Answers that mention Peec AI

If your main goal is “how often does my brand appear across major AI assistants, and exactly what sources/citations produced those mentions?”, I’d look first at Peec AI and Profound.

• peec.ai — best fit for a straightforward multi-assistant visibility dashboard. It tracks mention frequency, position, sentiment, and share of voice across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, and Microsoft Copilot. It also exposes the URLs/domains cited, including citation frequency. Peec AI Peec AI
• tryprofound.com — particularly strong if citation/source analysis is the priority. Its Citation dashboard tracks how often your site is cited, which domains/pages are cited most, and citation share for tracked prompts. It covers answer engines including ChatGPT, Perplexity, and Gemini. Profound Help Center Profound
• Otterly.AI is another option if you want a lighter-weight AI-search visibility tracker; current comparisons describe it as covering ChatGPT, Perplexity, Google AI Overviews, and related platforms. SiteTest.ai

What I'd choose

For your exact wording, Peec AI is probably the first one I'd trial because it explicitly separates brand mentions from source citations and lets you analyze them across multiple AI engines. Peec AI

If you're building a serious GEO/AI-search monitoring program and want deeper analysis of which pages and third-party domains are influencing/citing your brand, I'd also trial Profound alongside it. Profound

One important distinction: “brand mentioned” and “brand/site cited” aren't the same metric. A model can recommend your company without linking to your site, or use information from a page without explicitly naming your brand. Peec, for example, reports both source usage and explicit citations. Peec AI

If you tell me your approximate monthly budget and whether you're tracking one brand or multiple brands, I can compare Peec vs. Profound vs. Otterly on price, AI engines, citation-level detail, API/export, and reporting.

For a small marketing team looking to monitor AI share of voice (SOV) across multiple LLMs (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.), I’d prioritize tools that do three things well:

1. Track a fixed prompt set over time (not just one-off checks)
2. Compare your brand vs. competitors
3. Show citations/sources so your team knows what to improve

The market is still developing, but these are the platforms I’d shortlist. AI Visibility Software TechnologyAdvice

My shortlist by team size

1–5 person marketing team

I’d start with:

• Peec AI — if you mainly need “Are we showing up vs. competitors?”
• Otterly.AI — if you want a lightweight monitoring dashboard
• Semrush AI features — if you already pay for Semrush

Content-led SaaS / B2B marketing team

Consider:

• Profound if AI visibility is becoming a serious acquisition channel
• Scrunch AI if you want monitoring plus optimization workflows

Agency managing multiple brands

Look at:

• Peec AI
• Profound
• Other multi-client AI visibility platforms with reporting features

Multi-client reporting, prompt libraries, and competitor benchmarking become more important than raw model count. AI Visibility Software

The metrics I’d insist on tracking

A good dashboard should show:

• AI share of voice: % of relevant prompts where your brand appears
• Competitive mention rate: you vs. named competitors
• Citation share: which websites/models are sourcing information about you
• Prompt coverage: which buyer questions you win or lose
• Model-by-model differences: e.g., ChatGPT vs. Gemini vs. Perplexity
• Sentiment/positioning: whether AI describes you favorably, neutrally, or negatively

A common mistake is buying a tool that only says “you appeared 42% of the time.” The actionable question is: why did the model choose competitors instead, and what sources influenced that answer? Toolsolved

My practical recommendation for a small team

I’d avoid starting with the most expensive enterprise platform. Run a 60–90 day test:

1. Pick 50–100 buyer prompts.
2. Track your company + 3–5 competitors.
3. Measure weekly:

• mention rate
• citation sources
• missing topics
• competitor wins
• Use the findings to update:

• comparison pages
• FAQs
• product pages
• third-party reviews/listings

For most small marketing teams, Peec AI or Otterly.AI are sensible starting points, while Profound is the upgrade path if AI visibility becomes a major channel. AI Visibility Software AI Visibility Software

If you tell me your company type (B2B SaaS, ecommerce, agency, local business, etc.) and monthly budget, I can narrow this to 2–3 options.

For a small marketing team, I’d shortlist:

• Otterly.AI — easiest low-cost starting point; multi-LLM monitoring and share-of-voice tracking, with plans reported from ~$29/month. Toolsolved Geohats
• Peec AI — better if you need richer competitor benchmarking, multilingual tracking, and more marketing-oriented analytics; reported starting around €85–95/month. Geohats The Best Marketing Tool
• Profound — substantially more enterprise-oriented; deeper analytics and broader coverage, but likely overkill for a small team. Geohats

My starting point: Otterly.AI if your primary goal is simply “What percentage of relevant AI answers mention us vs. competitors?” Peec AI if competitive analysis is equally important.

