often is our brand mentioned?" crowdreply.io

And Google itself has started exposing this concept in Merchant Center. Its AI Performance Insights reports your share of voice against competitors for conversational shopping queries, broken down into Discovery, Evaluation, and Purchase stages. The catch is that it currently covers Google's own AI ecosystem rather than all assistants. support.google.com

The important distinction

If you're evaluating these for an ecommerce business, I wouldn't settle for a generic "AI visibility score." I'd want a platform that can show something like:

"For 500 buyer-intent prompts in our category, we're mentioned in 18% of AI answers, versus Nike 31%, Adidas 24%, and Hoka 12%."

And then drill down to:

• ChatGPT: 22% SoV
• Gemini: 14%
• Perplexity: 19%
• Claude: 11%
• Google AI: 17%
• Discovery vs. comparison vs. purchase-intent prompts
• Which products/SKUs are being recommended
• Which competitors replace you when you're absent
• Which websites/sources are causing the AI to recommend competitors
• Exact prompts and AI responses
• Trend over time

That's increasingly possible. For instance, RivalSee explicitly offers competitor SoV across multiple AI platforms, while Birdeye Search AI lets you toggle SoV by individual AI platform or aggregate them. www.rivalsee.com

If you're asking because you're considering building/buying this for an ecommerce brand, there's an interesting gap: most of these products are essentially SEO rank trackers translated into LLMs. The more sophisticated opportunity is measuring AI shopping share of voice at the product/category/query level, not merely brand mentions.

If you tell me your ecommerce category (e.g. beauty, apparel, supplements, electronics), I can compare the 5–10 leading platforms specifically for ecommerce and tell you which one I'd pick.

Yes. The category is usually called AI visibility tracking, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), or LLM share-of-voice tracking. Several platforms now measure how often an ecommerce brand appears in answers from ChatGPT, Claude, Gemini, Perplexity, and other conversational assistants. usehall.comwww.quattr.com

Some options:

For an ecommerce use case, the metrics I’d look for are:

• Brand share of voice: % of relevant shopping prompts where your brand appears
• Product mention rate: which SKUs get recommended
• Position/ranking in answers: first recommendation vs. buried mention
• Competitor displacement: who is winning prompts you care about
• Citation share: which websites/products AI systems rely on
• Prompt coverage: whether you appear for “best X,” “X vs Y,” “alternatives to X,” etc.

A few caveats:

• There is not yet a universal “Nielsen rating” for AI assistants; each platform usually creates a tracked prompt set and measures results over time.
• Results can vary by model version, geography, user context, and whether the assistant has shopping integrations enabled.
• For ecommerce, tools that connect AI visibility to product catalogs, feeds, reviews, and structured data tend to be more useful than generic brand-monitoring tools. www.yotpo.com

If you’re evaluating this for a large ecommerce site (100k+ SKUs) versus a Shopify/DTC brand, the shortlist would look different.

Yes. This category is emerging quickly under names like AI visibility, GEO/AEO, or AI Share of Voice. There are now platforms specifically designed to measure how often an ecommerce brand/product gets mentioned or recommended versus competitors across conversational assistants.

A few worth looking at:

For example, Parcel Perform explicitly reports market share relative to competitors in AI recommendations, while tracking ChatGPT, Gemini, Perplexity and Claude. www.parcelperform.com

GoVISIBLE Commerce is particularly interesting if you're thinking like an ecommerce analytics team: it tracks individual products/SKUs, retailers, categories, query types, AI engine, competitors and price points across ChatGPT, Gemini, Copilot and Perplexity. govisible.ai

Alhena goes even further toward a commerce-native model: it claims SKU-level visibility, product-rendering analysis, revenue attribution by AI source, and connections to the live storefront. alhena.ai

And Auspex is explicitly calculating product/brand citation share and competitor share-of-voice, with per-engine visibility metrics. useauspex.ai

The important distinction

If by "AI share of voice" you mean something like:

Of all the times shoppers ask AI assistants about my category, what percentage of the recommendations/mentions go to my brand vs. Nike, Adidas, Hoka, etc.?

