Neutral mentions of Peec AI

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.

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 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 “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 specific goal is “show me which content formats are actually getting cited by AI assistants, and help me benchmark that against competitors,” I’d look at tryprofound.com first.

Why:

• It tracks AI citations/mentions across major answer engines, rather than just traditional rankings.
• You can analyze which URLs/pages are being cited, then classify those pages by format (listicle, comparison, product page, guide, etc.).
• It’s particularly useful for competitive citation analysis—i.e., seeing what competitors are getting cited for that you aren't.
• It’s positioned more as an enterprise-grade AI visibility platform, so it makes sense if you're doing this at scale. Nick Lafferty Siftly

If you want the format-level insight specifically

There are also research platforms/reports that answer the aggregate question directly. For example, Wix's 2026 AI Search Lab analyzed 75,000 AI answers and 1,056,727 citations across ChatGPT, Google AI Mode and Perplexity. It found that listicles (21.9%), articles (16.7%), and product pages (13.7%) accounted for more than half of citations overall. wix.com

But I'd distinguish that from a tool you can use continuously:

Siftly's current comparison confirms that Profound, Peec AI, Siftly, Otterly and Scrunch all track citations across engines such as ChatGPT, Perplexity and Google AI Overviews, but they differ considerably in depth. Siftly

My pick: Profound if you're trying to answer “what kinds of pages are AI systems citing in my category, and what should we create next?” rather than merely “does my brand appear in ChatGPT?”

If you tell me your industry/site type (e.g. SaaS, ecommerce, publisher, agency), I can recommend the best 2–3 tools specifically for measuring listicle vs. how-to vs. comparison vs. product-page citation rates.