If your goal is specifically “Are we showing up in AI answers, and does that visibility translate into website traffic?”, I’d shortlist these:

My take

1. Profound — strongest fit if proving business impact is the priority.
It combines AI-answer visibility, citations and competitive analysis with AI crawler activity and AI-traffic measurement, so it's closer to a complete “visibility → traffic” measurement system than a pure rank tracker. Profound Profound

tryprofound.com

2. Ahrefs Brand Radar — particularly compelling if you already use Ahrefs.
It tracks custom buyer prompts across ChatGPT, Gemini, Perplexity, Copilot and Google's AI surfaces, while its AI Analytics identifies which pages receive AI traffic and tracks AI crawler visits. Ahrefs

ahrefs.com

3. OtterlyAI — good dedicated monitoring choice.
It tracks mentions, rankings, sentiment, share of voice and citations across seven major AI engines, and can identify which cited URLs generate traffic. It also provides API/MCP access if you want to feed the data into your own reporting. Otterly Otterly

otterly.ai

4. Peec AI — excellent for understanding why visibility changes.
Its core metrics are visibility, position, sentiment and share of voice, with prompt-level and citation-source analysis. It also exposes API/Looker Studio/MCP integrations, which makes it useful for building your own attribution dashboard. Peec AI Peec AI

peec.ai

The important distinction

There are really two different measurements you want:

AI visibility

• % of relevant prompts where you're mentioned
• position/rank in the answer
• share of voice vs. competitors
• citations and cited URLs
• sentiment / recommendation context
• changes by model, prompt, country and time

Business impact

• AI-referred sessions
• landing pages receiving AI traffic
• engagement/conversions from those sessions
• revenue/pipeline influenced by AI traffic
• AI crawler activity
• change in organic/direct traffic after gaining AI visibility

Most AEO products are much better at the first category than the second. Peec, for example, explicitly distinguishes brand mentions from source citations, while Ahrefs and Profound have more explicit AI-traffic/crawler analytics. Peec AI Ahrefs Profound

So if you're buying specifically to answer “we got featured in ChatGPT—how much incremental traffic/revenue did that generate?”, I'd put Profound and Ahrefs at the top of the evaluation, rather than choosing purely on AI-visibility score quality.

If you tell me your company size, monthly traffic, and whether you're B2B SaaS/ecommerce/media/etc., I can narrow this to 2–3 platforms and compare pricing, integrations, attribution methodology, AI engines, and API capabilities.

otterly.ai

4. Peec AI — excellent for understanding why visibility changes.
Its core metrics are visibility, position, sentiment and share of voice, with prompt-level and citation-source analysis. It also exposes API/Looker Studio/MCP integrations, which makes it useful for building your own attribution dashboard.

If your goal is specifically “Are AI assistants mentioning/citing us, and does that translate into incremental traffic?”, I’d separate the problem into two layers:

1. AI-answer visibility: prompts, mentions, citations, share of voice, competitors, cited URLs.
2. Actual business impact: AI-referred sessions, conversions, pipeline/revenue, and uplift after visibility changes.

The market is still young, and the tools generally measure visibility better than they measure true incremental causality. Marqeable Austin Heaton

Shortlist

For example, Otterly currently tracks mentions, citations, sentiment and share of voice across seven AI engines, including ChatGPT, Perplexity, Gemini, Claude and Google's AI experiences. Otterly Profound is positioned more toward enterprise-grade AI-search analytics and attribution. Lectern PickMySoft

What I'd actually measure

Don't make “AI visibility score” your primary KPI. I'd build a funnel like:

Prompts → AI mention → AI citation → cited URL → AI referral → engaged session → conversion → revenue

That distinction matters because a brand can be mentioned without receiving a link or traffic. Citation tracking is therefore much more useful for your stated goal. Austin Heaton

Then use GA4 (or your product analytics) alongside the AI-visibility platform to measure:

• AI-referred sessions by assistant
• landing pages receiving AI traffic
• engagement/conversion rate of AI visitors
• assisted conversions
• pipeline/revenue from AI referrals
• AI visibility/citation share before vs. after content changes
• competitors gaining/losing citation share
• which specific pages are being cited

My practical recommendation

If you're a larger marketing organization and traffic/pipeline attribution is central, I'd investigate Profound first.

If you're primarily trying to monitor AI answers and build an ongoing GEO/AEO reporting workflow, compare Peec AI and OtterlyAI.