Yes — that's now a measurable product category.

But I'd distinguish that from a simple AI visibility score. A useful ecommerce SOV product should ideally give you:

1. Share of answers — % of relevant AI responses mentioning you.
2. Share of recommendations — % where you're actually recommended.
3. Position/share of shortlist — are you #1, #2, etc.?
4. Competitor SOV — your 18% vs. competitor A's 31%, etc.
5. By assistant — ChatGPT vs. Gemini vs. Perplexity vs. Claude.
6. By intent — "best X", "X for running", "X under $100", "compare X vs Y", etc.
7. By SKU/product — not just brand-level visibility.
8. Citation/source share — why the model knows about you and which sites it trusts.
9. Trend over time — SOV increasing/decreasing.
10. AI → revenue attribution — ultimately, whether visibility turns into sales.

That last distinction is important because "mentioned" ≠ "recommended" ≠ "clicked" ≠ "purchased."

There are already tools covering pieces of this, but the market is still immature. One 2026 comparison identified roughly 18 AI-visibility platforms for ecommerce, with only a subset offering share-of-voice, product-query monitoring, or agent visibility. useauspex.aiecommerceguide.com

If you're asking because you're evaluating whether to build a product in this space, I can also map out the competitive landscape (Profound, Evertune, AthenaHQ, Scrunch, Goodie, etc.) and what the current platforms do/don't measure, which is probably the more interesting question.

Yes — but the category is still emerging. The thing you’re describing is usually called AI Share of Voice (AI SOV), Generative Engine Optimization (GEO) tracking, AI visibility monitoring, or LLM brand monitoring. It’s analogous to SEO rank tracking, but for answers generated by ChatGPT, Gemini, Claude, Perplexity, Copilot, Amazon shopping assistants, etc. AI shopping assistants are becoming a meaningful discovery channel for ecommerce brands, which is driving demand for these tools. www.emarketer.comwww.emarketer.com

Some platforms to look at:

For an ecommerce company, the metrics you’d probably want are:

• AI Share of Voice: % of relevant shopping prompts where your brand appears
• Position/share of recommendations: e.g., “best running shoes for marathon training” → how often you’re recommended vs Nike, Brooks, Hoka, etc.
• Citation share: which domains AI assistants rely on when mentioning your brand
• Sentiment/positioning: whether assistants describe you as premium, affordable, sustainable, etc.
• Competitor displacement: prompts where competitors appear and you don’t
• Conversion/referral impact: AI-driven traffic and revenue attribution where available www.emarketer.comwww.emarketer.com

A few caveats:

• There is not yet a universal Nielsen-like “AI SOV” standard across ChatGPT + Gemini + Claude + Amazon + Perplexity.
• Many tools rely on sampled prompt sets, so results can differ depending on the prompt universe.
• Ecommerce-specific tracking is harder because product recommendations change based on location, inventory, pricing, reviews, and feeds. AI shopping assistants are increasingly influencing purchase journeys, which makes catalog quality and product data important inputs. www.emarketer.com

If you’re an ecommerce brand, I’d evaluate vendors by asking:

1. Can I upload my product catalog/SKUs?
2. Can it track category-level prompts (“best protein powder for women”)?
3. Does it compare me against named competitors?
4. Does it show why I won/lost (citations, reviews, product attributes)?
5. Can it connect AI visibility to Shopify/GA4 revenue?

If you mean “AI share of voice specifically for product recommendations inside ChatGPT, Gemini, Claude, Amazon Rufus, etc.”, the market is much smaller and I’d look more closely at Profound, Scrunch AI, and Peec AI rather than traditional SEO tools.

Yes. This is now a fairly well-defined category usually called AI search visibility, GEO (generative engine optimization), or AI share of voice / share of model.

