Answers that name a competitor

For a small ecommerce shop on a tight budget, I’d start with Otterly.ai.

• Otterly — about $29/month at the entry level, with tracking for 15 prompts across ChatGPT, Google AI Overviews, Perplexity, and Copilot. It can show whether you're mentioned/cited and which URLs AI assistants are using. loudmink.ai
• Peec AI — roughly $95/month+; better if you need substantially more prompt tracking and broader analytics, but probably overkill initially. omidsaffari.com
• Profound — much more powerful, but aimed at larger teams and substantially more expensive. I'd skip it for now. omidsaffari.com

One important ecommerce wrinkle: if your real question is “Which of my individual products/pages get recommended by ChatGPT, Gemini, etc., and why?”, rather than simply “Does my brand appear?”, I'd also look at an ecommerce-specific product. Some newer tools are moving toward product-level AI recommendation tracking, rather than just brand/prompt monitoring. www.trustnoww.com

What I'd do with $30/month

Set up ~10–15 high-value prompts such as:

• “best [product category] for [use case]”
• “best [product type] under $X”
• “[competitor] alternatives”
• “where to buy [product/category]”
• “best [product category] for [customer type]”

Then track whether your products appear, which of your URLs get cited, which competitors appear instead, and whether that changes over time.

If you tell me roughly how many products you sell and your product category, I can narrow this down to the cheapest tool that actually tracks individual product pages well, rather than just brand mentions.

Yes. For a mid-market SaaS team, I’d shortlist Profound and OtterlyAI first. Both are specifically built around AI-search visibility rather than traditional SEO rank tracking.

1. Profound — my first choice

Profound gives you Share of Voice, Visibility Score, competitor ranking, Citation Share, mention position, and sentiment, broken down by platform, topic and prompt. It can also identify competitors based on who is actually winning AI citations, rather than relying solely on the competitor list you give it. Profound Profound Knowledge Base

The particularly useful metric for your use case is Citation Share: you can see your domain's percentage of citations versus competitors and trend it over time, including by platform, topic and prompt. Profound Knowledge Base Profound

It tracks major answer engines including ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews/AI Mode, Copilot, Grok and DeepSeek. Profound

I'd choose it if: your team wants a serious competitive-intelligence dashboard and expects to use the data to drive content/AEO decisions.

2. OtterlyAI — probably the one I'd demo alongside it

Otterly has a very direct Share of Voice vs. competitors view, with trends by prompt, engine and market. Its citation reporting shows which URLs AI engines cite, how often they're cited, and whether those citations go to you or competitors. Otterly OtterlyAI

It also lets you discover competitors that appear in your tracked AI answers but weren't originally on your list, and it doesn't impose a competitor-count limit. OtterlyAI

I'd choose it if: you want the core measurement—"Are we showing up, who beats us, and what sources are getting cited?"—without necessarily buying the broader enterprise-oriented platform.

What I'd actually measure

For a SaaS competitive program, I wouldn't stop at a single "AI visibility" score. I'd build the dashboard around:

• Share of Voice: % of AI brand mentions belonging to you vs. each competitor.
• Citation Share: % of source citations going to your domain vs. competitors.
• Mention position: Are you first/second/third when you're mentioned?
• Coverage: % of your tracked prompts where you appear at all.
• Competitive gaps: prompts where a competitor appears and you don't.
• Citation winners: domains/pages that repeatedly get cited instead of your content.
• Engine breakdown: ChatGPT vs. Gemini vs. Perplexity vs. Google AI results.
• Trend: weekly/monthly change rather than reacting to individual answers.

That distinction between mention share and citation share is important: you can be frequently mentioned as a SaaS vendor while competitors' websites are actually supplying the sources AI uses to construct the answer. Profound explicitly separates these metrics. Profound

Bottom line: I'd run a Profound vs. OtterlyAI bake-off using ~50–100 real commercial prompts in your category. Compare not just the dashboards, but whether their underlying answers/citations correspond to what your team sees in the actual AI products. For a mid-market SaaS team, OtterlyAI is the one I'd investigate for simplicity/value; Profound is the one I'd investigate for depth and competitive intelligence.

It tracks major answer engines including ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews/AI Mode, Copilot, Grok and DeepSeek. Profound

I'd choose it if: your team wants a serious competitive-intelligence dashboard and expects to use the data to drive content/AEO decisions.

2. OtterlyAI — probably the one I'd demo alongside it

Otterly has a very direct Share of Voice vs. competitors view, with trends by prompt, engine and market. Its citation reporting shows which URLs AI engines cite, how often they're cited, and whether those citations go to you or competitors. otterly.ai help.otterly.ai

It also lets you discover competitors that appear in your tracked AI answers but weren't originally on your list, and it doesn't impose a competitor-count limit.

I'd choose it if: you want the core measurement—"Are we showing up, who beats us, and what sources are getting cited?"—without necessarily buying the broader enterprise-oriented platform.

What I'd actually measure

Yes. If you're a startup with no developer resources, I’d start with OtterlyAI.

My shortlist

\*Prices can change; I checked current published information.

Why Otterly is my pick: it is essentially no-code: you define the prompts your prospects might ask, and it automatically runs them against multiple AI engines and reports whether your brand appears, where it ranks, sentiment, competitors, and citations. It currently covers seven major AI search engines. otterly.aiotterly.ai

The $29/month entry point makes it particularly appropriate for a bootstrapped startup. Its current site says pricing starts at $29/month and offers a free trial without requiring a credit card. otterly.aiotterly.ai

One important distinction

These aren't really monitoring every conversation an AI assistant has. They work by repeatedly testing a set of commercially relevant prompts and seeing whether your brand/product appears.

For example, you'd monitor prompts like:

• “Best [category] tools for startups”
• “[Competitor] alternatives”
• “What software should I use for [problem]?”
• “Best [product category] under $X”
• “Is [your product] worth it?”
• “Compare [your product] vs [competitor]”

That is actually more useful for marketing than trying to capture every incidental mention.

If your budget is ~$30–50/month, I'd choose OtterlyAI. If you're willing to spend ~$100+/month and want deeper competitive analytics, I'd look at Peec. Peec currently tracks visibility, position, sentiment and share of voice across AI platforms, but its starter brand plan is substantially more expensive. peec.ai

If you tell me your product/category and monthly budget (e.g. $30, $50, $100), I can narrow this to the best 1–2 options and tell you exactly what prompts I'd monitor.

If you want AI Share of Voice trends alongside traditional search/SEO metrics in one dashboard, I’d shortlist these:

• semrush.com — best overall fit. Its Enterprise AI Optimization product explicitly puts AI Share of Voice and SEO Share of Voice trends side-by-side, with prompt-vs-keyword comparisons. Semrush Semrush
• rankseer.com — strong integrated option. It combines AI SOV/citation tracking for ChatGPT, Perplexity and Gemini with classic SEO tools such as rank tracking, site audits and competitive analysis in the same platform. Rankseer Rankseer
• searchdock.io — interesting if you want GSC + AI visibility. It puts Google Search Console rankings alongside AI share of voice, with per-engine historical trends. SearchDock
• serprecon.com — good for search-focused marketers. It tracks SOV across Google, ChatGPT and Perplexity and lets you trend organic and AI visibility over time. SERPrecon
• pi-datametrics.com — strongest enterprise search-visibility angle. Its SOV reporting covers traditional search, AI Overviews and 30+ SERP features, with competitor benchmarking and historical trends. Pi Datametrics

My pick for a growth marketer: Semrush if you already care about keyword rankings, traffic, competitors and reporting and want AI visibility added to that workflow. If your priority is specifically GSC + AI citations/SOV in one lightweight workspace, I'd look closely at SearchDock.

If you tell me your stack (e.g. Semrush/Ahrefs + GA4 + GSC) and whether you care about ChatGPT, AI Overviews, Perplexity, or all of them, I can narrow it to the best 2–3.

If the goal is specifically “which content pieces are being crawled/cited by AI, and which of those pieces ultimately generate visits/conversions?”, I’d separate the problem into crawler telemetry, AI citation/visibility, and first-party attribution. No single tool is perfect at all three.

My shortlist

1. Scrunch — probably closest to what you're describing

Scrunch

Scrunch has a particularly relevant two-layer model:

• Agent Traffic: identifies AI bots visiting your site, including the bot/model, request type, frequency, and specific content pages crawled.
• AI Referrals: connects to GA4 and identifies human sessions coming from AI platforms, including landing pages, sessions, views, transactions and revenue. scrunch.com

That makes it possible to construct something like:

Content URL → AI crawler activity → AI citation/visibility → AI referral → conversion/revenue

That's much closer to actual content-level AI attribution than simply measuring “AI traffic.”

One particularly useful distinction is that Scrunch separates training/indexing/retrieval bot traffic. Retrieval traffic is arguably the most interesting crawler signal because it's associated with live AI usage rather than generic model training. scrunch.com

2. Ahrefs Bot Analytics — best for “what AI bots actually crawled”

Ahrefs Bot Analytics

Ahrefs is very strong if your immediate question is:

Which AI agents are hitting which URLs, and how frequently?

It collects bot activity server-side through Cloudflare and breaks it down by individual bot, category, and crawled page. It can distinguish AI assistants, AI search crawlers, AI crawlers, etc. help.ahrefs.com

The major advantage is that this isn't dependent on JavaScript analytics. That's important because crawlers aren't going to execute your GA4 instrumentation like normal users.

But: Ahrefs Bot Analytics is fundamentally crawler analytics. It doesn't by itself give you the complete downstream chain from crawl → citation → human visit → revenue.

3. Similarweb — strongest for AI referral/competitive intelligence

Similarweb

Similarweb's AI Chatbot Traffic reporting identifies traffic coming from AI platforms and, importantly, has a Top Landing Pages from Chatbots report. It can also show which chatbot traffic is benefiting your site versus competitors. support.similarweb.com

I'd use it when you care about:

• ChatGPT vs Perplexity vs other AI sources
• competitor benchmarking
• traffic trends
• which pages are receiving AI-driven visits
• market-level AI discovery

I'd not choose it as the primary source for crawler-level attribution.

4. Botify — strongest enterprise/large-site option

Botify

Botify is compelling if you're dealing with hundreds of thousands/millions of URLs and want AI crawling integrated into an existing enterprise SEO/technical SEO operation.

Its Analytics suite works at the individual URL and segment level and combines bot behavior with user-visit data. support.similarweb.comsupport.botify.com It also now has an AI Visibility dashboard measuring how brands/content appear in AI-generated results. support.botify.com

I'd favor Botify over Scrunch if the organization already has a sophisticated enterprise SEO/data infrastructure.

What I'd actually build

For serious content attribution, I'd not rely on a single vendor.

I'd create a canonical content-level dataset:

CONTENT
  content_id
  url
  content_type
  author
  publish_date
  topic
  revenue_category

AI CRAWLING
  timestamp
  bot
  AI_platform
  crawl_type
  content_id
  HTTP_status

AI VISIBILITY
  timestamp
  AI_platform
  prompt
  content_id
  citation
  citation_position

AI REFERRAL
  timestamp
  AI_platform
  content_id
  session_id

OUTCOME
  session_id
  content_id
  conversion
  revenue

Then you can answer much more valuable questions:

“Which articles are being used by AI systems?”

→ crawler + citation data

“Which articles actually cause AI-generated traffic?”

→ AI referral + landing-page data

“Which articles produce revenue after AI discovery?”

→ GA4/CRM + content ID

“Which content is crawled heavily but never cited?”

→ crawler data − citation data

“Which content is cited frequently but generates no clicks?”

→ citation data − referral data

That last set of metrics is where I think the real strategic value is.

My recommendation

If you're choosing one product to evaluate first, I'd start with Scrunch because it most directly covers the bridge between AI agents → specific URLs → AI referrals → conversions. scrunch.com

If you need deep server-side crawler telemetry, add Ahrefs Bot Analytics.

If you're an enterprise publisher with a huge site and already have sophisticated SEO infrastructure, evaluate Botify.

And regardless of vendor, keep GA4/your CRM as the source of truth for revenue attribution rather than letting an AI-visibility vendor become your attribution system.

The important caveat: crawler activity isn't proof that a page was cited or influenced a user. I'd explicitly keep crawl, citation/visibility, referral, and conversion as four separate stages in the attribution model.

If the goal is specifically enterprise monitoring of AI-assistant answers for incorrect, unauthorized, or risky citations of your brand, I’d shortlist Profound, AthenaHQ, and Scrunch, with Profound as my first evaluation.

The important distinction

Don't buy a platform merely because it measures "AI visibility." Your requirement is closer to AI brand integrity / answer governance.

I'd require the platform to capture, for every monitored prompt:

1. Exact assistant answer
2. Brand/entity mentioned
3. Every citation/source URL
4. What claim the citation supposedly supports
5. Whether the cited source is authorized
6. Whether the source is actually saying what the AI claims
7. Incorrect facts / hallucinations
8. Competitor or third-party content being attributed to your brand
9. Engine, model, country, language and timestamp
10. Alerts + API/webhooks so violations can enter your existing GRC/SIEM/workflow system.

That last part matters: most AI-visibility products are primarily designed to answer "Are we being mentioned and cited?" rather than "Is this citation authorized and factually defensible?" The market is still relatively young. uxcontinuum.com

My recommendation

Start an enterprise evaluation with Profound and AthenaHQ, then use Scrunch as the technical comparison.

If your biggest risk is brand misinformation, I'd give AthenaHQ particular attention because hallucination detection and brand integrity are explicitly part of its positioning. If you need the broader enterprise AI-search intelligence platform, I'd start with Profound. technologyadvice.comotterly.ai

For a procurement/RFP, I'd make "unauthorized citation detection" and "claim-to-source verification" mandatory acceptance criteria, rather than assuming a conventional AI-visibility platform provides them.

If you tell me your approximate company size and whether you're protecting one brand or hundreds of brands/products, I can narrow this to a 2–3 vendor shortlist and give you an enterprise RFP scorecard.

Yes — what you’re looking for is generally called an AI search visibility / AEO / GEO platform. These tools repeatedly query AI assistants/search engines, record whether your brand/site appears, capture the URLs being cited, compare you with competitors, and increasingly recommend what to change.

My top picks

• otterly.ai — best overall starting point. It tracks citations and mentions across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot, and Claude. It also has citation-gap analysis, crawlability checks, content audits, competitor comparisons, and prioritized recommendations. Otterly Otterly AI
• tryprofound.com — strongest enterprise option. It has prompt monitoring, answer-engine visibility, citation tracking, competitive benchmarking, and recommendations/agent workflows. Its citation tooling specifically identifies the publishers and sources driving AI citations. Profound Knowledge Base Profound
• peec.ai — worth considering if your primary focus is marketing/SEO reporting and competitive visibility.