If you already have Semrush or Ahrefs, I'd test their AI features before adding another standalone platform—the benefit is having your conventional SEO and AI-search data in one reporting environment.

One important caveat: no platform can perfectly measure “traffic uplift caused by being featured.” AI responses are dynamic and personalized, and different trackers sample different prompts. The strongest setup is therefore AI visibility tracking + first-party analytics + controlled before/after measurement, rather than relying on a single proprietary visibility score. Austin Heaton Marqeable

If you tell me your company size, monthly website traffic, B2B/B2C, and whether you're primarily interested in ChatGPT vs. all AI search, I can narrow this to 2–3 tools and compare their current pricing/features.

Yes. The category you’re looking for is usually called Generative Engine Optimization (GEO), AI Search Optimization, or AEO/LLM SEO. The goal is specifically to increase the odds that systems such as ChatGPT, Perplexity, Gemini, Claude, and Google AI surfaces mention or cite your content, rather than merely ranking it on Google. Geo Search Console SourceWatch

There are now tools built specifically for this:

• Profound — focused on measuring how brands appear across AI search and identifying citation/visibility opportunities.
• Scrunch AI — tracks AI visibility and helps identify how your content is represented in AI answers.
• Peec AI — monitors prompts and AI-search visibility, particularly useful for seeing which competitors get mentioned.
• Otterly.AI — tracks a defined set of prompts and the citations appearing in AI answers.
• RankScope — focuses on citation rate, share of voice, and changes in AI answers. Its current coverage includes ChatGPT, Google AI Overviews, Perplexity, and Google AI Mode. RankScope Semrush
• Frase — interesting if you specifically want content optimization plus GEO, rather than only monitoring citations. AI Search Visibility
• AMPD — takes a broader approach, analyzing and optimizing visibility across multiple ChatGPT-like systems. Amp'd

The important distinction

There are really two different types of tools:

1. AI visibility trackers — "Ask 500 relevant questions and tell me whether ChatGPT/Perplexity/etc. mentions or cites my company."
2. AI content optimizers — "Look at this article and tell me how to change it so AI systems are more likely to extract, trust, and cite it."

The second category sounds closer to what you're asking for.

And there's an important nuance: there isn't a magic "make ChatGPT cite this page" score. AI citation behavior varies considerably by engine and query. Recent research suggests that highly influential cited pages tend to have strong semantic alignment, clear structure, and easily extractable evidence such as definitions, statistics, comparisons, and procedural information. arXiv

If you're building a content product or evaluating a tool opportunity, there's actually an interesting gap here: most existing products seem much better at measuring AI visibility than at taking an arbitrary article and giving the writer specific, evidence-backed edits designed to increase citation probability.

If you tell me what you're trying to optimize (e.g. your company's blog, ecommerce pages, SaaS documentation, or a content platform you're building), I can recommend the 2–3 tools that are actually closest to that use case.

If by “AI crawler analytics feed” you mean “show me which AI queries/prompts resulted in an AI system using or citing our pages”, there are two related—but importantly different—types of products:

The distinction I'd pay attention to

There are actually three signals you may want in your feed:

1. Query → AI answer → your URL cited

“best accounting software for startups”
→ ChatGPT answer
→ yoursite.com/accounting-software cited

Otterly and Profound are designed for this type of analysis. Otterly explicitly exposes the underlying prompts, responses and cited URLs. help.otterly.ai

2. AI agent → your page

GPT/ChatGPT agent → /accounting-software
Claude agent → /pricing
Perplexity agent → /comparison

This is crawler/agent analytics rather than prompt analytics. Profound has particularly deep functionality here through CDN-level integrations; Otterly's newer Agent Analytics can also show visits and the engines visiting individual cited URLs. www.tryprofound.comhelp.otterly.ai

3. AI query → citation → human visit/conversion

This is the most interesting version if you're trying to prove ROI:

AI query → AI cites your page → user clicks → website session → signup/revenue

Profound specifically describes connecting crawler behavior with GA4 traffic and conversions. www.tryprofound.comhelp.otterly.ai

My shortlist

If your requirement is specifically “give me a feed of the queries that caused our content to be used”, I'd investigate Profound first, then OtterlyAI.

The key question for vendor demos is:

“Can you show me, for an individual URL on my site, the AI prompt/query, the AI engine, the resulting answer, the citation to my URL, and—separately—the crawler/agent request that fetched that URL?”

That's much more precise than asking for an “AI visibility” dashboard. A lot of GEO tools measure whether you're mentioned, but don't necessarily give you the underlying crawl → retrieval → citation chain.