For an ecommerce site, I'd shortlist these:

Otterly, for example, explicitly reports “Share of AI Voice”, competitor mentions, and visibility by individual engine. otterly.ai Semrush likewise has an AI Share of Voice metric and lets you break it down by platform. www.semrush.com

What I'd look for specifically for ecommerce

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

“Does ChatGPT mention my brand?”

You want something closer to:

For 500 high-intent shopping prompts, what percentage of the AI-generated consideration set contains my brand/products, compared with Amazon, Walmart, Target, competitors, etc.?

And ideally:

Prompt → Assistant → Response → Brands/products mentioned → Position → Citation/source → SOV

For example:

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

One caveat

The category is very young, and “share of voice” isn't standardized. Different vendors weight mentions, ranking/position, citations, prompt volume, and sometimes search volume differently. www.influencers-time.com

For ecommerce specifically, I'd therefore prioritize a platform that lets you see the underlying prompts and raw AI responses, not just gives you a proprietary 0–100 score.

If your goal is to measure an ecommerce brand's AI SOV across ChatGPT + Gemini + Perplexity + Claude and competitors, Otterly, Profound, and Semrush are the three I'd investigate first. If AI-attributed revenue/referral traffic is important too, I'd add Indexly to that shortlist. indexly.ai

If you tell me roughly your ecommerce category + Shopify/other platform + number of SKUs, I can narrow this to the 2–3 tools that are actually best suited to your use case.

Yes. This is now a real category—usually called AI visibility, GEO/AEO, or Share of AI Voice—and several platforms specifically measure how an ecommerce brand appears across conversational assistants.

A few worth looking at:

• Hall — tracks brand presence, sentiment, share of voice, and citations across ChatGPT, Gemini, Perplexity, Claude, Copilot, Google AI Overviews, and others. It also has website/citation and AI-agent analytics. usehall.com
• Surfient — particularly ecommerce/Shopify-oriented. It tracks Share of AI Voice at the category, brand, and product level, with competitor comparisons across ChatGPT, Perplexity, Claude, Gemini, Copilot and Google AI Overviews. www.surfient.com
• Quadrant — positioned toward enterprise retail/FMCG, with prompt-level measurement across ChatGPT, Gemini, Perplexity and Claude and metrics including citation rate and share of voice. geoblog.projectquadrant.com
• Semrush / Ahrefs / similar SEO suites are also moving into AI visibility tracking, although they're broader SEO platforms rather than ecommerce-first AI-share-of-voice products. A recent comparison found substantial variation in which engines and metrics each platform covers. ecommerceguide.com

What I'd look for specifically

If your goal is something analogous to Google Search Console + Semrush, but for ChatGPT/Gemini/Perplexity, I'd want the platform to show:

The important distinction is mention share vs. citation share. A brand can be named without its website being cited, and those have very different commercial implications. Surfient, for example, explicitly separates strong linked citations, unlinked mentions, and weaker generic references. www.surfient.com

And this is becoming particularly relevant for ecommerce: recent retail reporting shows brands such as Walmart, Ulta and Wayfair actively optimizing for shopping discovery in ChatGPT and Gemini. www.reuters.com

If you're evaluating this as a potential product/category rather than just looking for a tool, there's an interesting gap here: the really useful version isn't simply "how often does ChatGPT mention my brand?" It's AI SOV × category × product × competitor × assistant × revenue/traffic. That could become much closer to a "Nielsen/Similarweb for AI shopping."

Yes. There’s now a fairly active category for this, usually called AI visibility, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), or AI Share of Voice.

For an ecommerce site, the important distinction is whether a platform merely tracks mentions or actually measures competitive share of the answers to shopping/category prompts.