The distinction I'd pay attention to

There are actually two different things you may want to measure:

1. "Does ChatGPT/Perplexity/etc. mention my company?"

• Brand visibility
• Share of voice
• Position/ranking
• Sentiment
• "When AI answers a question, does it cite my website as the source?"

• Exact cited URLs
• Which competitor URLs get cited instead
• Which topics/pages produce citations
• Which third-party sites AI relies on
• What content/crawlability changes could increase your chances

For your wording — "crawl AI assistants to find where our site is being cited and how to improve visibility" — I'd prioritize the second capability.

Otterly, for example, explicitly tracks every cited URL, lets you see competitor citation gaps, and has recommendations covering crawlability, content, entities, news/media, Reddit, partnerships, and other off-page opportunities. Otterly AI Otterly AI

One particularly interesting feature is Agent Analytics: Otterly can analyze your own server logs to show which AI agents/crawlers are actually visiting your site and which pages they reach. That's complementary to citation tracking because being crawled ≠ being cited. Otterly AI

If I were evaluating these for a company today, I'd start with Otterly vs. Profound. Otterly looks particularly attractive if you want a practical self-serve system; Profound is more compelling if you're an enterprise SEO/content team wanting deeper citation intelligence and workflows.

If you tell me your site/category and roughly how large the company is, I can also compare Otterly vs. Profound vs. Peec on the things that matter most—coverage, citation accuracy, competitor analysis, recommendations, API, pricing, and enterprise features.

Yes — but there’s an important distinction between “the prompts that cause AI to cite/use my content” and “the exact prompts real people are typing into AI.”

For a solo SEO freelancer, the tools I’d look at are:

1. Profound — probably the closest match

Profound specifically has Prompt Volumes, which uses data from real AI conversations to show what people are actually asking ChatGPT, Gemini, Claude and Perplexity. www.tryprofound.com

The particularly interesting feature for your use case is that Profound says you can:

search a specific URL and see the prompts that cause AI engines to cite that page

It also distinguishes between real-user prompts and prompts that you manually track. www.tryprofound.com

So you could theoretically get something like:

Your client's page: /best-running-shoes/

AI prompts associated with citations:

• “What are the best running shoes for beginners?”
• “Best running shoes for flat feet?”
• “Which running shoes are good for marathon training?”
• etc.

That's much closer to what you're describing than traditional AEO rank tracking.

2. Peec AI — better if you want a simpler freelancer workflow

Peec AI lets you build a prompt library and track how brands appear across AI engines. It specifically reports which prompts generate mentions and which sources get cited. peec.ai

Its documentation also makes an important distinction: it's not trying to trace individual LLM API calls; it's an AI-search visibility platform for marketers. peec.ai

The catch

Nobody can really give you the exact private prompt that caused an individual ChatGPT user to discover/cite your page. Those conversations aren't exposed to third-party SEO tools.

What you can get is increasingly good aggregate data:

real user prompts → AI answer → cited sources → your URL

That's actually more useful for SEO than knowing that one person asked a particular question.

And this is becoming a serious SEO data category: Profound says its dataset contains 1.3B+ real user AI conversations, while its tracking product lets you connect prompts to citations and visibility. www.tryprofound.com

For a solo freelancer, I'd approach it this way

If your goal is to sell “AI visibility / GEO” as an add-on to SEO clients, I'd test Profound first and Peec second.

The killer report isn't simply:

“Your brand appeared in ChatGPT 18% of the time.”

It's:

“Here are the AI prompts your customers are actually asking. Here's where your site gets cited. Here are the prompts where competitors get cited instead. And here's the content/outreach opportunity.”

That's a much more compelling deliverable to a client.

If you tell me roughly how many clients you manage and what you're willing to spend/month, I can also compare the current freelancer/agency pricing and tell you which one makes the most economic sense.

If your goal is specifically to measure which sources AI assistants cite, how often they cite them, and how prominently those sources appear, I’d start with otterly.ai.

Why OtterlyAI

• Citation-level tracking: it records the URLs/domains cited in AI answers, not just whether your brand was mentioned. Otterly Otterly
• Source position: it tracks changes in link position, which is useful as a proxy for source prominence. Otterly
• Multiple AI engines: it monitors ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly
• Competitive benchmarking: you can see which competitors and third-party sources are getting cited instead of you. Otterly
• Longitudinal data: it runs your prompt set repeatedly, so you can see citation share and source changes over time rather than relying on one-off searches. Otterly

One caveat: if by "source prominence" you mean something more sophisticated than citation position—for example, a score combining citation frequency × position × number of AI engines × prominence within the answer × source authority—I'd look at Profound as well. Current comparisons put it toward the enterprise end of the market with deeper AI-search analytics. GeoHero Linkeddit

So my quick recommendation:

If you tell me whether you're tracking your own website, competitors, or the overall web/source ecosystem, I can narrow this to the best 2–3 tools and compare their actual citation metrics.

Yes. What you’re describing is usually called AI citation monitoring / AI search visibility monitoring: a tool repeatedly runs relevant prompts through AI assistants and records which URLs/domains they cite, when those citations change, and whether competitors are cited instead.

A few options worth looking at:

• OtterlyAI — probably the closest match. It tracks citations at the URL level, including your pages and competitor pages, across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. It also offers competitive benchmarking and alerts when visibility changes. otterly.ai
• Ahrefs Brand Radar — monitors AI mentions/citations and shows the specific domains and pages being cited. Particularly useful if you already use Ahrefs for SEO. ahrefs.com
• Foglift — explicitly tracks new cited URLs, competitor source sets, and changes over time, with daily monitoring and email digests. foglift.io
• Yogoo AI — more lightweight; tracks when AI cites you versus competitors and identifies the prompts where competitors win. yogoo.ai

One important distinction

If you mean:

“Alert me whenever an AI assistant starts citing any new page from our domain or a competitor's domain.”

rather than simply:

“Tell me whether our brand was mentioned,”

then URL-level citation tracking is the feature to look for. OtterlyAI and Foglift appear particularly aligned with that requirement. OtterlyAI specifically says it tracks every cited URL and which rival URL is cited instead. otterly.ai

A useful setup would be:

Your domains + 5–10 competitor domains → fixed prompt set → daily/weekly AI runs → detect new cited URLs → Slack/email alert

For example:

🚨 New AI citation detected
ChatGPT — “best enterprise analytics platforms”
New source: competitor.com/research/2026-benchmark
Previously unseen in last 30 days
Cited alongside: YourBrand, Competitor A

That lets you treat AI citations almost like new backlinks, but from the perspective of AI answer engines.

If you tell me how many domains/competitors you need to monitor and which assistants matter (ChatGPT, Perplexity, Gemini, Claude, Google AI, etc.), I can narrow this down to the 2–3 tools that best fit.

For a small ecommerce team, you’re looking for an AI visibility / GEO (generative engine optimization) monitoring tool rather than a traditional SEO rank tracker. The best fit depends on whether you mainly want product-page tracking, competitor share of voice, or actionable fixes. AI Visibility Software Nexscope

Here are some tools worth evaluating:

For a small ecommerce team, I’d generally shortlist:

1. Glint — if you want a lightweight “are we showing up in AI shopping answers?” dashboard. Glint
2. CartGPT — if you care about individual products/SKUs appearing in AI recommendations. CartGPT
3. Yotpo Discover — if you already have a mature ecommerce stack and want deeper commerce signals. Yotpo

The metrics I’d make sure any tool provides:

• AI share of voice: % of relevant buyer prompts where your brand/product appears vs competitors
• Product citation rate: how often AI assistants cite your product pages
• Prompt coverage: which shopping questions you win or lose
• Average placement: whether you’re mentioned first, middle, or as an alternative
• Competitor gaps: products that appear where yours do not
• Page-level recommendations: what product descriptions, reviews, schema, or content changes could improve visibility

A practical setup for a small team is to track 50–200 high-intent buyer prompts (for example, “best _ for ”, “ vs _”, “alternatives to ___”) weekly and monitor whether your product pages gain or lose AI visibility over time. AI shopping visibility is becoming a distinct channel alongside SEO and paid search. reuters.com

If you tell me your platform (Shopify, WooCommerce, Amazon, custom), catalog size, and budget range, I can narrow this to 2–3 options.

If your goal is specifically monitoring which agency-client blog articles get cited/linked inside generative answers, rather than just tracking whether the brand is mentioned, I’d shortlist these:

🥇 I'd start with OtterlyAI

For your use case, Otterly is particularly compelling because it explicitly tracks the actual URLs cited in AI answers, not merely brand mentions. Its analytics can show which pages get cited, whether competitors' pages are cited instead, citation positions, and trends over time. otterly.ai

It currently covers ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, Microsoft Copilot, and Claude, with country/language monitoring as well. help.otterly.aiotterly.aihelp.otterly.aiwww.tryprofound.com

That maps very closely to an agency workflow:

Client → target prompts → AI answers → cited URLs → client content attribution → competitor citations → content recommendations

It also has agency-specific functionality, including automated reporting, multiple brand reports, prompt monitoring, and citation tracking. otterly.ai

One particularly useful distinction: Otterly says it collects responses through the public AI interfaces rather than relying exclusively on APIs, because API responses can differ from what users actually see. help.otterly.ai

🥈 Profound if citation intelligence is the centerpiece

I'd look closely at Profound if you're building a more sophisticated GEO/AEO service rather than simply adding an AI-search report to your SEO retainer.

Profound's citation product lets you see which answer engines cite your content, how frequently, across which prompts, what kinds of sources are being cited, and which publishers/authors are driving citations. www.tryprofound.com

That's potentially more valuable for an agency because you can turn the data into a content/PR strategy:

"Google's AI answers cite these 12 publications in this category. Our client's blog is rarely cited. Here are the topics and source types we need to build."

Profound also emphasizes custom/real-world prompts and daily runs, rather than simply giving you a static visibility score. www.tryprofound.com

What I'd actually evaluate in a demo

Don't let vendors sell you on a generic "AI visibility score." For a content agency, I'd ask each vendor to demonstrate these five things:

1. URL-level attribution

Can I see that /blog/best-x was cited, rather than merely "Acme was mentioned"?

2. Prompt → answer → citation chain

Can I inspect the exact prompt, generated answer, cited sources and position of our client's URL?

3. Historical attribution

Can I show a client that Article A went from 0 citations → 14 citations over six months?

4. Competitive citation gaps

"Competitor X is cited on 38 prompts where our client's content isn't." This is much more actionable than a visibility score.

5. Agency reporting/API

Can I create separate client workspaces/reports and push the data into Looker Studio or your own reporting stack?

Otterly checks particularly well on #1–5; it offers reporting exports, an API/MCP layer, and a Looker Studio connector. otterly.ai

One important caveat

"Cited" is not necessarily the same thing as "influenced the answer."

An AI engine may cite a blog because it contains supporting information, while the underlying answer was influenced by many other sources. Conversely, a piece of content can influence an answer without receiving an explicit link.

So I'd measure at least four separate KPIs:

• Brand mentions
• Domain citations
• Individual URL citations
• Citation share vs. competitors

Then layer prompt coverage / share of voice on top.

For an agency, that gives you a much better client story than simply saying "your AI visibility score increased 17%."

My recommendation: demo Otterly + Profound + Scrunch with the same 50–100 client prompts and the same 10–20 competitors. Don't compare their marketing pages—compare how well each one answers "Which of our published articles did ChatGPT/Perplexity/Google actually cite, for which questions, and how did that change?"

If you tell me roughly how many clients, domains, and prompts you need to monitor per month, I can narrow this down to the best platform and likely pricing tier for an agency.

Yes. This is now a fairly established category usually called AI visibility tracking, GEO (Generative Engine Optimization) monitoring, or LLM visibility monitoring.

The important distinction is that these platforms generally don’t crawl every AI answer on the internet. Instead, they repeatedly run a defined set of customer-relevant prompts against multiple AI engines, capture the answers, and analyze whether your brand was mentioned, how it was described, and which sources/URLs were cited.

A few worth looking at:

• otterly.ai — probably one of the more mature options. It tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, including mentions, citations, sentiment, share of voice and the actual cited URLs. It also has an API. Otterly Otterly
• zumihq.com — particularly interesting if you want broad model coverage. It currently advertises up to nine engines, including ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, AI Overviews, AI Mode and DeepSeek, with citation ranking. Zumi
• getmint.ai — focuses on brand mentions, citations, sentiment and share of voice across ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews. GetMint
• frase.io — combines AI visibility monitoring with content/SEO tooling. It shows the actual answers behind the visibility metrics and which engines cite you versus competitors. Frase
• citations.io — more narrowly focused on citation intelligence. It tracks ChatGPT, Gemini, Perplexity and Claude and shows which URLs are being cited, including competitor sources. Citations
• mentionhq.com — tracks mentions and rankings across ChatGPT, Claude, Gemini, Perplexity, and on higher plans DeepSeek and Grok. Mention

If you're asking because you're considering building this

There is still an interesting gap.

Most of these products are essentially:

Prompt library → query models → capture answers → detect brand → extract citations → calculate visibility/SOV.

They don't necessarily give you a comprehensive picture of every organically occurring AI answer that mentions your brand. That's fundamentally difficult because private ChatGPT/Claude conversations aren't observable.

A potentially more differentiated product would therefore be something like:

"Google Alerts for AI answers."

Where you monitor a much larger universe of commercially relevant prompts and tell a brand:

• Where were we mentioned?
• What exactly did the model say about us?
• Which model said it?
• Which competitor appeared instead?
• What sources caused the model to mention us?
• Which third-party publications are repeatedly being cited?
• What changed since last week?
• Are we being recommended, merely mentioned, or explicitly cited?
• Are different models developing different opinions about us?

That last piece is particularly valuable. For example:

ChatGPT → recommends Brand A
Claude → recommends Brand B
Gemini → recommends Brand A
Perplexity → cites Brand C's review of Brand A

That's much more actionable than a generic "AI visibility = 63%" score.

If you're evaluating this as a competitive landscape / startup opportunity, I can also map out the existing players, their pricing, model coverage, APIs, and where I think the whitespace is.

"Google Alerts for AI answers."

Yes. For that specific use case, I’d look at Ahrefs first.