If you tell me roughly your site size, traffic level, and whether you're B2B/B2C, I can narrow this to 2–3 products and compare their actual query-level/crawler-level data, API access, pricing, and integrations.

If you mean “which AI systems are querying, crawling, or fetching our content, and what user queries caused that content to appear in AI answers?”, you’ll want an AI visibility / AEO (Answer Engine Optimization) analytics platform, not just traditional web analytics.

A key distinction:

• Crawler analytics → tells you which AI bots accessed which URLs (GPTBot, ClaudeBot, PerplexityBot, etc.).
• AI answer attribution → tries to tell you which prompts/queries produced answers that cited or used your content.
• True query → content usage mapping is still an emerging capability; no tool has perfect visibility into private ChatGPT/Claude sessions.

Here are the strongest options to evaluate:

For crawler-level feeds specifically (who fetched your pages, when, and which URLs):

• Kitbase — provides AI crawler analytics showing which AI crawlers visit, what they fetch, and page-level crawl activity. Kitbase
• Plumb — focuses on first-party crawler evidence, connecting edge/server logs with AI crawler activity and citation signals. Plumb
• Searchable — combines AI crawls, AI referrals, landing pages, and citation-related analytics. Searchable

What I’d shortlist depending on your goal

“Show me the prompts that cause our content to appear”

Start with:

1. Profound
2. Peec AI
3. Otterly.AI
4. AthenaHQ

These are closer to AI SEO rank tracking.

“Show me AI bots reading our site”

Start with:

1. Kitbase
2. Plumb
3. Searchable

These are closer to server-log observability. Kitbase Plumb

“We need an executive dashboard”

Look for a platform that combines:

• prompt monitoring
• citation tracking
• competitor comparison
• crawler logs
• referral traffic from AI tools

A practical stack many teams are moving toward is:

Cloudflare/server logs → crawler analytics → AI visibility tracker → content optimization workflow

One caution: a crawler hit does not prove that your content was used in an answer. A GPTBot or ClaudeBot fetch may be for indexing, training, evaluation, or retrieval preparation. Tools that claim exact “this query caused this answer to use this URL” should be evaluated carefully. Foglift

If you tell me your stack (enterprise site, SaaS docs, publisher/media, ecommerce, WordPress, Cloudflare, etc.), I can narrow this to the 2–3 tools most likely to fit.

Yes. The category you’re looking for is AI visibility / GEO (Generative Engine Optimization) software. These tools query AI assistants with buyer questions and show where competitors are mentioned or cited while your brand is absent, often down to the specific prompt and source being cited. Semrush Promptwatch

A few relevant options:

• Profound — enterprise-focused monitoring of AI search visibility, competitor presence, and citations.
• Peec AI — tracks brand visibility and competitors across AI search engines.
• OtterlyAI — more lightweight monitoring of mentions, citations, and competitor visibility.
• Semrush AI Visibility — useful if you already use Semrush and want AI visibility alongside conventional SEO. Semrush
• Frase — particularly focused on turning visibility gaps into content changes; it monitors prompts and identifies lost mentions. Frase
• jujuGEO — explicitly identifies questions where an AI engine names a competitor instead of you, then helps draft content intended to close that gap. jujuGEO

The specific capability to look for

If your goal is “Show me every important question where ChatGPT/Perplexity/Gemini answers with Competitor X's content instead of ours”, don't settle for a simple brand-monitoring tool. Look for these features:

1. Prompt discovery — automatically finds questions your customers might ask.
2. Competitor gap detection — identifies prompts where competitors appear and you don't.
3. Citation/source analysis — shows which pages AI is using to support the competitor's answer.
4. Content gap analysis — explains what information is missing from your own content.
5. Multi-engine tracking — ideally ChatGPT, Gemini, Perplexity, Google AI, and Claude.
6. Historical monitoring — lets you see whether the gap is persistent or just one model response.

For example, a useful report would look like:

Prompt: “Best CRM for a 50-person SaaS company”
ChatGPT: Competitor A, Competitor B
You: Not mentioned
Sources cited: G2, Competitor A comparison page, industry publication
Gap: No authoritative page on your site addressing implementation cost for 50-person SaaS teams.

That prompt → competitor → cited source → missing content chain is the key functionality.

If you tell me your company/category and whether you're targeting B2B, B2C, or ecommerce, I can identify the tools that specifically support this workflow and compare their current pricing/features.