Platforms worth looking at

For example, Seerly's visibility platform explicitly reports share of voice by category, competitor, and individual AI engine, rather than giving you just one overall score. seerly.app

SkuLift AI Share of Voice is particularly close to what you're describing: it defines SOV as the percentage of AI answers in a defined query set where your brand appears/cites versus competitors, across ChatGPT, Claude, Perplexity and Gemini. www.skulift.com

And Verity Score's AI Share of Voice guide is interesting for ecommerce because it explicitly covers DTC/ecommerce and emphasizes running the same prompts multiple times because AI responses aren't deterministic. verityscore.ioarxiv.org

What I'd want for an ecommerce use case

If you're evaluating these platforms, I'd make sure they can answer questions like:

"For people asking AI assistants for the best running shoes under $150, what percentage of answers mention Nike vs Adidas vs Hoka vs my brand?"

And then break that down into:

• ChatGPT SOV: 18%
• Gemini SOV: 11%
• Claude SOV: 7%
• Perplexity SOV: 23%
• Google AI Mode/Overviews: 15%
• Overall: 16%

Then drill into which prompts you win/lose, where competitors are cited, which sources AI is using, and whether you're actually recommended as a product vs merely mentioned.

That's becoming particularly important for ecommerce because AI-generated shopping recommendations are becoming a meaningful acquisition channel; Reuters reported recently that retailers including Walmart, Ulta and Wayfair are actively adapting their content for ChatGPT/Gemini shopping discovery. www.reuters.com

One important caveat

I'd be careful with platforms that give you a single "AI visibility score." SOV needs to be calculated from a defined prompt universe and repeated runs. AI answers can vary substantially from one run to another, and different assistants retrieve very different sources. Research has also found significant differences in retrieval between generative search systems. verityscore.ioarxiv.org

So if you're asking because you're considering building/buying a platform for this, there absolutely is a market—but the more interesting product is probably "Semrush/Ahrefs for AI shopping visibility", rather than another generic AI brand-monitoring dashboard.

If you tell me your ecommerce category and approximate company size, I can also compare the 5–10 leading platforms specifically on price, AI engines, product-level tracking, SOV methodology, and Shopify/ecommerce integrations.

Yes. There’s now a growing category of AI visibility / AI share-of-voice platforms that do roughly what you’re describing: they run buyer-intent prompts across multiple conversational/search assistants, identify which brands/products are mentioned, and benchmark your visibility against competitors.

For an ecommerce site, I’d look at these first:

The closest match to what you're asking

If your question is essentially:

"For queries like 'best running shoes for flat feet,' what percentage of AI recommendations does my ecommerce brand/product get vs Nike, Hoka, Brooks, etc., across ChatGPT, Gemini, Perplexity, Claude, and other assistants?"

then Alhena, Quadrant, and ProductSup are probably the most interesting to investigate.

Alhena explicitly positions itself around AI-generated shopping answers, with product-level visibility and the ability to connect visibility to revenue. alhena.ai

Quadrant is particularly close to the classic Share of Voice concept: its dashboard shows overall SOV plus visibility broken down by individual AI platforms, including ChatGPT, Gemini, Perplexity, Claude, Grok and Google AI surfaces. www.projectquadrant.com

ProductSup is interesting if you have a large product catalog, because its AI Visibility dashboard is built around shopper intents and can monitor brands, products and categories across AI engines. help.productsup.com

One important caveat

I'd be careful treating "AI Share of Voice" as an exact equivalent of Google Search SOV.

LLM responses are stochastic: the same prompt can produce different recommendations at different times. Recent research specifically finds substantial variability in AI citation/visibility measurements and argues that good systems should use repeated sampling and uncertainty estimates rather than treating a single run as definitive. arxiv.org

So the good platforms aren't merely counting brand mentions. Ideally you want:

• Category/discovery prompts, not just branded queries
• Brand/product mention rate
• Position/shelf placement in recommendations
• Share of voice vs competitors
• Sentiment / positioning
• Citation/source domains
• Breakdown by AI assistant
• Product-level visibility
• Visibility over time
• Prompt/query-level evidence
• Ideally, connection to traffic/revenue

If you're evaluating this from a product/market opportunity perspective, there's actually an interesting gap here: most of these tools are measuring brand visibility, while the really valuable ecommerce metric would be something closer to "AI commerce share of shelf" — when an AI assistant recommends products in a category, what percentage of the commercially relevant recommendations are yours, and does that recommendation ultimately generate a transaction?