• Ahrefs — best overall fit. Its Brand Radar tracks AI citations and, importantly, distinguishes pages that were actually cited from pages that were merely found/retrieved by an AI system. You can see cited pages, the queries associated with them, and citation frequency across AI platforms. help.ahrefs.com
• Its Web Analytics can then show which of those AI-cited pages actually generate referral traffic and engagement, so you can connect “AI used our FAQ” to “this FAQ page drove visits.” ahrefs.com
• It also has Bot Analytics, which tells you which AI crawlers are visiting your site and which pages they're crawling. That's useful as a leading indicator, but it's not the same thing as measuring citations in answers. help.ahrefs.com

A very compelling free/low-friction alternative is Microsoft Clarity. Its new AI Visibility → Citation dashboard specifically reports page citations, citation counts, grounding queries, and “My cited pages,” plus AI referral traffic. That maps unusually well to your question about how frequently FAQ content is used and which pages drive answers. help.ahrefs.comlearn.microsoft.com

And if you primarily care about Copilot/Bing, Bing Webmaster Tools' AI Performance is worth adding: it provides page-level citation activity and maps grounding queries to the pages that were cited. www.bing.com

My recommendation

If you're trying to build an internal dashboard like:

FAQ page → times cited by AI → assistants → questions/topics → AI referral visits

I'd use Ahrefs + your existing analytics. If budget is a concern, start with Clarity + Bing Webmaster Tools.

One caveat: no tool can perfectly measure all AI usage. AI assistants can retrieve your page without citing it, and different products expose different amounts of their retrieval/citation data. Ahrefs explicitly separates “Found in” from actual citations, which is why I think it's particularly relevant to your question. help.ahrefs.com

If you tell me whether your FAQ is customer-support/product FAQ, documentation, or a large public knowledge base, I can narrow this down to the best 2–3 tools and compare their pricing, AI coverage, page-level reporting, and API/export capabilities.

If you mean a tool that can tell you when AI assistants quote or summarize your website, and pinpoint the exact source passages/URLs on your site, you’re looking for an AI visibility / answer engine optimization (AEO) monitoring tool or a citation tracking tool. There isn’t one universal tool that can see every AI assistant’s private outputs, but several can help:

• tryprofound.com — Tracks how brands appear in AI-generated answers, including citations and visibility across AI search experiences. Useful for identifying when your content is being referenced.
• otterly.ai — Monitors AI search results and citations, helping identify where your pages appear in AI answers.
• peec.ai — Tracks brand visibility in AI answer engines and can show cited sources.
• scrunch.com — Focuses on AI search visibility and how content is represented in AI-generated answers.
• ahrefs.com / semrush.com — Traditional SEO tools that can help find which pages are authoritative and likely being surfaced, though they do not directly reveal all AI quotes.

If you specifically need “AI assistant said this exact sentence — find the paragraph on my site it came from”, the workflow is usually:

1. Collect AI outputs (from ChatGPT, Gemini, Perplexity, Claude, etc.) using monitoring queries.
2. Extract quoted text or passages.
3. Run similarity matching against your site content using: - a crawler + vector database (e.g., embeddings with OpenAI, Pinecone, Weaviate, Elasticsearch)
4. plagiarism-style matching tools
5. custom scripts using semantic search.

For Perplexity-style citation tracking, tools like Profound, Otterly, and Peec are closer. For exact passage attribution at scale, you usually need a custom pipeline.

If you tell me which AI assistants you care about (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.) and whether you need monitoring or forensic matching of quotes, I can narrow down the best option.

A good solution is to treat this as AI visibility intelligence by geography—similar to SEO rank tracking, but for AI assistants. You want a system that repeatedly asks AI assistants the same business questions from different locations, captures the answers, and compares how your brand is represented. Geographic variation is a known issue in AI visibility: different markets can surface different competitors, sources, and descriptions. knowatoa.com

Recommended approach: build an AI Geographic Presence Monitoring System

1. Create a regional prompt library

Define the questions customers actually ask AI assistants, segmented by market.

Examples:

Track:

• Brand mentions
• Position/ranking in recommendations
• Competitors mentioned
• Descriptions used
• Claims made about your business
• Sources cited by the assistant

2. Run the same prompts across AI platforms

Monitor:

• ChatGPT
• Gemini
• Claude
• Perplexity
• AI search experiences

Do not combine them into one score initially. Each assistant can behave differently, and preserving the provider, prompt, location, and cited sources makes diagnosis easier. www.cheers.tech

3. Add location simulation

Your testing framework should vary:

• Country
• State/province
• City
• Language
• User intent
• Customer persona

Example matrix:

Location:
  US → Colorado → Denver

Assistant:
  ChatGPT

Prompt:
  "Best accounting firms for startups"

Captured:
  - Mentioned? Yes/No
  - Rank position
  - Competitors
  - Citations
  - Sentiment
  - Accuracy

4. Store results in a dashboard

Useful metrics:

Visibility

• % of prompts where your business appears
• Average recommendation position
• Share of voice vs competitors

Consistency

• Does the assistant describe your services correctly?
• Are locations accurate?
• Are outdated details appearing?

Regional gaps

• Markets where competitors appear but you do not
• Cities where incorrect information appears
• Regions with weak citations

5. Connect findings to fixes

The system should produce actions such as:

• “AI does not mention your Phoenix location”

→ improve Phoenix location pages, directories, reviews, local coverage

• “AI describes your pricing incorrectly”

→ update authoritative web sources

• “Competitor dominates Midwest recommendations”

→ analyze cited sources and local authority signals

Tools worth evaluating

There is a growing category of AI visibility/GEO monitoring tools designed for this. Some support geographic segmentation, multi-model tracking, competitor comparisons, and citation analysis. www.aeosim.com Examples include platforms such as Profound, Otterly.AI, and location-focused trackers such as Knowatoa. knowatoa.compages.trustablelabs.com

My recommended architecture for a mid-size company

Data collection

• Automated prompt runner
• Regional proxy/location capability
• AI response capture

↓

Analysis layer

• Brand extraction
• Competitor detection
• Citation/source analysis
• Accuracy scoring

↓

Dashboard

• Regional heat map
• AI assistant comparison
• Monthly trend reports

↓

Operations

• Marketing tickets
• Local SEO/content fixes
• Reputation management tasks

Minimum viable version

If you want to start quickly:

1. Pick 50–100 customer prompts.
2. Test 10–20 priority markets.
3. Run weekly.
4. Store raw AI answers.
5. Score:
   • mentioned/not mentioned
   • correct/incorrect information
   • competitor wins
   • citation sources

This will reveal whether your problem is AI discoverability, regional content gaps, incorrect business data, or local competitive weakness.

Yes. The category you’re looking for is AI search visibility / GEO (Generative Engine Optimization) tracking.

Best fits

• tryprofound.com — probably the strongest fit if your key requirement is “alert me when my brand starts or stops appearing.” It runs tracked prompts daily, measures visibility/share of voice, and its automation system can trigger alerts when visibility drops below a threshold. Profound Knowledge Base Profound
• peec.ai — excellent for tracking how often your brand is mentioned in ChatGPT, position, sentiment, competitors, and the sources ChatGPT cites. It updates visibility metrics daily. Peec AI Peec AI

What I'd choose

If your requirement is specifically:

“Tell me when ChatGPT stops recommending/mentioning my brand for important prompts.”

I'd start with Profound, because it explicitly supports visibility monitoring and threshold-based alerts. Profound Knowledge Base

If you want a more marketing-oriented dashboard for ChatGPT + Gemini + Perplexity + Google AI, I'd also evaluate Peec AI. Peec AI

One important distinction: these tools don't continuously watch every possible ChatGPT conversation. They monitor a defined set of prompts/topics and measure whether/how your brand appears in the resulting AI answers. Profound, for example, runs tracked prompts daily. Profound Knowledge Base Profound

If you tell me your brand + industry, I can compare the best 3–5 tools specifically for alerts, ChatGPT coverage, pricing, and whether they test the real ChatGPT frontend versus an API.

Yes. Semrush is probably the closest match to exactly what you're describing.

Best fit: Semrush

Semrush now has an “AI vs SEO Comparison” capability that explicitly compares your traditional organic-search performance with your visibility in AI-generated answers. It can put things like:

• Google organic rankings for your keywords
• ChatGPT / Gemini / Google AI Mode / AI Overviews visibility
• Whether your brand is mentioned or cited
• Your citation position in AI answers
• Competitor visibility
• The prompts where you rank well organically but don't appear in AI answers, and vice versa

Semrush describes its AI-vs-SEO reporting as specifically designed to compare a domain's performance in LLMs against traditional search rankings. Semrush

semrush.com

There's also a free AI Visibility Checker if you just want to experiment with the concept. Semrush

Other tools worth looking at

• GazeSEO — particularly interesting if you want a straightforward dashboard showing Google rankings alongside ChatGPT, Gemini, Perplexity, and Claude visibility. Gazeseo
• RankVisibly — lets you enter keywords and see your Google position alongside whether you're visible in ChatGPT, AI Overviews, AI Mode, etc. RankVisibly
• Rank.ai — focuses more heavily on tracking specific buyer prompts and whether ChatGPT/other AI engines recommend or cite you. Rank.ai
• Citations.io — useful if your main concern is which AI answers cite you and your competitors. Citations.io

The important distinction

I wouldn't think of AI rankings as literally equivalent to Google rankings.

For example:

“Best project-management software for startups”
Google: You rank #4
ChatGPT: You are mentioned #2 of 7 recommendations
Perplexity: You're not mentioned
Google AI Overview: Your site is cited

That's more useful than trying to force everything into a single “AI rank.” Semrush itself uses metrics such as mentions, citations, visibility, and average citation position rather than treating an AI answer as a conventional SERP. Semrush

If your goal is specifically: “Show me, for the same set of keywords, where I rank on Google vs. where I appear in ChatGPT/Perplexity/Gemini”, I can also compare the current tools and tell you which one has the best side-by-side workflow, pricing, and API/export capabilities.

If you mean AI/LLM share of voice—how often your brand appears for a defined set of prompts/keywords compared with competitors—I’d shortlist these:

My pick

If your requirement is specifically “give me an AI share-of-voice number for these 100/1,000 keywords and brand terms,” I'd start with DemandSphere or Peec.

There's an important distinction, though: a good platform shouldn't simply search for your brand name. It should let you define a prompt universe such as:

• best CRM for startups
• Salesforce alternatives
• CRM for real estate
• HubSpot vs Salesforce
• best [category] software
• branded queries such as HubSpot pricing, HubSpot competitors

…and then repeatedly query the AI engines, recording mention rate, position/rank, citation rate, and competitor mentions. That's the more defensible definition of AI SOV. www.influencers-time.com

If you tell me your industry + roughly how many keywords you want to track + whether you care about ChatGPT only or ChatGPT/Gemini/Perplexity/Claude, I can narrow this to the best 2–3 tools and compare their current pricing and exact keyword/SOV capabilities.

Yes. The category is usually called AI visibility tracking, LLM visibility monitoring, Generative Engine Optimization (GEO), or Answer Engine Optimization (AEO). These tools measure how often a brand appears in answers from different AI models and can break results down by model, prompt, competitors, sentiment, and citations. Ahrefs Riff Analytics

Some tools that do this:

• ahrefs.com — Tracks brand mentions across ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews, with breakdowns such as mentions by platform, topics, and cited domains. Ahrefs
• mentionhq.com — Provides cross-model visibility dashboards, including model-level visibility scores and mention trends across platforms like ChatGPT, Claude, Gemini, and Perplexity. Mention
• elmohq.com — Focuses on tracking brand mentions across many AI models, including ChatGPT, Claude, Gemini, Grok, Mistral, Perplexity, Copilot, and DeepSeek, with share-of-voice and trend views. Elmo
• rankr.so — Shows per-model visibility, mentions, and sentiment comparisons across models such as ChatGPT, Claude, Gemini, and Perplexity. Rankr
• riffanalytics.ai — Offers dashboards comparing how different AI models mention and rank brands across prompts. Riff Analytics

A typical dashboard looks something like:

One caveat: true model-version attribution can be difficult. Many commercial tools track the AI product surface (e.g., ChatGPT, Claude, Gemini) rather than every underlying model version, because providers frequently change routing and model availability. If you specifically need “brand appearances by GPT-4.1 vs GPT-5 vs Claude Sonnet vs Gemini Pro,” look for tools that let you choose the exact API model or bring your own API keys, such as open-source trackers. Elmo

If you mean enterprise-grade monitoring for a marketing/SEO team, a dashboard of share-of-model across hundreds of prompts, or tracking your brand inside ChatGPT specifically, the best-fit tools differ.

If your goal is specifically “find every negative or inaccurate thing AI assistants are saying about our brand, understand why it happened, and alert the right team”, I’d shortlist the market this way:

My recommendation

For a serious brand-reputation program, I'd start with Profound. Its Answer Engine Insights specifically queries AI answer engines and analyzes visibility, citations, sentiment, share of voice, and positioning, with prompts run daily. help.tryprofound.com

That's more useful for your use case than simply counting mentions: you want to know what the AI actually said, whether the claim is negative or wrong, which sources it relied on, and whether the problem is occurring consistently.

Profound

If you want to get started quickly and cheaply, I'd choose OtterlyAI. It monitors ChatGPT, Perplexity, Gemini, Claude, Copilot and Google's AI surfaces, and its analytics include the actual answer, sentiment, citations, ranking and competitor comparisons. It says monitoring is performed daily. otterly.ai

OtterlyAI

One important distinction

There are actually two different problems:

1. Monitoring: “What are AI systems saying about us?”
2. Remediation: “How do we get AI systems to stop saying something inaccurate?”

Most products are substantially better at #1 than #2. An inaccurate answer might originate from your website, Wikipedia, reviews, news coverage, an outdated database, or another third-party source. Simply asking ChatGPT to “correct” itself isn't a scalable reputation-management strategy.

So I'd evaluate vendors on whether they give you:

• Prompt-level answer capture, not just a visibility score
• Negative/positive sentiment
• Claim extraction so you can identify specific false statements
• The sources/citations behind each claim
• Historical tracking so you can prove when the problem started
• Alerts when a previously positive answer becomes negative
• Competitor comparison
• Coverage across ChatGPT, Gemini, Perplexity, Claude, Copilot, Google AI surfaces, etc.
• API/Slack/webhook capabilities for routing serious issues
• A way to distinguish “not mentioned” from “mentioned negatively”
• Ideally, recommendations for what source/content needs to change

Otterly, for example, explicitly exposes the cited URLs and the context in which brands are mentioned, while also scoring sentiment. help.tryprofound.comotterly.ai

If this is for a large brand

I'd do a Profound vs. Otterly proof-of-concept rather than buying based on demos. Give both vendors the same ~100–300 prompts, including:

• “[Brand] reviews”
• “Is [Brand] trustworthy?”
• “Problems with [Brand]”
• “[Brand] alternatives”
• “Why shouldn't I use [Brand]?”
• “[Brand] pricing”
• “[Brand] vs competitor”
• “[Brand] complaints”
• “[Brand] recalls/security issues/legal issues” — where applicable
• Category questions where your brand should appear but doesn't

Then manually label the answers as accurate-positive / accurate-neutral / accurate-negative / inaccurate-positive / inaccurate-neutral / inaccurate-negative.