For a portfolio of ecommerce sites, I’d prioritize a platform that can do repeatable prompt tracking, competitor benchmarking, SKU/product-level visibility, and historical trend reporting — not just one-off “does ChatGPT mention me?” checks.

The shortlist I’d evaluate:

My recommendation by portfolio size

10+ ecommerce sites, serious AI-search program

Start with Profound. It is the closest match to a “portfolio command center”:

• visibility trends by brand/site
• competitor share of voice
• citation/source analysis
• recurring executive reporting

LLM Visibility Tools Vizby### Agency managing many ecommerce clients

Look hardest at Peec AI:

• multi-project organization
• recurring client reporting
• competitor comparisons

Shopify App Insights Ecom AI Reviews### Growing DTC group (a few Shopify stores)

Consider Otterly.AI or a Shopify-focused tool before paying enterprise prices. Shopify App Insights Ecom AI Reviews

Metrics I would insist on tracking

For ecommerce, a useful long-term dashboard should include:

1. Prompt coverage

• “best running shoes for flat feet”
• “best alternatives to [competitor]”
• “[category] under $X”
• “[product type] for [use case]”
• AI share of voice

• % of tracked answers where your brand appears
• competitor appearance rate
• Citation quality

• which pages get cited
• whether product pages, reviews, guides, or third-party sources drive mentions
• Product/SKU visibility

• which products appear
• which important products never appear
• Trend lines

• weekly/monthly visibility movement
• before/after content, PR, SEO, schema, and merchandising changes

Practical stack I’d use

For a portfolio, I’d usually pair:

• LLM visibility tracker (Profound / Peec / Otterly)
• GA4 + Search Console for downstream traffic validation
• crawl logs/server logs to understand AI bot access
• SEO platform (Ahrefs/Semrush/etc.) for traditional search overlap

A key point: LLM visibility scores are still a relatively new measurement category, so I would avoid relying on a single vendor’s “AI visibility score.” Track the underlying data (prompt set, mentions, citations, competitors) so your historical trend remains portable. github.com imaginaire.co.uk

If you tell me:

• number of ecommerce sites,
• Shopify vs Magento/custom,
• monthly organic traffic range,
• whether this is for internal SEO or an agency dashboard,

I can narrow it to 2–3 options and suggest a tracking architecture.

For a portfolio of ecommerce sites, I’d prioritize a platform that treats LLM visibility as a longitudinal dataset—not just a rank checker.

My shortlist

Recent 2026 comparisons consistently put Profound, Peec and Otterly in the core competitive set, while ecommerce-focused evaluations increasingly emphasize product/shopping prompts rather than generic brand mentions. 1001 SEO Media licheo.com

For your specific use case

If by "long-term trends" you mean something like:

20 ecommerce domains × 100–500 prompts/domain × 12–24 months, with visibility/share-of-voice tracked by model, country, product category and competitor

then I'd put data model and historical retention ahead of UI.

I'd want these dimensions preserved for every observation:

• Domain / brand
• Product/category
• Prompt
• Country/language
• AI engine/model
• Mentioned vs. not mentioned
• Position/order of appearance
• Citation/source URL
• Competitors mentioned
• Sentiment/context
• Date/time
• Prompt category: discovery, comparison, branded, product-specific, "best X", etc.

That lets you answer much more useful questions than "are we visible?": Is Brand A gaining share of AI answers? Which categories are deteriorating? Which competitors are taking mentions? Are citations shifting from our PDPs to retailers/review sites?

For ecommerce specifically, recent evaluations also distinguish product/shopping visibility from generic LLM brand visibility; that's important because a brand being mentioned in an answer isn't necessarily the same as its products being surfaced in a shopping experience. LLM Visibility Tools

My practical choice

If this is a serious multi-brand portfolio: I'd demo Profound and Peec side-by-side, using your actual ecommerce prompts, and make historical data ownership/export/API capabilities a gating criterion.

If you have lots of smaller sites and want inexpensive monitoring: start with Otterly and validate whether its prompt/engine limits are sufficient.

If the portfolio is heavily ecommerce/product-oriented: I'd also test Promptwatch, specifically for shopping/product prompts and whether its historical data model maps cleanly to your portfolio reporting. Current comparisons describe it as particularly oriented toward daily multi-engine ecommerce monitoring and shopping/ads visibility. aisearchtoolrank.com bestgeosoftware.com

One important caveat: I wouldn't choose based on a vendor's "visibility score." For a 12–24 month program, I'd want raw prompt-level observations and an API/export so you can build your own canonical time series. The AI-search measurement market is changing quickly, and platform-level scores can change when the vendor changes its methodology.