If that's what you're thinking about building, I can also map out the existing players, their features/pricing, and where the white space is.

Yes. There are platforms emerging around AI Search / Generative Engine Optimization (GEO) that track how often an ecommerce brand or product appears in answers from ChatGPT, Gemini, Claude, Perplexity, and similar assistants.

The category is often called AI Share of Voice (SOV) or AI visibility.

A few platforms worth looking at:

• Profound — tracks brand visibility and mentions across AI search/conversational engines, including competitive comparisons.
• Otterly.AI — monitors how brands/products appear across AI answers and tracks visibility over time.
• Peec AI — focused on GEO/AI-search visibility, including rankings and competitor benchmarking.
• Scrunch AI — tracks brand presence and performance across AI search engines.
• AthenaHQ — AI visibility/GEO analytics with monitoring of how brands are represented in AI responses.

For ecommerce specifically, the interesting distinction is whether a platform can go beyond "did ChatGPT mention Nike?" and measure something like:

For 1,000 product/category prompts relevant to my store, what % of AI answers mention my brand/product, across ChatGPT + Gemini + Claude + Perplexity, versus competitors?

That's a much more useful definition of AI Share of Voice.

If you're evaluating this as a product/category opportunity, I can also map out which platforms actually support ecommerce/product-level SOV, what assistants they cover, their pricing, and where the gaps are.

Yes. The category is usually called AI visibility tracking, AEO (Answer Engine Optimization) analytics, GEO (Generative Engine Optimization) tracking, or AI Share of Voice. These platforms simulate shopper prompts across conversational assistants and measure whether your ecommerce brand/products appear, how often competitors appear, citations, sentiment, and rankings. www.topmention.aimentionable.ai

Some platforms to look at:

For an ecommerce site, I’d evaluate them based on whether they can answer:

1. Prompt coverage — Can you define your own buyer questions?

Example: “best running shoes for flat feet,” “best protein powder under $50,” “alternatives to Brand X.”

2. Assistant coverage — Does it include the assistants that matter for your audience?
   • ChatGPT
   • Gemini
   • Claude
   • Perplexity
   • Google AI Overviews / AI Mode (if relevant)

3. Product-level visibility — Does it tell you which SKU/product was recommended, not just whether your brand was mentioned?

4. Competitive share — Can you see:
   • Your mention rate %
   • Competitor mention rate %
   • Position in recommendations
   • Citation sources driving visibility

5. Actionability — Does it explain why a competitor won (reviews, content, feeds, third-party mentions, structured data, etc.)?

If you are thinking about building this capability internally, the core metric is usually something like:

AI Share of Voice = (number of relevant AI answers mentioning your brand ÷ total tracked AI answers) × 100

with additional weighting for position (e.g., #1 recommendation vs. a passing mention). www.topmention.ai

For a Shopify/DTC brand, I’d start by testing TopMention, Surfient, SearchMention, and Livesov; for an enterprise SEO team, broader AI visibility platforms may be a better fit. www.topmention.ai

Yes. There’s now a fairly clear category emerging around AI Search Visibility / Generative Engine Optimization (GEO), and several platforms measure something close to “AI share of voice” across conversational assistants.