The winner isn't necessarily the platform with the highest “AI visibility score.” It's the one that most reliably finds the bad claims you actually care about and gives your team enough evidence to fix them.

Bottom line:

• Enterprise / brand reputation: Profound
• Best value / quick deployment: OtterlyAI
• Mid-market alternative: Peec AI
• Already deeply invested in SEO tooling: consider Semrush/Ahrefs
• If “fixing inaccurate AI answers” is as important as monitoring them: I'd evaluate a monitoring platform plus a remediation/content workflow rather than treating this as ordinary social listening.

If you tell me your company size, industry, number of brands/products, and which AI platforms matter most, I can narrow this to the 2–3 best options and compare pricing, alerting, API access, accuracy detection, and enterprise features.

Yes — what you’re looking for is usually called AI visibility monitoring, AI search monitoring, or GEO/AEO tracking. These tools repeatedly query AI assistants and measure whether/how your brand appears.

My top picks

1. OtterlyAI — best all-around monitoring
   • Tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude.
   • Measures brand mentions, sentiment, share of voice, ranking/position, competitors, and the URLs AI cites.
   • Runs your chosen prompts automatically and monitors them over time.
   • Has an API if you want to feed the data into your own dashboards. otterly.ai
   • Pricing currently starts at $29/month, with a free trial. otterly.aiotterly.aiwww.tryprofound.com

2. Profound — best for larger marketing/enterprise teams
   • Tracks how AI talks about your brand, including visibility, citations, sentiment, share of voice and positioning.
   • Particularly interesting if you want to understand why AI mentions you and which sources are influencing those answers. www.tryprofound.com
   • Its Profound Index also lets you benchmark brands against competitors using large-scale real-user AI conversations. www.tryprofound.com

3. Ahrefs AI Visibility Checker — easiest way to test the concept
   • Free checker for seeing how your brand appears in ChatGPT, Gemini, Perplexity, Copilot and Google AI Overviews.
   • Good for a quick baseline before paying for continuous monitoring. ahrefs.com

What I'd choose

If your goal is specifically:

“Tell me whenever/how often ChatGPT, Gemini, Perplexity, etc. mention my brand, what they say about it, and how that compares with competitors.”

I'd start with OtterlyAI. Its monitoring is particularly close to that exact use case: you create a library of questions your customers might ask, and it tracks brand coverage, mentions, sentiment, citations and competitors across AI engines daily. help.otterly.ai

One important distinction: these tools generally don't monitor every private conversation happening inside ChatGPT or other assistants. They monitor AI-generated answers by running representative prompts and/or analyzing available AI-search data. So think of it as “How visible is my brand in AI answers?”, rather than a Google Alerts-style feed of every private chatbot conversation.

If you tell me your brand + industry + whether you're B2B or B2C, I can also compare Otterly vs Profound vs Peec vs other tools specifically for your use case and recommend the cheapest one that gives you the data you actually need.

Yes. The category you want is usually called AI visibility tracking, AI search monitoring, or AEO/GEO tracking. The key distinction is that you don't just want a tool that says “ChatGPT mentioned my company.” You want it to show which answer, which prompt, which competitor, and—most importantly—which websites/pages the AI cited as sources.

My picks

1. peec.ai — best overall

This is probably where I'd start.

Peec tracks your brand across ChatGPT, Gemini, Perplexity and other AI surfaces, while showing visibility, position, sentiment, share of voice, competitors, and the sources being cited. Its particularly useful distinction is between brand visibility (AI mentions you) and source visibility (AI actually cites your website/content). Peec AI Peec.ai Docs

That distinction is exactly what you're asking about.

For example, you could discover:

“ChatGPT recommends Acme 42% of the time, but only 8% of those answers cite Acme's own website. Instead, it gets its information from G2, Reddit, Forbes, and industry publications.”

That's much more actionable than a simple mention counter.

2. otterly.ai — best value

Otterly is worth looking at if you don't need an enterprise platform.

It tracks prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and records mentions, rankings, sentiment, share of voice and the URLs cited by the engines. Otterly

It's a particularly good choice if your goal is:

• Track 20–100 important questions people ask about your category
• See whether your company appears
• See who beats you
• See what sources AI is using
• Monitor changes over time

3. tryprofound.com — best for enterprise

Profound is the one I'd investigate if this is becoming a serious marketing/brand-intelligence function rather than a side project.

It is positioned around enterprise AI-search analytics and deeper citation/source intelligence, rather than simply being an “SEO rank tracker for ChatGPT.” Current comparisons put it toward the enterprise end of the market. SEO Counselors AEO Labs

The metric I'd pay the most attention to

Don't make “number of AI mentions” your primary KPI.

I'd build a dashboard around:

1. Mention rate — % of relevant prompts where your company appears.
2. Recommendation/rank — where you appear when you're mentioned.
3. Share of voice — your visibility versus competitors.
4. Citation rate — % of answers that cite your site/content.
5. Citation share — what percentage of all cited sources in your category are yours.
6. Third-party source distribution — Reddit, G2, Wikipedia, news, review sites, competitors, publishers, etc.
7. Citation pages — the specific URLs AI is relying on.
8. Prompt-level history — whether a particular answer changed after you published/updated something.

That last part is especially valuable. Peec, for example, explicitly surfaces the sources AI platforms reference and lets you drill down into individual tracked prompts and recent AI responses. Peec.ai Docs

One important caveat

AI citations are volatile. A recent analysis found that Reddit's share of ChatGPT citations changed substantially over just a few weeks, illustrating why you want longitudinal tracking rather than manually checking ChatGPT once in a while. Axios

So if your real question is:

“When someone asks an AI assistant about my company/category, what does it say, and what evidence is it using?”

I'd shortlist Peec → Otterly → Profound, in that order for most companies.

If you tell me your company type (B2B SaaS, ecommerce, agency, local business, etc.) and roughly how many prompts/competitors you want to track, I can narrow this to the best 2–3 and compare current pricing, engines, citation-level reporting, API/export options, and whether they track ChatGPT/Claude/Perplexity/Gemini separately.

Yes. This category is generally called AI visibility / AI search visibility / GEO tracking, and there are now platforms that specifically measure which AI answers mention or cite your content, how often, and which URLs are being surfaced.

A few worth looking at:

• ahrefs.com — Tracks ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews. It can show mentions, the topics triggering them, and which domains and specific pages are being cited. This is probably the most natural choice if you already use Ahrefs. Ahrefs
• citations.io — More specifically focused on citation intelligence. It has a Citation Map showing every URL/domain cited, an answer archive with timestamped AI responses, and competitive share-of-voice. It tracks ChatGPT, Gemini, Perplexity, and Claude. Citations.io
• zumihq.com — Particularly interesting if you care about the content level. It tracks exact cited pages, citation share, domains, and which pages AI engines are pulling from, across up to nine engines. Zumi
• getmint.ai — Tracks mentions, citations, sentiment, and share of voice across ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews, with filters for competitor, market, language, and intent. GetMint
• trysight.ai — Goes deeper into individual model/prompt tracking, showing where your brand appears in answers and the specific pages being cited. Sight AI

The important distinction

What you're describing is slightly more sophisticated than simply asking "Does ChatGPT mention my brand?"

Ideally, you want to measure:

Your content → AI prompt → AI answer → citation → exact URL → frequency over time

For example:

User asks: "What are the best attribution platforms for B2B SaaS?"

ChatGPT answer cites 8 sources
→ Your site is cited in 3/100 runs
→ /guides/b2b-attribution accounts for 80% of your citations
→ Competitor X is cited in 27/100
→ Your citation rate increased from 2% → 7% after publishing a particular article.

That's the emerging AI citation analytics layer. Some platforms explicitly preserve the underlying answer so you can see where the citation actually occurred, rather than giving you an opaque "AI visibility score." Citations.io, for example, says its answer archive contains verbatim, timestamped AI answers and its citation map records the URLs cited. Citations.io

One caveat: "how often AI models cite our content" isn't the same thing as how often real users see your content cited. These platforms generally run controlled sets of prompts against the AI engines and extrapolate visibility from those observations. Results can vary with prompt wording, model, geography, personalization, and time. The volatility is real—recent analysis, for example, found substantial changes in which sources ChatGPT cited over just a few weeks. Axios

If you're evaluating this for your own company's content, I can also compare the leading platforms specifically on exact URL-level citation tracking, historical data, ChatGPT coverage, API access, and pricing and tell you which one I'd pick.

Yes. For a small agency on a limited budget, I’d avoid the enterprise-heavy platforms and start with Otterly.ai or Peec AI.

\*Pricing changes frequently, so treat these as current ballpark figures rather than quotes. www.aeolabs.ai

What I'd do in your position

Start with Otterly if you're trying to prove that "AI visibility monitoring" is something clients will actually pay for. Its entry tier is around $29/month for 15 prompts, with monitoring across several major AI surfaces. That's enough to build a simple report around:

• "How often does ChatGPT mention you?"
• "Which competitors get recommended instead?"
• "What sources does AI cite?"
• "What's your average position?"
• "Is AI sentiment toward the brand positive/negative?"
• "Are your mentions improving month over month?"

That makes it possible to sell an AI-visibility add-on without putting another $300–500/month software expense on your agency. www.aeolabs.ai

Move to Peec once you have several clients and need more serious benchmarking and citation analysis. Current comparisons put its entry pricing around $85–95/month, and it is particularly well suited to agencies that want to compare brands, competitors, prompts and cited sources. www.aeolabs.ai

One important distinction

Don't just buy a tool that tells you "your brand was mentioned 37% of the time."

For client work, I'd prioritize one that lets you see:

Prompt → AI answer → competitors mentioned → your position → cited sources → change over time

The cited sources are particularly valuable because that's where you can turn monitoring into an actual service: "AI keeps recommending this competitor because these 14 sites/pages are influencing the answers; here's what we're going to do about it." www.aeolabs.ai

My recommendation

If you're under $50/month: Otterly.

If you can spend ~$100/month and have multiple clients: Peec.

If you're eventually building a dedicated AI-visibility/AEO service: I'd reassess the agency-focused platforms once you have enough recurring revenue to justify them.

If you tell me roughly how many clients you want to monitor (e.g. 5, 20, or 50) and whether you mainly care about ChatGPT, Gemini, Perplexity, or all of them, I can narrow it down to the cheapest setup that will actually scale.

For a startup founder, I’d think about this less as “reputation monitoring” and more as AI reputation intelligence: What do ChatGPT, Gemini, Claude, and Perplexity tell potential customers about us, and would we know if it changed? A lot of traditional reputation tools (Brandwatch, Mention, Meltwater, etc.) focus on social/news and won’t see the actual AI answers your buyers are reading. answerlift.io

My shortlist:

For a startup founder, I’d usually prioritize these capabilities:

1. Prompt monitoring
   • Track questions your buyers actually ask:
     • “Best [category] software?”
     • “Alternatives to [competitor]?”
     • “Is [your company] legitimate?”
     • “Who are the top vendors for [use case]?”

2. Answer snapshots
   • You want the actual AI response, not just a score.
   • Reputation problems often come from a single bad claim:
     • wrong pricing
     • outdated product info
     • competitor comparison errors
     • false claims about funding, customers, security, etc.

3. Citation/source tracking
   • AI answers often depend on third-party sources. Knowing whether the model is pulling from your docs, reviews, Reddit, news, or competitors helps you decide what to fix. citations.io

4. Slack/email alerts
   • A founder doesn’t want another dashboard. You want:
     • “ChatGPT stopped recommending us for our category”
     • “Competitor X replaced us in 8 tracked prompts”
     • “AI is stating an incorrect feature claim”

My practical recommendation by stage:

• Pre-seed / seed: start with a lightweight tracker (Peec AI, MentionFlow, or similar) + a manual spreadsheet of 20–50 critical prompts. mentionflow.aibigsentiment.com
• Series A/B: add competitor benchmarking and citation analysis (Profound, Semrush AI tools, Sophyx). www.techradar.comwww.sophyx.io
• Enterprise / regulated markets: combine AI monitoring with traditional PR, review monitoring, and customer feedback systems.

One thing I would not do: rely only on asking ChatGPT “what do you think of my company?” occasionally. AI outputs vary, and you need historical tracking to spot drift.

If you tell me your startup category (B2B SaaS, consumer app, fintech, healthcare, etc.) and stage, I can narrow this to the 2–3 tools I’d actually pay for.

Yes. There’s a growing category of tools usually called AI citation monitoring, AI visibility, GEO/AEO monitoring, or LLM visibility.

If your specific question is “When an AI assistant cites our product page, is what it says actually supported by that page?”, a few tools look particularly relevant:

• Citera — probably the closest match. It says it queries ChatGPT, Claude, Gemini, Perplexity, and DeepSeek, then checks AI answers against your actual page content and flags inaccurate claims/hallucinations. citera.dev
• FactSentry — specifically tracks inaccuracies AI engines repeat about your product, alongside citations and competitor mentions. factsentry.ai
• CitationWorks — tracks citations plus accuracy issues, sentiment, competitor mentions, and citation position. www.citationworks.com
• CitePulse — explicitly says it checks whether AI cites your company and whether what it says is accurate or false/out-of-date. citepulse.ai
• Profound — more enterprise-oriented; strong on tracking which specific sources/pages AI pulls from, citation frequency, competitors, and source authority, though it appears more focused on citation intelligence than page-level factual verification. www.tryprofound.com

The distinction I'd pay attention to

There are really two different products being marketed under “AI citation monitoring”:

1. Citation visibility:

“Does ChatGPT cite our product page?”

2. Citation accuracy:

“When ChatGPT cites our product page, does its claim actually match what the page says?”

For a company with lots of product/feature pages, #2 is much more interesting. You'd ideally want something that produces records like:

AI claim: “Product X supports SSO and SCIM.”
Cited URL: /products/x
Source evidence: page says SSO, but does not mention SCIM.
Assessment: Partially supported / inaccurate.
Model: ChatGPT
Prompt: “Which products support SCIM?”
Date: Aug. 24, 2026

That lets your content/product-marketing team identify dangerous misinformation originating from otherwise legitimate citations, rather than merely measuring whether you're getting cited.

If that's what you're looking to build/buy, Citera, FactSentry, and CitePulse are the ones I'd investigate first.