If your goal is creating content outlines that increase the chance of being quoted/cited by conversational AI systems (ChatGPT, Gemini, Perplexity, Claude, AI Overviews, etc.), you’re looking for tools in the GEO (Generative Engine Optimization) / AEO (Answer Engine Optimization) category rather than traditional SEO brief tools. These tools usually focus on question targeting, entity coverage, citation patterns, and AI visibility tracking. GeoCopy SitePoint

Here are the strongest options by use case:

Best for AI-quotable content briefs

frase.io

Best for: Solo writers, content teams, SEO strategists

Why it fits:

• Builds research-driven outlines from SERP and competitor analysis
• Finds missing topics/entities competitors cover
• Encourages question-based sections and concise answers (useful for AI retrieval)
• Good bridge between classic SEO and GEO-style formatting

Use it when you want:

“Create an authoritative article outline that covers everything an AI answer engine might need.”

surferseo.com

Best for: Teams already doing SEO at scale

Useful features:

• Content editor and topical coverage analysis
• NLP/entity suggestions
• Competitive content gap analysis

It is more SEO-first than GEO-first, but strong outlines often translate into better AI retrieval because they improve topical completeness. MarqOps

Best for tracking whether AI models actually quote you

tryprofound.com

Best for: Enterprise teams

Strengths:

• Tracks AI visibility and citations
• Helps identify which sources AI systems reference
• Useful for reverse-engineering what kinds of pages get cited CrowdReply MarqOps

This is less of an outline generator and more of a “why are we or competitors being mentioned?” tool.

peec.ai

Best for: Monitoring AI mentions and citations

Useful if your workflow is:

1. Create content
2. Publish
3. Measure whether AI engines start referencing it

GitHub

Best all-in-one GEO workflow tools

writesonic.com

Best for: Teams wanting AI content creation + optimization

Combines:

• Content generation
• SEO optimization
• AI visibility features

Useful if you need a single platform rather than assembling several tools. CrowdReply

semrush.com

Best for: Existing marketing teams

Good fit if you already use it for:

• Keyword research
• Competitor analysis
• Content planning

Its AI visibility features extend a traditional SEO workflow into AI search monitoring. GitHub

My recommended stack for creating “AI-citable” outlines

For most content teams:

1. Research + outline creation

• Frase or Surfer
• AI citation intelligence

• Profound or Peec AI
• Final outline rules

• Start each section with a direct answer
• Use question-style H2s
• Include definitions, comparisons, tables, statistics, and named sources
• Add original data/examples where possible
• Make key claims easy to extract as standalone passages

A good AI-oriented outline usually looks less like a traditional blog outline:

Introduction → history → overview → conclusion

and more like:

What is X?
How does X work?
What are the main types of X?
X vs Y comparison table
Expert examples/data
Common mistakes
FAQ

That structure gives conversational systems more self-contained passages to quote.

If you tell me your niche (SaaS, ecommerce, finance, health, publishing, etc.) and whether you care more about ChatGPT citations, Google AI Overviews, or Perplexity, I can suggest a tighter stack.

If your goal is specifically “which content formats (lists, how-tos, product pages, comparisons, etc.) are AI assistants citing most often?”, you’ll want an AI citation analytics / GEO (Generative Engine Optimization) tool that exposes cited URLs + page types + patterns, not just brand mentions. Linkeddit Scrunch

A few tools worth evaluating:

My recommendation by use case:

• You want a dashboard that tells you “AI assistants cite listicles 3× more than product pages in our category” → look at Profound or Scrunch AI first. They are closer to the raw citation data you need. Scrunch Nick Lafferty
• You want a lightweight experiment → use Otterly.ai or Peec AI, export cited URLs, then classify pages yourself (/blog/, /guides/, /products/, comparison pages, etc.). The Rank Masters Plug

A useful workflow is:

1. Track a fixed set of buyer prompts (e.g., “best X,” “how to choose X,” “X vs Y,” “X pricing”).
2. Export every cited URL from ChatGPT/Perplexity/Gemini/AI Overviews.
3. Classify each citation:

• listicle
• how-to/tutorial
• product page
• comparison page
• glossary/definition
• review/testimonial
• research/data page
• Calculate citation share by format.