For an ecommerce site, I’d look at these:

For example, GetMint explicitly reports visibility, citations, sentiment, and share of voice, while DeepSmith reports mention rate, citation rate and SOV, broken down by engine. www.getmint.ai

What I'd measure for an ecommerce brand

The interesting part is that “share of voice” shouldn't just mean how many times the brand name appears. A useful dashboard would have something like:

AI SOV

% of relevant AI recommendations where your brand/product appears vs. competitors

Then break it down by:

• Assistant: ChatGPT vs Gemini vs Claude vs Perplexity
• Category: “best running shoes”, “best skincare for dry skin”, etc.
• Intent: discovery / comparison / transactional
• Position: #1 recommendation, #2, #3, etc.
• Product: individual SKU/product visibility
• Sentiment: positive / neutral / negative
• Citation: which websites/pages the assistant used
• Competitors: who wins the recommendation when you don't
• Trend: SOV over time

There are already Shopify-focused products moving in exactly this direction. Shop Mentions, for example, positions itself as Shopify-native and tracks whether AI assistants recommend your products, including competitor comparisons. shopmentions.com

One important caveat

I'd be careful treating the reported SOV number as an absolute truth. AI answers are non-deterministic: the same prompt can produce different answers at different times. Recent research specifically finds substantial variability in citation/visibility measurements across repeated queries. arxiv.org

So the better metric is something like:

“Across 1,000 representative buyer prompts, what percentage of responses recommend us, and how does that compare with competitors?”

rather than:

“Our AI visibility score is 63.”

If you're asking because you're evaluating this as a product/category opportunity, there's an especially interesting gap between generic AI-visibility tracking and ecommerce-specific AI SOV—product/SKU-level visibility, category share, retailer availability, pricing, and actual AI-assisted conversions. I can map out the existing competitive landscape and what seems genuinely underserved.

Yes. A new category of tools has emerged around AI visibility, AI search optimization, and LLM share of voice. These platforms measure how often your brand or products appear in responses from conversational AI systems like ChatGPT, Gemini, Claude, Perplexity, and others.

Some of the better-known options include:

What "AI share of voice" usually means

These platforms typically:

• Run hundreds or thousands of prompts relevant to your category.
• Query multiple AI assistants (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.).
• Measure:
  • Frequency your brand appears.
  • Position in recommendations (first, second, etc.).
  • Competitors appearing alongside you.
  • Sources or websites the models cite.
  • Trends over time.
  • Geographic or persona differences.

For an ecommerce company, you might track prompts like:

• "Best running shoes under $150"
• "Best protein powder for women"
• "Best office chair for back pain"
• "What espresso machine should I buy?"

The platform then reports something like:

Many also calculate an "AI visibility score" by weighting ranking position and frequency.

Ecommerce-specific metrics

The more advanced products can also monitor:

• Product-level visibility (not just brand-level)
• Category coverage
• Citation sources influencing AI answers
• Retailer mentions (Amazon, Walmart, Shopify store, etc.)
• Review site influence
• Seasonal changes in AI recommendations
• Impact of content or SEO changes on AI visibility

If you're looking for enterprise-grade analytics

For a medium-to-large ecommerce business, I'd look at:

1. Profound — one of the most mature AI visibility platforms for large brands.
2. Otterly.AI — easier to adopt for SEO and content teams.
3. Peec AI — strong focus on AI search rankings and share of voice.

If your goal is product recommendation share of voice (for example, "How often does ChatGPT recommend my specific SKU versus competitors?"), the field is still developing. Most platforms currently focus on brand- and category-level visibility, though several are adding product-level tracking as retailers increasingly optimize for AI-driven shopping experiences.

Yes. This has become a new category often called AI visibility, AI search analytics, or LLM share of voice. These platforms measure how often brands or products are recommended or mentioned by conversational AI systems such as ChatGPT, Gemini, Claude, Perplexity, Copilot, and others.

Some of the more established options include:

What they typically measure

Most platforms report metrics such as:

• Share of Voice (SOV): How often your brand appears versus competitors.
• Recommendation rate: How frequently your products are suggested for buying-related prompts.
• Ranking/position: Whether your brand appears first, second, etc., in AI-generated answers.
• Sentiment: Whether the AI presents your brand positively, neutrally, or negatively.
• Citation sources: Which websites or documents AI systems appear to rely on when mentioning you.
• Prompt categories: Performance by prompt type (e.g., "best running shoes under $150" vs. "best sustainable sneaker").
• Historical trends: Changes in visibility over time after content or site updates.