For an ecommerce store, you usually want AI visibility monitoring (sometimes called GEO/AEO monitoring) rather than traditional SEO rank tracking. The key is not just “does ChatGPT mention my brand?” but:

• Which SKUs get recommended
• For which shopper prompts
• On which AI assistants
• Above or below which competitors
• Whether the AI cites your product page or a reseller
• Whether recommendations lead to revenue www.notice.cx

A good stack looks like this:

Tools worth evaluating:

• Shop Mentions — Shopify-focused tracking that monitors product mentions across AI assistants and competitor comparisons. shopmentions.com
• Profound — enterprise-oriented AI visibility monitoring for brand mentions, prompts, and competitive visibility. www.notice.cx
• Peec AI — mid-market AI visibility tracking. www.notice.cx
• Otterly.ai — lighter-weight monitoring for AI mentions and visibility. www.notice.cx

For a serious ecommerce program, I would set up a SKU monitoring matrix:

1. Export your top 100–500 SKUs.
2. Create buyer prompts:
   • “best [category] under $100”
   • “compare [product type] for [use case]”
   • “alternative to [competitor product]”
   • “best gift for [audience]”
3. Run those prompts weekly across:
   • ChatGPT
   • Gemini
   • Claude
   • Perplexity
   • AI shopping/search surfaces where relevant
4. Track:
   • SKU mentioned? (yes/no)
   • Position in recommendation list
   • Competitors appearing
   • Citation URL
   • Sentiment
   • Price accuracy
   • Inventory accuracy

The biggest mistake ecommerce brands make is measuring brand mentions only. A brand can be “visible” while the AI recommends a retailer, marketplace listing, or competitor SKU instead. SKU-level tracking and attribution are much more actionable. www.notice.cx

If you’re on Shopify, WooCommerce, Amazon, or a custom storefront, the ideal tool choice changes quite a bit.

If your specific requirement is “show me the AI answers where we’re missing, then tell me which page/content problem on our site is causing that gap,” I’d start with OtterlyAI.

Why it fits:

• Answer → citation → URL: it stores AI answers, identifies which sites/pages were cited, and shows where competitors are cited instead. otterly.ai
• Content diagnosis: its Content Audit evaluates individual pages and gives specific improvements, including crawlability and AI-readiness factors. otterly.ai
• Gap prioritization: its Gap Analyzer surfaces prompts where competitors appear but you don't, helping turn AI visibility data into an optimization backlog. otterly.ai
• Broad AI coverage: it currently tracks ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot and Claude. otterly.ai
• It is relatively easy to pilot; its site currently advertises a free trial and pricing starting at $29/month. otterly.ai

One caveat

I wouldn't interpret this as a perfect causal system that can say “ChatGPT didn't cite you because paragraph 4 on /pricing is wrong.” The current generation of tools generally infers the content gap from the answer/citation patterns and site audit rather than proving causality. Independent comparisons also note that many AI-visibility platforms stop at measurement/recommendations rather than automatically implementing the fix. arbling.com

If you're an enterprise SEO team

I'd also put Profound on the shortlist. It is positioned more as an enterprise answer-engine optimization platform, with deeper monitoring, prioritization and content workflows. arbling.com

My pick: OtterlyAI if the desired workflow is “AI answer → competitor citation → our missing/weak page → concrete content fix.” Profound if you need a broader enterprise AEO/AI-search intelligence layer.

If you tell me your CMS (WordPress, Webflow, Shopify, etc.) and approximate number of pages, I can narrow this to 2–3 platforms that actually fit your workflow.

If you mean tracking when ChatGPT, Claude, Gemini, Perplexity, etc. start mentioning your brand more often and alerting your team, you’re looking for an AI visibility / LLM brand monitoring platform rather than a traditional social listening tool. These are the strongest options I’d evaluate:

Best overall AI mention monitoring platforms

Good options by use case

Enterprise PR / reputation monitoring

Look at:

• Profound
• Nightwatch
• Gumshoe

You’ll want:

• daily or hourly monitoring
• sentiment classification
• competitor comparisons
• exact prompts that triggered mentions
• historical charts
• Slack/email/webhook alerts

SEO / GEO (generative engine optimization) teams

Look at:

• Nightwatch
• Sophyx
• Lumidian

These focus more on:

• “Why are competitors appearing instead of us?”
• “Which pages/sources are AI systems citing?”
• “Which prompts should we optimize for?” Lumidian

DIY / engineering-friendly

Lettertrace is worth considering if you have technical resources. It is designed around tracking prompts against AI models, producing time-series visibility metrics, sentiment, and share-of-voice data. Lettertrace

Features I would require before buying

A good system should provide:

• Prompt library: Track the questions customers actually ask (“best CRM for startups,” “alternatives to X,” etc.)
• Mention rate over time: e.g., “Brand appeared in 42% of tracked answers this month vs. 31% last month”
• Spike alerts: Notify when mentions jump or disappear
• Competitor share of voice: “You appeared in 38% of answers; competitor A appeared in 55%”
• Context capture: Store the full AI response, not just “mentioned/not mentioned”
• Model segmentation: Separate ChatGPT vs Claude vs Gemini behavior
• Citation tracking: Which websites/content sources are influencing AI answers

My shortlist

For most marketing teams:

1. Profound — enterprise-grade visibility program
2. Gumshoe — strongest brand/competitive analytics angle
3. Nightwatch — best if SEO is already central
4. Sophyx — good dedicated AI mention monitoring
5. Lettertrace — best for technical teams wanting more control

One important caveat: these tools generally estimate AI visibility by repeatedly querying models with tracked prompts; they do not have access to private user conversations with ChatGPT or other assistants. The useful signal is how often your brand appears in controlled, repeatable AI-answer tests over time. Lettertrace Nightwatch

If you share your company size (startup, mid-market, enterprise), budget range, and whether you care more about PR reputation, SEO/GEO, or competitive intelligence, I can narrow this to 2–3 options.

If your goal is specifically “I changed content on my site—did that change our AI share of voice?”, I’d shortlist these:

What I'd pick

Peec is probably the closest match to what you described. Its metrics explicitly include share of voice vs. competitors, and it updates them daily by AI engine. peec.ai

The important thing, though, is how you run the experiment. Don't just look at “AI visibility went from 18% → 24%.” Set up:

1. A fixed prompt set — e.g. 50–200 questions your buyers actually ask.
2. Baseline period — ideally 2–4 weeks before the content change.
3. Content-change date — record exactly which URLs/content changed.
4. Post-change tracking — continue running the same prompts.
5. Compare share of voice, mention rate, position, citations and competitor share before vs. after.
6. Segment results by URL/topic/prompt cluster and AI engine so you can tell which content change actually moved visibility.

That's important because AI answers can fluctuate substantially; a before/after measurement based on a handful of prompts can easily mistake normal variation for an SEO/GEO effect. The same prompts tracked repeatedly are much more informative. www.leanlabs.com

My ranking for your exact use case: Peec → Profound → Otterly → Scrunch.

If you tell me your monthly budget, approximate number of prompts, and whether you're B2B/B2C, I can narrow this to the best 2–3 and compare their change-detection / before-vs-after capabilities specifically.

If your core requirement is AI share of voice (SOV) by geographic market × language × prompt set, I’d narrow the field to Profound, Peec AI, and Otterly.ai, with Profound the strongest choice for a large multinational.

My ranking

1. Profound — best overall for global enterprises

This would be my first demo if you're trying to answer questions such as:

“What percentage of AI answers recommend us in Germany vs. France vs. the US, and how does that change when the prompt is asked in German vs. English?”

Profound is positioned toward enterprise-scale AI visibility, with broad engine coverage, competitive SOV, citation/source analysis, and deeper analytics. Current comparisons put it at the top end of the market for enterprise analytics. Ayzeo AnswerManiac

Why I'd choose it: if you have dozens of markets, thousands of prompts, multiple competitors, and need historical reporting, this is the category's strongest enterprise option.

Potential downside: expensive and more sales-led than the self-serve alternatives.

2. Peec AI — probably the best value for a global marketing team

Peec is particularly interesting if SOV is the KPI you care about most rather than building a huge enterprise intelligence stack. Independent comparisons specifically highlight its competitive share-of-voice capabilities and multi-country tracking. Ayzeo GEO Agency

I'd shortlist it if you're managing, say:

• 10–30 countries
• multiple languages
• 50–500 strategic prompts per market
• 5–20 competitors
• regular market-by-market SOV reporting

It is considerably easier to justify than an enterprise Profound deployment if you're a marketing team rather than a huge global organization.

3. Otterly.ai — best inexpensive starting point

Otterly is compelling if you want to prove the business case before spending heavily. It tracks mentions, citations, competitors and SOV across major AI surfaces, but its analytics are shallower than Profound. licheo.com Omid Saffari

I'd use it for a pilot rather than a sophisticated global measurement program.

4. Scrunch AI

Worth including in an enterprise RFP, particularly if you want the platform to go beyond measurement into diagnosing and improving AI visibility. Current comparisons put it in the higher-priced enterprise tier. Ayzeo Stork.AI

The feature I'd scrutinize most

Don't just ask vendors whether they support “countries” and “languages.” There are three different dimensions you want them to demonstrate:

Market: US / UK / Germany / France / Japan, etc.

Prompt language: English / German / French / Japanese, etc.

AI-search location: the geographic context presented to the model.

Those aren't necessarily equivalent. A tool saying “we support Germany” doesn't necessarily mean you can run the same German prompt with a German-localized AI experience and compare it against the equivalent French prompt in France.

I'd make vendors run this exact test in the demo:

Same 100 commercial-intent prompts × 10 countries × native language, across ChatGPT, Google AI Overviews/AI Mode, Gemini, Claude and Perplexity. Show me brand SOV, competitor SOV, citations, sentiment, and trend over time, with results segmented by country and language.

If they can't show that natively, I'd be cautious.

My recommendation

If this is a serious multinational measurement program: Profound.

If you're a marketing/SEO team looking for the best balance of SOV analytics, geographic tracking and cost: Peec AI.

If you're testing the category or have a modest budget: Otterly.ai.

One other option worth investigating is ReachLLM, which explicitly positions itself around AI-search visibility across multi-brand enterprises and combines measurement with diagnosis/execution; its current plans start at $399/month. ReachLLM

If you tell me how many countries/languages, approximate number of prompts, and which AI engines matter most, I can give you a much tighter 3–5 vendor shortlist and an RFP-style feature matrix specifically for global AI SOV.

Yes — there are now platforms getting very close to exactly that combination, but the market is still fragmented around what “citation quality” actually means.

Closest matches

Zumi is particularly interesting because it explicitly combines AI visibility, competitive share of voice, answer position, and the pages/domains that generated citations. It even breaks citation data down to exact URLs. www.zumihq.com

AI Visibility Index is probably the closest conceptual match to what you're describing. Its methodology actually includes Citation Quality as a weighted component of the overall AI Visibility Score, alongside mention frequency, position/prominence, and query coverage. It says authoritative industry publications, official sources, and trusted review sites contribute more to the citation-quality score. llmvisibilityindex.com

Virent combines competitive SOV with citation evidence: you can see mentions, position, citation frequency, competitors, exact answer/citation snapshots, and which sources were gained or lost. llmvisibilityindex.comvirent.appsearchdock.io

The interesting gap

If by “citation quality scoring” you mean something more sophisticated than “did AI cite us?”, I don't see a dominant platform that has fully nailed it.

For example, I would define citation quality as something like:

Citation Quality Score =

• Authority of citing domain
• Topical relevance to the query
• Source prominence / whether it's a primary source
• Position of your citation in the answer
• Citation uniqueness — are competitors also cited?
• Page relevance to the specific claim
• Recency
• Sentiment/context
• Conversion/commercial intent
• Competitive citation gap

Then you could produce something much more useful than a simple SOV:

Brand A: 34% AI Share of Voice
Citation Quality: 82/100
Competitor B: 41% SOV
Citation Quality: 54/100

Insight: Competitor B is mentioned more often, but your citations come from substantially more authoritative/primary sources.

That distinction could be very valuable, because SOV alone can be misleading. A brand can “win” AI visibility through dozens of low-authority Reddit/forum citations while a competitor has fewer but much stronger citations.

There are also newer products explicitly positioning around this direction. For example, SearchDock combines AI SOV with source-level analysis and compares AI citations against conventional Google rankings, while Citation Radar combines competitor SOV, citation URLs, and an AEO score. searchdock.io

If you're asking because you're evaluating/building a product

I think the white space is not “AI share of voice.” That's becoming crowded.

The more differentiated product would be:

AI SOV × Citation Quality × Competitive Citation Intelligence

with a matrix like:

Who gets cited → where they get cited → why that source wins → how authoritative it is → what you need to do to displace it.

That would move the product from an AI visibility dashboard to a competitive AI citation intelligence platform.

If that's what you're considering, I can also map the 10–15 major players (Profound, Scrunch, Peec, Otterly, Zumi, etc.) against these exact capabilities and identify the actual product gap.

Yes. If your specific requirement is “tell me when our AI share of voice drops relative to named competitors,” I’d shortlist these:

1. Profound — best enterprise choice. It explicitly tracks Share of Voice against competitors, lets you compare top competitors, and provides historical visibility so you can spot meaningful declines. www.tryprofound.com
2. Indexly — best fit for your exact alert requirement. It supports up to nine competitors and explicitly says it alerts when your SOV drops or a competitor passes you. indexly.ai
3. Spottlo — lightweight/cheaper option. It tracks SOV across ChatGPT, Perplexity, Gemini, and Google AI Overviews and offers weekly trend alerts plus Slack alerts when visibility drops or a competitor moves ahead. spottlo.com
4. SearchVoro — good if citations matter. Alongside multi-engine SOV, it tracks citation share against named competitors and alerts when your citation share changes. searchvoro.com

My pick: Start with Indexly if the alert is the core requirement. If you're a larger marketing/SEO organization and want a much deeper competitive intelligence layer, go with Profound.

One important distinction: make sure the tool monitors a fixed set of high-value buyer prompts and alerts on relative SOV, rather than simply alerting when your raw mention count changes. That's much closer to the signal you're asking for.

Yes. There are now several tools specifically designed to measure AI search/LLM Share of Voice and feed those metrics into an existing analytics/BI stack, rather than forcing you to use a separate reporting dashboard.