Most tools today expose the citation URLs, but few automatically normalize them into “format performance” categories, so the last classification step is often custom. Scrunch

If you’re building a content strategy rather than just monitoring visibility, I’d prioritize a tool with URL-level citation exports over one that only gives an “AI visibility score.” Nick Lafferty

If your goal is specifically “show me which page/content formats AI assistants actually cite”, I’d look at HubSpot’s AEO tooling first. It tracks visibility across answer engines and pairs that with research on citation patterns. Its 2026 research analyzed AI citations across ChatGPT, Gemini, Google AI Overviews, and Perplexity, including format-level differences such as listicles, articles, product pages, comparisons, and how-tos. HubSpot Blog HubSpot Blog

blog.hubspot.com

A useful distinction, though: there isn't one universally dominant format. For example, a 2026 study of 25,337 citations found articles at 23.7%, listicles at 19.6%, and product pages at 16.3%, while noting substantial variation by industry. DeltaV Digital

If you want a more specialized citation-analysis tool, I'd also investigate Peec AI. It is used in AI-search research specifically to analyze what gets cited, and its data underpins Wix Studio's large-scale AI citation research. HubSpot Blog

What I'd want the tool to report:

• Citation share by format: listicle, how-to, comparison, product, category, documentation, etc.
• Breakdown by ChatGPT vs. Gemini vs. Perplexity vs. Google AI
• Citation rate by search intent/buyer stage
• Competitor pages that get cited for the same prompts
• Which formats are underrepresented on your site relative to cited competitors

If you tell me whether you're looking for a SaaS tool to buy or a free research tool/report, I can narrow this to 2–3 concrete options and compare pricing/features.

If your goal is monthly client-facing LLM/GEO visibility reports with polished visual dashboards, I’d shortlist these:

My recommendation: AgencyAnalytics + AI Tracker

If you're a conventional digital/SEO agency and the deliverable is something like:

"Here is your monthly AI visibility report, alongside SEO, traffic, leads, PPC, etc."

I'd look very seriously at AgencyAnalytics.

Its AI Tracker covers ChatGPT, Google AI Overviews, Google AI Mode, Claude, Perplexity and Gemini, and—crucially—puts those metrics into the same dashboards/reports as your other marketing channels. It supports competitor comparisons, visibility trends, citations/sources, custom dashboards, automated reports and white-labeling. AgencyAnalytics

agencyanalytics.com

That makes it particularly good for selling LLM visibility as an additional monthly service rather than creating an entirely separate reporting ecosystem.

If you want a dedicated GEO/LLM reporting product: Peec

Peec AI is probably the one I'd demo first.

Its agency offering specifically supports branded Looker Studio dashboards, where clients can access dashboards without having a Peec login. It also provides CSV/API access for feeding data into BigQuery, Tableau, Power BI, etc. Peec AI

peec.ai

That's attractive if you want to build a dashboard that looks like:

Client → AI Visibility

• AI Share of Voice
• Brand Mention Rate
• Citation Rate
• Competitor Share of Voice
• Visibility by LLM
• Visibility by prompt category
• Sentiment / brand perception
• New citations
• Lost citations
• Top cited pages
• Competitors gaining visibility
• Month-over-month change
• Recommended actions

Then have the system automatically generate a monthly executive summary underneath it.

For enterprise clients: Profound

Profound is more appropriate if your clients are large brands and will expect fairly sophisticated analysis of what AI engines are saying about them.

It is positioned toward enterprise-grade analytics and agency use cases, including deeper prompt/answer analysis. The tradeoff is that it's generally a much heavier investment than the simpler monitoring platforms. AI Search Tools AxiomAI

tryprofound.com

What I'd choose by agency type

• SEO/PPC agency already using AgencyAnalytics: AgencyAnalytics AI Tracker
• Agency building a dedicated GEO/LLM service: Peec AI
• Small agency testing whether clients will pay for LLM visibility: Otterly.ai
• Enterprise GEO consulting: Profound
• Want visibility tracking + content/action workflows: Promptwatch

One important distinction: don't optimize for a dashboard that merely shows an "AI visibility score." For a monthly client service, the valuable report is the movement and explanation: Where did we gain/lose visibility? Which competitors are appearing instead? Which prompts matter? What sources are LLMs citing? What should we do next month? Current agency-focused comparisons similarly emphasize client-ready dashboards, exports, white-labeling and actionable gap analysis rather than just a score. The Rank Masters About Martech

If you tell me how many clients you have (e.g. 10, 50, 100+) and what you want to charge per client/month ($200, $500, $1k+), I can narrow this down to the best 2–3 options and map out the exact monthly dashboard/report I'd build.

agencyanalytics.com

That makes it particularly good for selling LLM visibility as an additional monthly service rather than creating an entirely separate reporting ecosystem.

If you want a dedicated GEO/LLM reporting product: Peec

Peec AI is probably the one I'd demo first.