For ecommerce specifically

If you sell products online, the most valuable capability is usually product-level visibility, not just brand visibility. For example, you might want to know:

"For 'best ergonomic office chair under $500,' how often does ChatGPT recommend our Model X compared to Herman Miller, Steelcase, and Branch?"

The better platforms can track hundreds or thousands of prompts across:

• Product discovery
• Category recommendations
• Gift guides
• Comparison queries
• Purchase intent questions
• Brand research questions

Current limitations

There isn't a single authoritative "AI share of voice" metric because each assistant has different models, retrieval systems, and ranking behavior. Most platforms estimate visibility by:

1. Running large sets of prompts on a schedule.
2. Recording which brands appear and where.
3. Aggregating the results into dashboards.

That makes these metrics useful for tracking trends and competitive positioning, but they aren't equivalent to traditional search impression share.

If you're evaluating vendors

For an ecommerce business, I'd look for a platform that supports:

• Multiple AI assistants (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.)
• Custom prompt sets based on your product catalog
• Competitor benchmarking
• Product- and SKU-level reporting
• Citation/source tracking
• API access or exports to your BI tools
• Scheduled monitoring rather than one-off prompt testing

If your catalog has more than a few hundred products, enterprise-focused platforms like Profound tend to be the most feature-rich. For smaller ecommerce teams, Otterly.AI or Peec AI may offer a more approachable starting point.

Yes. This is an emerging category often called AI visibility, LLM SEO, AI search analytics, or AI share of voice. There isn't yet a universal equivalent of Google Search Console for conversational AI, but several platforms attempt to measure how often brands and products appear across assistants like ChatGPT, Gemini, Claude, Perplexity, and others.

Some of the more established options include:

For ecommerce specifically

The better platforms typically let you:

• Track visibility for thousands of product-related prompts (e.g. "best running shoes under $150")
• Compare your brand against competitors
• Break down visibility by AI assistant (ChatGPT vs. Gemini vs. Perplexity, etc.)
• Measure citation frequency and source attribution
• Monitor changes over time
• Identify prompts where your products are absent but competitors appear

Some also estimate:

• AI Share of Voice (%) = your brand appearances ÷ all brand appearances for a prompt set
• Sentiment
• Recommendation rank (1st recommendation vs. 5th)
• Citation quality
• Traffic opportunities

If you're looking for true "AI Share of Voice"

The closest products today are probably:

1. Profound (most mature for enterprise brands)
2. Peec AI (purpose-built around AI search visibility)
3. Otterly.AI (popular with marketing teams)
4. Scrunch AI (strong for larger organizations)

These are analogous to SEO rank trackers, but for generative AI.

One limitation

No platform has direct access to the internal ranking systems of ChatGPT, Claude, Gemini, or other assistants. Instead, they generally:

• Run large prompt sets repeatedly across multiple AI systems.
• Record which brands and products appear.
• Aggregate results into visibility and share-of-voice metrics.
• Track trends over time.

Because AI responses can vary between users, locations, and over time, these measurements are best viewed as directional benchmarks rather than exact market share.

If you're running a medium-to-large ecommerce business (10,000+ SKUs), I'd also look for platforms that support SKU-level or category-level visibility, since that's becoming a key differentiator beyond simple brand-level AI share of voice.

Yes. This has become a new category often called AI visibility, AI Share of Voice (AI SoV), or Generative Engine Optimization (GEO). Several platforms now measure how often your brand appears across conversational assistants like ChatGPT, Gemini, Perplexity, Claude, and Google AI experiences.

For ecommerce, the strongest options are:

What these platforms actually measure

Most of them report metrics like:

• Share of Voice: What percentage of AI responses mention your brand versus competitors.
• Prompt coverage: Which shopping questions your brand appears for.
• Citation sources: Which pages the LLM is using when it recommends your products.
• Ranking/position: Whether you're the first recommendation or buried lower in the response.
• Competitor comparison: Which brands consistently outrank you.
• Per-assistant performance: You might dominate ChatGPT but barely appear in Gemini.