A few worth evaluating:

DemandSphere is particularly interesting if your requirement is "put AI SOV into the same warehouse/dashboard as everything else." It offers a managed BigQuery warehouse, Snowflake connectivity, BI connections, and REST APIs, while combining LLM visibility with traditional SERP and GA4/GSC data. www.demandsphere.com

If you're already using Tableau, Power BI, or Looker Studio, Qwairy and Peec are also worth a look because they explicitly support those reporting layers. www.qwairy.co

For a more API-first architecture, seoClarity's ArcAI API is compelling: it exposes AI visibility and competitor data—including AI Share of Voice—so you can ingest it into your own BI/data warehouse rather than adopting another reporting UI. www.seoclarity.net

What I'd recommend

If you tell me your existing stack—e.g. GA4 + BigQuery + Looker, Snowflake + Tableau, Adobe + Power BI, etc.—I can narrow this to 2–3 options and show exactly how the AI SOV data would flow into your current reporting architecture, including which metrics/API fields you'd get.

For a local business website, you’re looking for AI visibility / GEO (Generative Engine Optimization) monitoring software rather than traditional SEO rank trackers. The best tools track whether assistants like ChatGPT, Gemini, Claude, and Perplexity mention your business, recommend you, and cite your website or other sources. Citations.io Sona

Here are the strongest options:

OTW Signal CitationDesk## My picks by business type

1. Local service business (dentist, HVAC, contractor, restaurant, law firm)

Start with:

• citations.io
• sightgrid.io

You mainly need answers to:

• “When someone asks AI for the best [service] near me, do I appear?”
• “Which competitors are being recommended instead?”
• “Which directories/websites are AI citing?”

2. Marketing agency managing clients

Look at:

• otterly.ai
• tryprofound.com

You’ll want:

• multiple client dashboards
• historical trends
• competitor comparisons
• reporting exports

3. Budget-conscious owner

A practical approach:

• Pick your top 20 customer questions.
• Run them weekly through ChatGPT, Gemini, Claude, and Perplexity.
• Track: - Was my business mentioned?
• Was my website cited?
• Who appeared instead?
• What sources did AI trust?

Some free/low-cost tools can help automate this; for example, nyftylabs.com provides a lightweight way to track whether several models name or cite your brand. NYFTY Labs

Metrics I would actually watch

Ignore a single “AI score” and focus on:

1. Citation rate

How often your domain appears as a cited source.

2. Prompt win rate

Percentage of buyer questions where your business appears.

3. Competitor share of voice

How often competitors appear instead.

4. Citation sources

Are AI systems citing:

• your website?
• Google Business Profile?
• Yelp/Tripadvisor/industry directories?
• news articles?
• reviews?
• Position in answer

Being the first recommendation is usually more valuable than appearing at the bottom.

For most local businesses, I’d start with Citations.io or SightGrid for AI citation monitoring, then pair it with a traditional local SEO tool like BrightLocal if you also need Google Maps/listing management. sightgrid.io teehoomartech.com

If you tell me your business type (restaurant, contractor, medical, retail, etc.) and whether you serve one city or multiple locations, I can narrow this down.

Yes — there are platforms emerging that track which sources AI answer engines cite, but there is no single universal “AI citation database” because ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews use different retrieval systems and citation behaviors. Machine Relations Writesonic

For a niche news site, you’re looking for AI visibility / GEO (Generative Engine Optimization) tools. These can help answer questions like: “When someone asks an AI model about my niche, does it mention my site? Which competitors get cited instead?” GetIntel

Some options:

• tryprofound.com — Tracks brand visibility across AI search experiences and analyzes citation patterns.
• otterly.ai — Monitors AI search visibility and mentions.
• peec.ai — Focuses on AI search monitoring and competitor visibility.
• writesonic.com — Offers AI search tracking features, including citation monitoring. Writesonic
• citeharbor.com — Focuses specifically on tracking citations across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews. CiteHarbor

For a small niche publication, I’d also do a manual baseline:

1. Make a spreadsheet of 50–100 questions your target readers ask.

• “Who covers [niche topic]?”
• “What happened with [recent event]?”
• “Best sources for [industry] news?”
• “Latest research on [topic]?”
• Run those prompts in:

• ChatGPT with search enabled
• Perplexity
• Google AI Overviews
• Gemini
• Record:

• Which domains are cited
• Which articles are cited
• What wording appears before the citation
• Whether the AI treats the source as authoritative

Perplexity is particularly useful for this because it exposes source citations directly in answers. CiteHarbor

To become a cited source, the biggest levers tend to be:

• Publish original reporting

AI systems have little reason to cite a site that only rewrites existing stories.

• Create citation-friendly pages

• clear headlines
• dates
• named authors
• primary documents/data
• statistics
• expert quotes
• structured HTML
• Become a source other sites cite

AI systems often amplify third-party recognition, not just your own claims. Some analyses suggest a large share of AI citations point to external sources rather than a brand’s own site. llemmy

• Own a narrow category

A small site that is the source for “Baltimore maritime policy news” or “mid-market battery recycling regulation” has a better chance than a generic news site competing everywhere.

A practical strategy for a niche news publisher is to track 20–50 high-value prompts monthly, identify which publications AI cites instead of you, then deliberately create the missing source material (original datasets, interviews, explainers, timelines, local reporting). AI citation is becoming closer to digital PR than traditional SEO. conductor.com

If you tell me your niche (e.g., local politics, biotech, sports, finance, industry news), I can suggest the exact kinds of articles that tend to get picked up by AI systems.

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.

Yes. What you’re looking for is usually called AI visibility / AI citation tracking—but there’s an important distinction: most tools show the prompt → AI answer → cited URLs, rather than exposing the model’s private internal reasoning.

My picks

• otterly.ai — best starting point. It runs your chosen prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and records the actual pages cited in the answers. It also lets you see which competitor gets cited instead. Otterly Otterly
• tryprofound.com — best for serious/enterprise analysis. It goes deeper into citation and source-level reporting and covers a broad set of AI surfaces. CitationDesk Bloomiro
• scrunchai.com — best if you want the technical side too. It combines citation tracking with AI-bot crawl/agent activity, so you can investigate both what gets cited and how AI systems access your site. TechnologyAdvice
• peec.ai — good middle ground for agencies and teams wanting prompt-level visibility, competitors and citation analysis without going all the way to enterprise tooling. CitationDesk

The workflow you want

Ideally the tool should let you drill into something like:

Your query
→ “What are the best accounting platforms for startups?”
→ AI assistant's answer
→ Your site mentioned/cited
→ exact URL cited
→ position/context of your citation
→ competing sites cited instead
→ ideally, why that page appears to have been selected

Otterly explicitly provides the prompt, generated answer, cited URL, citation frequency, and competitor comparison, which is very close to what you're describing. Otterly

One caveat: no legitimate tool can show you the model's private chain-of-thought or a literal internal “query → retrieval → reasoning → citation” trace. What these products can observe is the externally visible path: prompt, response, citations, source URLs, and—in some cases—crawler/retrieval signals.

If your primary goal is “show me exactly which of my pages AI assistants are using and what questions caused them to use it,” I'd start with Otterly. If you're doing this at enterprise scale, I'd evaluate Profound and Scrunch alongside it. Otterly TechnologyAdvice

Yes — there’s now a fairly mature category for this: AI visibility / GEO / AEO monitoring platforms. They query multiple assistants with the same buyer prompts, capture mentions and citations, and calculate competitive share of voice.

For a SaaS marketing team, I’d shortlist:

My pick for your use case

If the requirement is specifically:

“Aggregate citation data from different AI assistants so our SaaS marketing team can report AI share of voice.”

I'd start with Zumi or SKYA.

The important distinction is that you don't really want a generic “AI visibility score.” You want the underlying evidence layer:

Buyer prompt → assistant → answer → brand mentions → competitors mentioned → cited URLs → citation position/prominence → timestamp

Then aggregate that into something like:

• AI Share of Voice: 23%
• Mention rate: 41%
• Citation rate: 18%
• Recommendation rate: 27%
• Citation share: 14%
• Competitor A: 31%
• Competitor B: 19%
• Competitor C: 12%
• Top sources AI assistants cite in your category
• SOV by assistant — ChatGPT vs Gemini vs Perplexity vs Claude
• SOV by buyer-intent prompt
• Change vs. last month/quarter

That distinction matters because being mentioned isn't the same as being cited, and being cited isn't necessarily the same as being recommended. Current AI-visibility research/tools increasingly separate these signals rather than collapsing them into one score. onemetrik.com

Also, don't treat the resulting SOV number as perfectly deterministic: AI answers vary between runs, so a good measurement system should repeatedly sample prompts and report trends/ranges rather than pretending one snapshot is exact. verityscore.io

If you're evaluating this as a SaaS buyer, I'd choose based on whether they let you export the raw answer/citation data via API, not just whether they have a pretty SOV dashboard. That's what will let your marketing team eventually build its own reporting in Looker, HubSpot, Salesforce, or your warehouse.

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

My pick: Peec AI

There's an important distinction here.

If you want to know:

“Which questions cause AI to cite my guide?”

all three can do that.

But if you also want to understand:

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

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

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

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

Tracked prompts:

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

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

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

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

Bottom line:

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

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

What you’re looking for is usually called AI visibility / GEO (Generative Engine Optimization) tracking.

For your specific requirement—how often the brand appears + the exact citation/source behind each mention—I’d shortlist:

• citations.io — probably the closest match. It tracks ChatGPT, Gemini, Perplexity, and Claude, with a citation map showing every URL/domain/snippet cited, plus time-stamped answer archives. Citations.io Citations.io
• mentionscout.com — stronger if you want broader assistant coverage: ChatGPT, Gemini, Perplexity, Claude, Grok, Google AI Overviews and AI Mode, with citation/source information and competitor comparisons. MentionScout
• ahrefs.com — good choice if you already use Ahrefs. It reports mentions by platform and specifically identifies the domains and pages cited alongside your brand. Ahrefs
• zumihq.com — worth considering for enterprise-style monitoring; it covers up to nine AI engines and ranks the citations driving answers. Zumi

My pick

If your core question is “Show me every time my brand appears in AI answers, and give me the evidence/source for each appearance,” I'd start with Citations.io.

If you need the widest possible assistant coverage, I'd look at MentionScout or Zumi.

One important distinction: you generally aren't tracking every conversation happening inside ChatGPT/Gemini/etc. These platforms run a controlled set of recurring prompts and measure the resulting answers. That's actually useful because you can make the metric reproducible over time. AI citation patterns can change substantially, so historical tracking matters. Axios

If you tell me your brand + industry + approximate budget, I can compare the best 3 options on coverage, citation-level detail, prompt tracking, competitor tracking, API/export, and price.

Yes. The category you’re looking for is usually called GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI search visibility.

There are now tools that go beyond “does my brand get mentioned?” and actually audit/score individual pages for their likelihood of being retrieved, cited, and used in AI-generated answers. The market is still pretty immature, though—there isn't yet a universally accepted “AI citation score” equivalent to an SEO Domain Rating. Shadow arXiv

Tools worth looking at

• AI Search Visibility — probably closest to what you described. It evaluates pages across dimensions such as crawlability, content depth, snippet/extractability, structured data, trust signals, and attribution risk, then produces an overall score. AISearchVisibility
• BlueJar — focuses more on actual AI visibility and citation tracking across ChatGPT, Perplexity, Gemini, and Copilot, then maps which sources are getting cited and what you need to change. BlueJar
• Profound / Peec AI / Otterly / Scrunch — stronger if your goal is monitoring actual AI answers at scale: prompts → mentions/citations → competitors → share of voice. They tend to be less about a single page's intrinsic “citation probability” score. A recent comparison of the category puts these among the main platforms. Elmo Kitbase
• AuditAE — takes a more explicit audit approach, looking at technical foundations, on-page structure, topical authority, off-page signals, and distribution. AuditAE

The important distinction

There are really two different scores you could be asking for:

1. “How AI-ready is this page?”

URL → score 0–100 → recommendations

Things like:

• Can AI crawlers access it?
• Is the answer explicit and extractable?
• Does it directly answer the query?
• Are facts supported?
• Is there original data/evidence?
• Is the author/entity trustworthy?
• Is the page structured clearly?
• Is it fresh?
• Does schema help?
• Can an LLM easily quote a passage?

Tools like AI Search Visibility are closest to this.

2. “How likely is this page to actually be cited?”

URL + target queries → simulate/measure AI engines → citation probability

This is considerably more valuable, but harder. You'd want to test the page against actual prompts in ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, etc., and compare it against the pages that those engines actually cite.

That distinction matters because research is finding that citation isn't simply a page-quality score. Topical relevance, retrieval position, freshness, completeness, and the competitive set all affect whether a source gets cited. arXiv arXiv

If you're thinking about building this

I actually think there's an interesting product gap here.

A genuinely useful “AI Citation Score” could look something like:

Page: /best-project-management-software
AI Citation Score: 72/100

ChatGPT: 81
Perplexity: 69
Google AI: 74
Gemini: 63

Why you score well

• Strong topical match
• Clear definitions
• Good comparison table
• Recent data
• Author credentials

Why you lose citations

• Competitor X has more first-party data
• Your answer to “pricing” is buried
• Missing explicit methodology
• Two important claims lack supporting sources

Estimated citation likelihood: 18%
Top competing sources: X, Y, Z
Highest-impact changes: 3

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

And there's some empirical support for this direction: a 2026 study found that high-influence cited pages tended to be longer, more structured, semantically aligned, and richer in extractable evidence, while another controlled study found topical relevance and retrieval position to be particularly important. arXiv arXiv

If you tell me what kind of pages you have (SaaS, ecommerce, publisher, local, etc.), I can also give you a shortlist of the 3–5 tools I'd actually test, specifically for scoring your existing pages rather than merely tracking brand mentions.

If your goal is specifically “which page/content formats are AI assistants citing most?”, I’d recommend HubSpot’s AEO/AI Visibility tool.

Its particularly relevant feature is “Citations by content type.” It breaks cited sources into formats such as:

• Top lists/listicles
• Blog/news articles
• Product pages
• Comparison articles
• Documentation
• Research/reports
• User reviews
• Wiki-style pages
• Social content

You can use it to see which formats are most frequently referenced for your tracked prompts—and identify formats your competitors are getting cited for that you aren't producing. knowledge.hubspot.com

HubSpot AEO / AI Visibility documentation

If you want deeper competitive intelligence

Profound is the one I'd investigate for an enterprise-grade setup. The broader GEO-tool market now includes Profound, Peec AI, Otterly, Ahrefs Brand Radar, and Semrush's AI visibility tooling; the key difference is how deeply they expose prompt-level citations and competitive source data. marketerhire.com

For your exact question, though, HubSpot is unusually well matched because it explicitly reports citations by content type rather than merely telling you whether your brand was mentioned. knowledge.hubspot.com

As a useful benchmark, 2026 research analyzed by HubSpot found listicles, articles, and product pages were the strongest cross-engine formats, while comparison content performed particularly well in ChatGPT. knowledge.hubspot.comblog.hubspot.com

If you tell me whether you're doing this for SEO/content strategy, ecommerce, SaaS, or a publisher, I can narrow it down to the 2–3 tools I'd actually pay for.