Its agency offering specifically supports branded Looker Studio dashboards, where clients can access dashboards without having a Peec login. It also provides CSV/API access for feeding data into BigQuery, Tableau, Power BI, etc.

If you mean AI/LLM visibility reporting—e.g. “How often does our client appear in ChatGPT, Perplexity, Gemini, Claude, Google AI results, what sources are cited, and how are competitors performing?”—there are now several agency-focused platforms.

For a typical agency delivering a monthly client report + visual dashboard, I’d shortlist these:

My practical shortlist

1. LLM Pulse — if you want to plug into your existing reporting stack

Its agency offering specifically supports multi-client dashboards, white-labeling, and a Looker Studio connector, which is attractive if your agency already builds monthly reports in Looker Studio. It also lets you blend AI visibility with traditional SEO/PR metrics. LLM Pulse

llmpulse.ai

2. Tower GEO — if you want the reporting product basically ready-made

Tower is explicitly designed around agencies: multi-client workspaces, competitive benchmarking, sentiment/citation tracking, white-label PDFs, branded client dashboards, custom domains and automated monthly reports. Tower GEO

towergeo.com

3. GeoBubbles — if visual reporting is particularly important

Its agency product has a custom report builder, drag-and-drop cards, saved templates, shareable branded links, executive/C-level views, plus LLM citation tracking and geographic visualization. GeoBubbles

geobubbles.com

4. GetIntel — if the report needs to lead naturally into “what should we do?”

Beyond visibility reporting, GetIntel emphasizes identifying gaps and drafting fixes. It also offers a multi-client dashboard, white-label reports and a Looker Studio connector, so it can fit an existing agency reporting process. GetIntel

getintel.ai

What I'd put in the monthly dashboard

Regardless of vendor, I'd avoid making the report just a giant collection of LLM screenshots. A useful client dashboard would have:

• AI Visibility / Share of Voice
• Visibility trend vs. previous month
• Mention rate across tracked prompts
• Citation rate and top citation sources
• Average position/rank where measurable
• Competitor comparison
• Visibility by AI engine
• Visibility by topic / customer intent
• Newly gained and lost citations
• Prompts where competitors appear but the client doesn't
• Actual example AI answers
• Recommended actions for the next month
• “What changed?” executive summary

That last section is particularly important: clients generally care less about an abstract “LLM score” than what changed, why it changed, and what you're doing next.

There are also meaningful differences between white-label PDF reporting and a genuinely white-label client portal. Several vendors market both as “white label,” but they aren't equivalent; a client login on your domain is considerably more valuable if you're trying to productize LLM visibility as a recurring service. SEO for GPT

If I were evaluating them for an agency

I'd run a trial with LLM Pulse, Tower GEO, GeoBubbles, and GetIntel and give each the same 20–30 client prompts. I'd judge them on:

1. Data quality/repeatability of the LLM measurements.
2. How attractive the client dashboard looks without customization.
3. How much manual work it takes to produce the monthly report.
4. Whether clients can access a branded live portal, rather than just receive a PDF.
5. Competitor/citation analysis.
6. Ability to export/API the data into your existing reporting system.
7. Per-client economics at 10, 25, 50 and 100 clients.

The agency market is moving quickly, so I'd put considerably more weight on the actual client-facing workflow and unit economics than on whoever claims to have the highest “AI Visibility Score.” Current agency comparisons likewise emphasize multi-client workspaces, white-label reporting, scalable pricing and data depth as the key differentiators. The Rank Masters Maya

If you tell me roughly how many clients you want to report on (e.g. 10, 50, 200) and whether you want PDF reports, live client dashboards, or both, I can narrow this to the 2–3 platforms that fit and compare their current pricing/features.

2. Tower GEO — if you want the reporting product basically ready-made

Tower is explicitly designed around agencies: multi-client workspaces, competitive benchmarking, sentiment/citation tracking, white-label PDFs, branded client dashboards, custom domains and automated monthly reports. towergeo.com

towergeo.com

3. GeoBubbles — if visual reporting is particularly important

Its agency product has a custom report builder, drag-and-drop cards, saved templates, shareable branded links, executive/C-level views, plus LLM citation tracking and geographic visualization. geobubbles.com

geobubbles.com

4. GetIntel — if the report needs to lead naturally into “what should we do?”

Beyond visibility reporting, GetIntel emphasizes identifying gaps and drafting fixes. It also offers a multi-client dashboard, white-label reports and a Looker Studio connector, so it can fit an existing agency reporting process.