One important finding from recent research is that AI assistants behave very differently. A brand that performs well in ChatGPT may not perform well in Gemini or Perplexity, so measuring only one assistant can give a misleading picture. trakkr.aiverityscore.io

For ecommerce specifically

The most valuable prompts are usually things like:

• "Best running shoes under $150"
• "Best organic mattress"
• "Best coffee grinder for espresso"
• "Where should I buy skincare online?"
• "Alternatives to Allbirds"

The better platforms continuously run hundreds or thousands of these purchase-intent prompts across multiple LLMs and track:

• whether your store appears
• which products appear
• how frequently you're recommended
• which competitors displace you over time

If you're building an ecommerce dashboard

A useful "AI Share of Voice" product would combine:

• AI assistant visibility (ChatGPT, Gemini, Claude, Perplexity)
• Google AI Overviews/AI Mode visibility
• AI referral traffic (from GA4)
• Conversion rate by AI source
• Revenue attributed to AI assistants
• Citation/source monitoring
• Competitor AI SoV trends

That gives both visibility ("Are we being recommended?") and business impact ("Did those recommendations drive sales?").

This area is growing quickly because AI shopping referrals are increasing and often convert well, even though they still represent a relatively small share of overall ecommerce traffic today. www.reuters.com

Yes. This has become a new category often called AI visibility, AI Share of Voice (AI SoV), or Generative Engine Optimization (GEO). Several platforms now track how often a brand appears across conversational AI assistants, although they differ in coverage and depth.

For an ecommerce brand, these are the strongest options:

For ecommerce specifically

If you're interested in products (not just brand mentions), there are two emerging approaches:

1. Brand Share of Voice
   • "Best running shoes"
   • "Best coffee makers"
   • "Best skincare for dry skin"

The platform measures:

• How often your brand is recommended
• Which competitors appear instead
• Which citations the AI uses
• Trends over time

2. Product-level visibility
   • Whether specific SKUs appear
   • Which product attributes AI cites
   • Which retailers are recommended
   • Shopping-specific prompts

This second capability is newer and not every platform supports it well.

Google's ecommerce reporting

Google has also begun introducing AI Performance Insights in Merchant Center for ecommerce merchants. It includes AI-specific impression metrics and Share of Voice within Google's AI shopping experiences, making it one of the first native AI visibility reports for merchants. www.digitalapplied.com

What the best platforms measure

The more mature tools typically report:

• AI Share of Voice by assistant (ChatGPT vs Gemini vs Perplexity, etc.)
• Brand recommendation frequency
• Competitor comparison
• Citation sources
• Prompt categories (informational vs purchase intent)
• Sentiment of recommendations
• Geographic differences
• Historical trends

For ecommerce, they'll often segment prompts like:

• "best espresso machine under $500"
• "where should I buy hiking boots"
• "best protein powder"
• "gift ideas for runners"

and show how frequently your products or brand appear.

Current limitations

No platform has complete visibility because OpenAI, Anthropic, Google, and others don't provide APIs exposing every recommendation they generate. Most vendors maintain large libraries of prompts, execute them on a schedule across multiple assistants, and aggregate the results into an AI Share of Voice metric. That means the numbers are directional rather than exhaustive, but they're still useful for tracking changes over time. www.reddit.com

If your focus is consumer ecommerce (Shopify, BigCommerce, Magento, etc.), I'd narrow the field to:

• Profound for enterprise brands with larger budgets.
• Semrush AI Toolkit if you're already using Semrush for SEO and want AI visibility alongside traditional search.
• Scrunch AI if your goal is improving AI discoverability across multiple assistants.

Are you looking for a platform to measure AI visibility, or one that also provides recommendations to improve your visibility in AI assistants?