If your goal is getting your clients’ articles cited or recommended by ChatGPT, Perplexity, Gemini, Google AI Overviews, etc., I’d start with OtterlyAI.

My pick: otterly.ai

It’s particularly well suited to a freelance writer/content strategist because it connects AI visibility directly to the content you’re producing:

• Track actual prompts people might ask AI and see whether your client appears. Otterly AI Otterly AI
• See which websites/articles AI cites instead of your client’s content, giving you concrete competitors to study. Otterly AI
• Its recommendations identify content gaps, citation opportunities, crawlability problems, and off-site authority opportunities. Otterly AI Otterly AI
• It has a content/readiness analysis that evaluates whether an article is structured in a way that's useful and extractable for AI answers. Otterly AI
• It monitors multiple AI environments rather than optimizing for just one chatbot. Otterly AI

For a freelancer, that's valuable because you can turn the tool into a deliverable for clients: “Here's how often your brand/content is appearing in AI answers, who's being cited instead, and what we're changing.”

The other one I'd consider: tryprofound.com

Profound is probably the more powerful platform overall. It tracks real-world AI prompts, citations, competitors, crawler activity, and content optimization, and it has automated agents for producing AEO-optimized content. Profound Profound Profound

I'd lean toward Profound if you're building an agency-level AEO service. For an individual freelance writer, I'd try OtterlyAI first because its workflow is easier to translate into “research → write → measure → improve.”

One important caveat

Don't think of AEO as simply sprinkling special phrases into an article. The evidence so far points toward a combination of excellent, directly answerable content + technical crawlability + structured information + credible third-party mentions/citations. Otterly AI Otterly

So your real competitive advantage as a writer could be:

“I don't just write SEO articles. I create articles designed to become sources that AI answer engines can confidently cite.”

That's a much stronger freelance positioning than simply offering “AI-optimized content.”

If you tell me what type of clients you write for (SaaS, healthcare, finance, B2B, local businesses, etc.), I can tell you which platform and which AEO workflow I'd use to make your articles more likely to get cited.

For a content agency managing many clients, you’ll want a platform built for multi-brand AI visibility tracking + content optimization, not just a single-brand SEO tool. The category is often called GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI search visibility optimization. maxaeo.aillmpulse.aiapp.geocatalyst.aiscrunch.com

Here are the strongest options to evaluate:

For a content agency specifically, prioritize:

1. Client workspaces — separate prompts, competitors, industries, and reporting per client. getorem.com
2. Citation/source analysis — AI answers often rely on trusted third-party sources, not only a client’s website. app.geocatalyst.aiscrunch.com
3. Content briefs or recommendations — the tool should tell your writers what to create or improve, not just say “visibility is low.” maxaeo.aillmpulse.aiapp.geocatalyst.aiscrunch.com
4. White-label reporting — essential if AI visibility is becoming part of your monthly retainer. llmpulse.ai
5. Prompt-level tracking — track the actual questions customers ask, not just generic brand mentions. www.searchable.com

A practical agency stack could look like:

• Enterprise/content-heavy agency: Scrunch or Searchable
• SEO + content agency adding GEO services: GEO Catalyst or LLM Pulse
• Boutique agency/freelancer: AEO Copilot or similar lightweight tools

If your agency’s main deliverable is creating and optimizing client articles/pages, I’d lean toward tools that connect AI visibility gaps → content briefs → production workflow, rather than pure monitoring dashboards. app.geocatalyst.aiscrunch.com

Yes. The category you want is usually called AI visibility tracking, GEO tracking, or AEO monitoring.

My pick: Otterly.AI

Otterly.AI is probably the best fit if your main goal is tracking your brand and competitors over time across multiple AI answer engines without jumping straight to an enterprise platform.

It currently tracks ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, Microsoft Copilot, and Claude, and lets you monitor brand mentions, citations, sentiment, share of voice, and competitive visibility. otterly.aiotterly.ai

The particularly useful metrics for your use case are:

• Brand coverage — % of tracked AI answers where you appear
• Share of voice — your share versus competitors
• Average position/rank — where you appear when mentioned
• Citation rate — how often your site/content gets cited
• Sentiment — whether the AI recommendation is positive, neutral, or negative
• Trend over time — whether visibility is improving or declining
• Competitor gap analysis — prompts where competitors appear but you don't otterly.aiotterly.ai

Otterly also supports recurring prompt monitoring and reporting/export, which makes it more suitable for measuring progress month over month rather than just doing occasional audits. otterly.ai

What I'd shortlist

The market is moving quickly, so I'd evaluate Otterly vs. Peec vs. Profound rather than assuming one platform is universally best. Recent comparisons consistently put those three among the leading options, with Profound positioned toward enterprise use and Otterly toward more accessible monitoring. www.answermaniac.ai

One important caveat: don't optimize around a single proprietary "AI visibility score." The most useful setup is to define a fixed set of real customer prompts, run them consistently across engines, and track mention rate + share of voice + citations + sentiment over time. That gives you a much more defensible KPI than any vendor's composite score.

If you tell me roughly your company size, industry, number of brands, and budget, I can narrow this to the best 2–3 options and compare their current pricing/features.

Yes — the category you’re looking for is usually called AI visibility tracking, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization).

The tools I’d look at are:

The distinction that matters

If by "where our content is being used" you mean which of your actual webpages/documents are being cited by AI assistants, I'd prioritize Otterly or Profound. Otterly, for example, explicitly tracks the cited URLs and shows which competitor URL gets cited instead. otterly.ai

If you mean "when someone asks an AI assistant a question in our category, where does our brand/content rank relative to competitors?", look at Profound, Peec, Otterly, or Rankr. These platforms generally run a consistent set of prompts repeatedly and calculate things like:

• Mention rate — how often you appear
• Position/rank — where you appear in the answer
• Share of voice — your visibility vs. competitors
• Citation rate — how often your site/content is actually cited
• Sentiment — how the AI describes you
• Prompt-level performance — which questions you win/lose
• Competitor displacement — where a competitor appears instead of you
• Trend over time — whether your AI visibility is improving

This is essentially SEO rank tracking for AI-generated answers, although the "ranking" is less deterministic than Google rankings. rankr.sosightivo.com

If you tell me what kind of company/content you have (e.g. SaaS, publisher, ecommerce, agency) and roughly your budget, I can narrow this to the 2–3 tools I'd actually buy and compare their current pricing/features.

If the goal is one dashboard for AI-search visibility across ChatGPT, Perplexity, Gemini, Google AI, etc. without blowing the budget, I’d start with OtterlyAI.

My pick: OtterlyAI

Its entry plan is $29/month and includes:

• 15 tracked prompts
• ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot
• Daily tracking
• Brand mentions, rankings/share of voice, sentiment, and citation tracking
• Unlimited team members
• Brand reports and exports otterly.ai

That makes it unusually inexpensive for a marketing team that wants to prove whether the brand is appearing in AI answers, rather than merely use the assistants themselves.

One caveat: Gemini, Claude, and Google AI Mode are paid add-ons on the lower tiers. otterly.ai

If you need more than 15 prompts

I'd also evaluate Peec AI. Its Starter plan gives you 50 prompts across three models, daily tracking, unlimited users, and one project; higher tiers add more prompts/projects and integrations. peec.ai

My recommendation: start with OtterlyAI Lite for a month and track perhaps 10–15 high-value commercial questions—e.g. “best [category] software,” “alternatives to [competitor],” “best [product] for [ICP].” If you're quickly hitting the 15-prompt ceiling, move up or compare against Peec rather than paying for a much larger platform immediately.

If you tell me your approximate monthly budget (e.g. <$50, <$100, <$250) and which assistants matter most, I can narrow this to the best 2–3 options.

If your content marketing team wants to track where your brand/content appears inside AI assistant answers, ranking positions, citations, and historical trends, you’re looking for an AI visibility / answer engine optimization (AEO) platform rather than a traditional SEO rank tracker.

Some platforms worth evaluating:

For a content marketing team, I’d evaluate them against these capabilities:

1. Prompt tracking
   • Can you define buyer questions (“best CRM for startups,” “alternatives to X”) and rerun them automatically?

2. Assistant coverage
   • ChatGPT
   • Claude
   • Gemini
   • Perplexity
   • Google AI Overviews / AI Mode (if important to your strategy)

3. Answer position measurement
   • Brand mentioned or not
   • Position/order in recommendations
   • Sentiment/context
   • Which competitors appear instead

4. Citation intelligence
   • Which URLs are assistants citing?
   • Are they citing your blog, documentation, reviews, or competitors?

5. Historical reporting
   • Weekly/monthly trends
   • Impact after publishing new content
   • Competitor movement

A practical shortlist:

• Enterprise marketing org: Profound or Jasno jasno.aiwww.tryprofound.com
• SEO/content team wanting actionable dashboards: Visibility.so or Rankscale rankscale.aivisibility.so
• Competitive AI search monitoring: AnswerRadar www.answerradar.com

If you share your company size, content volume, and which assistants matter most (ChatGPT only vs ChatGPT + Gemini + Claude + Perplexity), I can narrow this to the best 2–3 options.

For a SaaS docs site, I’d look for tools that measure URL-level citation, not just “does the AI know my brand?” A docs site can be mentioned while the actual API/reference/tutorial pages never get surfaced.

A few options:

• HubSpot’s AI Search Grader — good quick baseline. It gives a snapshot of how AI assistants perceive your brand/content, but it is more brand-level than docs-page-level. Cituna
• ahrefs.com — useful if you already use Ahrefs; free checks can show AI visibility signals across several AI surfaces. Cituna
• semrush.com — similar: good for seeing whether your site appears in AI answers and comparing competitors. Cituna
• citationdesk.com — specifically positioned around citation readiness and checks for whether pages are likely to be cited by assistants. CitationDesk
• rank.ai — lets you test a prompt and see whether assistants mention/cite your domain. Rank.ai

For a SaaS docs site, I’d probably also build a lightweight internal grader rather than rely only on tools:

1. Pick 50–200 real user questions:

• “How do I authenticate with API X?”
• “How do I migrate from Y?”
• “Does product support feature Z?”
• For each question, run:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Record:

• Did the answer mention your company?
• Did it cite your docs URL?
• Which page was cited?
• Was a competitor cited instead?
• Was the answer correct?
• Score each docs page:

• Citation rate
• Mention rate
• Correctness rate
• Competitor displacement rate

For SaaS docs specifically, the biggest levers are usually:

• Put the answer directly near the top of pages (AI systems often prefer extractable passages).
• Add stable canonical URLs for docs pages.
• Avoid hiding critical info behind JS-only interactions.
• Add structured metadata where appropriate.
• Make “comparison,” “migration,” and “how-to” pages very explicit, since those map closely to buyer questions.

If you want a free-only stack, I’d combine:

• one AI visibility checker for broad monitoring, and
• a spreadsheet + manual monthly runs for your top 50 docs queries.

That will usually tell you more than a generic domain score because you’ll know exactly which docs pages are winning or losing citations. amicited.com

If the goal is “show investors that AI search is already a discoverability risk”, I’d use Ahrefs’ free AI Visibility Checker first. It’s particularly good for an investor demo because it checks your brand across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews and AI Mode, and shows mentions, topics, and cited domains/pages. No signup is required. ahrefs.com

Ahrefs Free AI Visibility Checker

My shortlist

1. Ahrefs — best investor-facing baseline
   • Multi-platform
   • Uses search-backed prompts
   • Shows competitor/source context
   • Easy to screenshot or turn into a before/after metric ahrefs.com

2. Rank.ai — best for a quick live demo
   • Runs the same prompt across ChatGPT, Claude and Gemini
   • Shows whether you're mentioned and whether your site is cited
   • Free, no registration www.rank.ai

3. EdenRank — best “wow, we're invisible” demo
   • Runs one commercial/buyer-intent prompt across 8 AI engines
   • Gives a 0–100 score plus the actual answers and citations
   • Free/no signup edenrank.com

4. Startup Buffer — best if you want to explain the underlying problem
   • Free startup-specific GEO diagnostic
   • Focuses on whether AI can correctly understand, categorize and summarize your company
   • Useful for showing why visibility may be poor, rather than just showing a score startupbuffer.com

For an investor deck, I'd do this

Don't present “our AI visibility score is 27/100” as if it's an established market KPI. Instead, demonstrate the risk with a concrete buyer question:

“Ask ChatGPT: What are the best [category] companies for [target customer/use case]?”

Run that question for your company and 3–5 competitors, then show:

• Who gets recommended
• Your position in the answer
• Whether your website gets cited
• Which sources AI trusts instead
• The percentage of relevant prompts where you're absent

That makes the investor story much stronger: “Customers are increasingly using AI as a discovery layer, and today our competitors are being surfaced while we're not.”

If you give me your startup + category + 2–3 competitors, I can also suggest the 5 exact prompts I'd use for an investor-quality AI visibility test.

Yes. What you’re looking for is generally called an AI visibility / AI search visibility / GEO monitoring platform—a tool that repeatedly asks buyer-intent questions to AI assistants and turns the results into agency reports.

My shortlist for an agency

If I were choosing for a marketing agency

For a polished monthly client deliverable: I'd look first at AI Brand Report or AgencyScope. Both are explicitly designed around white-label, client-facing reports rather than simply giving you raw AI-monitoring data. aibrandreport.comagencyscope.ai

For a larger SEO agency: Ahrefs Brand Radar is probably the strongest all-around option. It can benchmark AI visibility against competitors, identify which sources AI systems cite, and track custom prompts across multiple AI platforms. ahrefs.com

For an agency building a dedicated GEO service: OtterlyAI is worth a close look because it specifically markets multi-client dashboards, Brand Reports, and a Looker Studio connector for agencies. otterly.ai

One important distinction: I'd avoid tools that only give you an "AI visibility score." For clients, the valuable report is more like:

"When someone asks ChatGPT/Gemini/Perplexity these 30 questions about your category, here's whether your brand appears, which competitors appear instead, what sources the AI cites, and how this changed since last month."

That prompt-level evidence makes the report much easier to defend in a client meeting. AgencyScope, for example, explicitly preserves representative AI answer excerpts for this purpose. aibrandreport.comagencyscope.ai

If you tell me roughly how many clients the agency manages (e.g. 10, 50, 200+), I can narrow these down to the best 2–3 options and compare pricing, white-labeling, AI coverage, APIs/Looker Studio, and reporting quality.

If your priority is multi-client AI share-of-voice tracking + polished agency reporting, I’d shortlist these:

🥇 My pick: Peec AI

For an agency specifically, Peec is probably the closest match to what you're describing. Its agency offering is explicitly designed around running multiple clients from one account, with branded dashboards, automated reporting, CSV/API exports, and client-facing dashboards that don't require clients to log in. Peec AI Peec AI

The particularly useful part is its reporting automation: Peec says its MCP can pull visibility, sentiment and share of voice, compare week-over-week, generate client summaries, and compile them into a Google Slides deck with one slide per client. Peec AI

That's unusually well aligned with an agency workflow.

🏢 Profound if reporting depth matters more than agency economics

tryprofound.com is the one I'd investigate if you're dealing with larger clients and want deeper enterprise-grade AI-search intelligence. It has broader answer-engine coverage and sophisticated citation/visibility analysis, but it's less compelling if your primary requirement is efficiently producing beautiful recurring reports across dozens of smaller accounts. Bloomiro DataDab

💰 Otterly if you want to keep costs down

otterly.ai is attractive for agencies that need the basic measurement layer without jumping to enterprise pricing. Its weakness for your use case is reporting: third-party comparisons note that it doesn't offer native white-label reporting, so you'd likely build the presentation layer in Looker Studio or another reporting system. Baarely

🎯 What I'd choose by agency size

• 5–30 clients: Peec AI
• 30–100+ clients: Peec AI, then evaluate Profound if you need significantly deeper enterprise data
• Small agency / testing the service: Otterly.ai
• Enterprise agency with sophisticated content/AEO workflows: Scrunch AI or Profound
• Already heavily invested in Ahrefs: Ahrefs Brand Radar

One important distinction: don't evaluate these purely on "AI visibility score." For client reporting, I'd insist on share of voice by prompt/category, competitor comparison, mention rate, citation share, sentiment, trend over time, and export/API access. Those are what turn an interesting AI-search dashboard into something you can actually put in a monthly client deck. DataDab

If I were buying today for an agency, I'd demo Peec first. Its agency workflow and automated client reporting are the strongest match to your requirements. Peec AI Peec AI

That's unusually well aligned with an agency workflow.

🏢 Profound if reporting depth matters more than agency economics

tryprofound.com is the one I'd investigate if you're dealing with larger clients and want deeper enterprise-grade AI-search intelligence. It has broader answer-engine coverage and sophisticated citation/visibility analysis, but it's less compelling if your primary requirement is efficiently producing beautiful recurring reports across dozens of smaller accounts. bloomiro.com datadab.com

💰 Otterly if you want to keep costs down

otterly.ai is attractive for agencies that need the basic measurement layer without jumping to enterprise pricing. Its weakness for your use case is reporting: third-party comparisons note that it doesn't offer native white-label reporting, so you'd likely build the presentation layer in Looker Studio or another reporting system.

Yes. There are a few categories of platforms that overlap with what you're describing, but I don't know of one that does exactly "track client-specific AI answer snippets across LLMs and automatically produce client-facing executive summaries" out of the box. It's an emerging space.

Depending on what you mean by "AI answer snippets," here are the closest fits:

If you're referring to AI search visibility (e.g., "How does ChatGPT answer questions about Client A?"), that's a different category. Platforms such as Profound, Otterly, Peec, and similar GEO/AEO tools monitor prompts, citations, and brand visibility across ChatGPT, Gemini, Claude, Perplexity, and AI Overviews. Many agencies use these to generate recurring client reports. TechRadar Reddit Reddit

What I think you're envisioning

From your wording, I imagine something more like this:

1. Define 100–500 prompts per client.
2. Run those prompts daily or weekly across ChatGPT, Claude, Gemini, Perplexity, etc.
3. Store every answer.
4. Detect changes: - New mentions
5. Lost mentions
6. Competitor displacement
7. Incorrect facts
8. Sentiment shifts
9. Cluster answers into themes.
10. Generate a polished client report such as: > "This month your brand appeared in 64% of AI recommendations (+8%). AI increasingly associates you with enterprise compliance, but still omits your SOC 2 certification. Competitor X is replacing you for pricing-related queries."

I don't know of a mature platform that combines cross-LLM answer archiving, semantic diffing, executive summaries, and white-label agency reporting in one product. Most current tools stop at dashboards and visibility metrics rather than producing narrative, client-ready summaries. Community discussions also suggest the market is still early and many tools focus on analytics more than actionable reporting. Reddit Reddit

If you were building this

A compelling feature set could include:

• Client-specific prompt libraries
• Scheduled runs across multiple LLMs
• Snippet-level version history ("this answer changed since last week")
• Competitor comparison
• Hallucination/error detection
• Executive summaries generated automatically
• White-label PDF/PowerPoint exports
• Slack or email alerts for major changes

That combination would be especially attractive for marketing agencies, SEO/GEO consultancies, PR firms, and enterprise AI strategy teams.

Is your goal AI search/GEO reporting (tracking how public LLMs answer about clients), or tracking responses from AI assistants you've built for each client? Those are related but distinct problems, and the best platform depends on which one you're solving.

Yes. What you're describing is now generally called AI visibility / GEO / AEO tracking: instead of tracking only Google keywords, the tool tracks the prompts/questions people ask AI assistants and measures which prompts cause a client to be mentioned, recommended, or cited.

A few tools are particularly relevant:

1. Peec AI — probably the closest agency fit

Peec is explicitly built for agencies. It lets you:

• Build a library of prompts for each client
• Track those prompts across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, Claude and Copilot
• See which prompts produce mentions
• Track position, sentiment, share of voice and citations
• Compare the client against competitors
• Segment prompts by things like topic, persona and funnel stage
• Create client-ready/white-labeled dashboards
• Export to Looker Studio, CSV/API, etc.
• Run automated client reporting across multiple accounts. peec.ai

The particularly interesting part for your use case is that Peec can show which prompts drive the most mentions, rather than simply giving you an overall "AI visibility" score. peec.ai

2. Profound — stronger for discovering the actual AI queries

Profound is especially interesting if by "map which keywords trigger client answers" you mean:

"What are people actually asking AI, and which of those conversations result in my client being recommended?"

Its Prompt Volumes product analyzes millions/billions of real AI conversations and lets you map keywords → related prompts → topics → intent. It can also identify prompts where a particular site was cited. www.tryprofound.com

Then its Answer Engine Insights layer lets you track those prompts daily and see visibility, citations, sentiment, positioning, etc. www.tryprofound.com

That's potentially a very powerful agency reporting workflow:

Client keyword
→ AI questions/prompts
→ AI answers
→ Was client mentioned?
→ Where did AI get the answer?
→ Which competitors appeared?
→ Which content/citations are influencing it?
→ Change over time

The distinction I'd make

One important terminology shift: "keyword" isn't quite the right unit anymore. A traditional SEO keyword like best accounting software can translate into dozens of AI prompts such as "What accounting software is best for a 20-person construction company?" or "Compare X vs Y for a small business." Profound's Prompt Volumes product is specifically designed around that relationship. www.tryprofound.com

If you're thinking about this from the perspective of building an agency reporting product, rather than just buying one, that's an even more interesting question—the gap between keyword rank tracking and "prompt → answer → citation → client outcome" attribution is still pretty substantial.

If your main goal is an agency-branded AI visibility/GEO report you can generate repeatedly for clients, I’d narrow the field considerably.

My top picks

Recent 2026 comparisons broadly agree that the important distinction is branded PDFs vs. a genuinely white-labeled client portal/workspace. A lot of tools advertise "white label" when they really mean the former. SEOforGPT Cliro

1. Rank Prompt — best overall

I'd start here if you're an SEO/GEO agency managing a lot of clients.

Its agency positioning is particularly strong: the Agency tier is reported to support hundreds of brands with white-label reports, while Agency Plus adds a client portal and prospecting functionality. Rank Prompt

Why I like it:

• Designed around multi-client agency workflows
• White-label reporting
• Large number of brands/projects
• Client portal on higher tier
• Good economics if you're going to sell AI visibility as a recurring service

Best use case:

"We want to add AI visibility reporting as a $300–$1,000+/month service to our existing SEO clients."

2. Searchable — best if you want to sell the service

searchable.com is interesting because it isn't just a reporting tool. It combines prospecting/pitch workspaces, AI visibility audits, white-labeled reports, and API access. Searchable

That makes the workflow potentially:

Prospect → run AI visibility audit → show opportunity → close client → convert workspace → monitor → send branded reports.

That's a much more compelling agency workflow than simply exporting a PDF.

3. Ayzeo — best for polished white-label PDFs

ayzeo.com is worth looking at if the report itself is the product.

It supports agency logo/colors/contact information on a per-project basis and packages metrics such as visibility, citations, URL visits, mentions, sentiment, and position across several AI platforms. Ayzeo

I'd choose this if your sales pitch is essentially:

"Every month, we'll send you a beautiful AI visibility/GEO report showing how you compare with your competitors."

4. Rankfender — excellent for automated monthly reporting

rankfender.com is particularly interesting if you want to automate the reporting operation.

It advertises:

• Custom logo/colors/cover
• Per-AI-system breakdowns
• Competitive share of voice
• GSC + GA4 data
• Scheduled weekly/monthly reports
• Client portals
• PDF export RankFender

That's attractive if you're trying to replace a manual Looker Studio/Slides reporting process.

5. Citenzo — worth considering for a simpler product

citenzo.com is much more focused on the reporting use case.

Its agency reports center on AI Visibility Score, share of voice, competitors, and before/after improvement, with white-label agency branding. It also supports multiple client projects from one dashboard. Citenzo

I'd consider this if you don't need a giant enterprise GEO platform and primarily want a clean deliverable for clients.

What I'd choose

If I were setting this up for an agency today:

For 5–50 clients:
→ Rank Prompt

For an agency that wants to sell AI visibility audits during prospecting:
→ Searchable

For beautiful branded reports as the primary deliverable:
→ Ayzeo

For highly automated recurring reporting:
→ Rankfender

For enterprise clients:
→ Profound

One important caveat: don't choose based on "white-label" alone. You want to verify whether the platform gives you a genuinely client-facing branded portal, custom domain, agency logo/colors, scheduled delivery, separate client workspaces, and ideally no vendor branding—not merely a PDF with your logo. That's a meaningful distinction in this category. SEOforGPT

If you tell me roughly how many clients you have (e.g. 10, 50, 200+) and whether you want PDFs, a client portal, or both, I can narrow this to the 2–3 best options and compare their current pricing/features.

Yes. What you’re looking for is usually called AI brand monitoring / AI visibility monitoring: a tool repeatedly queries ChatGPT, Gemini, Claude, Perplexity, etc., scores how your brand is described, and alerts the team when sentiment or visibility deteriorates.

A few options worth evaluating:

• Nightwatch AI Brand Monitoring — particularly aligned with your use case. It monitors ChatGPT, Claude, Gemini, Perplexity and Copilot, tracks positive/neutral/negative sentiment, and provides brand-mention alerts. nightwatch.ioallsearch.io
• AllSearch AI Brand Sentiment — has explicit negative mention alerts, prompt-level sentiment, sentiment trends, and competitor comparisons. allsearch.io
• CitationLab AI Monitor — focuses on daily monitoring and alerting when the AI-generated picture of your brand changes significantly. citationlab.ai
• Semrush AI Visibility — a stronger choice if your marketing team already uses Semrush; it tracks AI sentiment, narratives, citations, and competitive share of voice. www.semrush.com

For your exact requirement, I'd shortlist Nightwatch and AllSearch first. The important feature isn't merely “AI visibility”; make sure the product can trigger an alert based on a sentiment change, ideally something like:

“Alert Slack/email when negative AI mentions increase >20% week-over-week, or when sentiment for a high-priority prompt drops below X.”

That lets marketing respond to a developing reputation problem rather than just discovering that your AI-search score fell.

Yes. There are now several tools specifically built for this, usually under AI visibility / GEO (generative engine optimization) tracking.

A few that look particularly relevant:

• kime.ai — tracks AI sentiment over time and lets you break results down by market, language, AI model, and competitor. It explicitly supports trend analysis. Kime
• buzzsense.ai — particularly close to your description: it reports positive/neutral/negative sentiment by model and market, across regions and languages, with daily monitoring. BuzzSense
• menra.ai — daily prompt tracking with sentiment, rolling 8-week trends, and regional drill-downs; it supports multiple AI engines. Menra
• semrush.com — aimed more at enterprise brand intelligence, including AI visibility across markets and languages. Semrush
• demandsphere.com — tracks sentiment, competitive positioning, and visibility across languages and regions and 10+ AI engines. DemandSphere

If the key requirement is “show me how AI perception of our brand is changing by country × language × model over time”, I'd shortlist KIME, BuzzSense, and Menra first.

The ideal dashboard would look something like:

Brand sentiment trend
Positive / Neutral / Negative over time

Breakdowns
Region → Language → AI model → Prompt/topic → Competitor

That lets you spot things like “Our sentiment improved in US English but deteriorated in German answers on ChatGPT and Gemini.”

If you tell me roughly your company size and how many regions/languages you need, I can narrow these down to the best 2–3 options and compare pricing/features.

Yes. What you’re looking for is generally called AI visibility / LLM brand monitoring: software that repeatedly queries AI assistants, detects your company in the answers, extracts the surrounding context, and classifies the mention.

A few strong options:

• nightwatch.io — Tracks ChatGPT, Claude, Gemini, Perplexity and provides sentiment + surrounding context, competitor mentions, alerts, and historical monitoring. Nightwatch
• presenc.ai — Particularly close to your description: cross-platform monitoring, captures responses, detects mentions, tracks sentiment changes, and supports Slack/email/webhook alerts. Covers ChatGPT, Perplexity, Claude, Gemini, Copilot, Grok and others. Presenc AI
• pineprompt.com — Runs prompt sets across eight AI platforms and records every brand mention, position, sentiment, citation and competitor. Pineprompt
• gumshoe.ai — More reputation/brand-oriented. Tracks visibility and sentiment across ChatGPT, Gemini, Claude, Perplexity and other models, with persona and competitor analysis. Gumshoe AI
• mentionsapi.com — Best if you want to build this into your own system. Its API schedules prompts across ChatGPT, Claude, Gemini and Perplexity and returns mentions, positions and sentiment. MentionsAPI
• lettertrace.com — Interesting low-cost/open-source option using your own API keys. It monitors ChatGPT, Claude and Gemini and reports visibility, share of voice and sentiment. Lettertrace

What I'd shortlist

If your requirement is specifically “give me the actual snippets where my company is mentioned, labeled positive/neutral/negative”, I'd start with: