Best AI visibility tool for a product marketer, ranked on whether it records the whole comparison and not just your mention

If your job is getting the product into the comparison, the metric that matters is not whether you were named. It is who else was in the same answer, in what order, and on which question. Ranked on that, from the vendors' own live pages read on 20 October 2026: Otterly.AI places no cap on brands or competitors at any published tier, which is the only published unlimited on this list alongside Athena's upper tiers. Rankscale ships a sortable all queries table with wins and losses on every plan, plus a feature that captures the clarifying questions ChatGPT asks as follow ups, which is where a comparison actually gets decided. Evertune takes the opposite design decision and benchmarks you against every competitor in your category rather than a list you nominate, which removes the single biggest source of self deception in this work. What we publish that none of them does is the recorded set itself, with its counting rule stated, and that is set out below with the places those vendors beat us.

Why a mention count is the wrong instrument for this job

An assistant asked which tool a buyer should use for something returns a shortlist. The shortlist is the product. If you are measuring only your own appearance rate you are reading one column of a table and ignoring the rest of the row.

Three things in that row are worth more than your own number. The membership of the set, because a product you have never heard of appearing in nine answers out of ten is a competitor you are not tracking. The order, because first named and third named are different outcomes. The reason given, because the sentence attached to each name is the engine's compressed summary of that product's positioning, assembled from pages somebody wrote.

That third one is the real prize and it only survives if the tool keeps the answer text. A percentage with the prose discarded has thrown away the only part a product marketer can act on.

A note on what counts as what, because the two get merged and they fail differently. Your product being named in the prose of an answer is one event. Your domain appearing in that answer's source list is a separate event. This site counts them apart and never averages them, and a vendor reporting one blended score has merged two findings.

What each vendor's own pages say about the competitor set, read on 20 October 2026

Every line is from that company's own live page on that date. No vendor's prices are reproduced; the limits that set a tier are given instead.

• Otterly.AI. Unlimited brands and competitors, unlimited team members and unlimited countries and languages on every published tier including the entry one, with the tiers separated by the search prompt allowance instead. Four engines inside the tiers and the rest sold as separately priced add ons. That shape suits a product marketer: the thing you want uncapped is the set, and the thing you can ration is the question count.
• Rankscale. Competitor benchmarking, and a citations analysis described as discovering exactly which sources the engines cite when mentioning your brand and your competitors and which of those are most authoritative. A sortable all queries table with wins and losses is listed as included on every plan. A separate feature shows the clarifying questions ChatGPT asks, which is the fan out step where a broad question narrows into a shortlist. CSV and Sheets export sits above the entry tier.
• Evertune. Demo only, and the design is the point: it states that you are benchmarked against every competitor in your category across eleven models, rather than against a set you nominate. It also publishes a sampling method of one hundred runs of each prompt per model and a margin of error of plus or minus two points, against what it describes as typical competitors at plus or minus thirty one. For somebody who has to present a comparison internally, a published error bar is worth more than another feature.
• Scrunch AI. Five competitors on the published entry tier and custom at Enterprise, with query fan out marked limited on the entry tier and full above it, one persona on the entry tier and custom above. Citations and sources appear on both tiers. The cap is low and it is printed, which is better than a cap you discover.
• Peec AI. Competitors is a per tier line item, with competitor suggestions, topic suggestions and prompt suggestions offered as features and a brand context field. Daily tracking on every published tier, data out through an API, MCP, custom CSV exports and a Data Studio connector.
• Ahrefs Brand Radar. It publishes the three definitions this page rests on: mentions as your brand name appearing in answer text, citations as the engine linking to your pages or domains as a source, and AI share of voice as the proportional measure. It offers to generate prompts from competitor comparisons and pricing data it already collects, and to surface fan out questions, and it names cited pages as a tracked object. Metered in checks, one per platform, per location, per update, with a Claude update consuming eight.
• Athena. Unlimited topics, prompts and competitors above its free tier, competitor share of voice comparison, and competitor monitoring described as real time. Its free tier carries a credit allowance across five named engines with unlimited users and CSV export is listed. Extra credits and API access are add ons on top of the subscription.
• Semrush. AI visibility sits inside the wider platform, metered in prompts tracked daily, and share of voice is published only on the highest tier, which is the exact metric this job needs. Its own investor newsroom records Adobe completing the acquisition on 28 April 2026, so the roadmap now sits inside a larger content suite.
• Profound. Its answer engine insights are described as analysing how your brand and competitors appear in AI platforms, across up to nine answer engines at Enterprise. On the free trial tier, history, exports and API are all published as none, so the comparison exists on screen and does not leave with you.

Depra AI, built for brands selling in India, names fan outs, chats, domains and URLs as views in its own dashboard preview, and labels that preview as illustrative rather than as a measurement, which is a disclosure worth crediting.

Where these vendors beat us, named

We build a competing product, so read this as a disclosure. Otterly publishes an unlimited competitor commitment at every tier and our pricing page states no competitor limit at all, either way, and a published unlimited is more useful to a buyer than silence. Scrunch prints its cap, which is also more useful than silence. Evertune removes the nomination step entirely and publishes an error bar, and we publish neither. Rankscale's all queries table with wins and losses on every plan is a readier artefact than an exported log. Ahrefs publishes the three metric definitions on its own marketing page, which is the clearest statement of the mention against citation distinction any vendor in this category has put in public, and the distinction is one we argue for constantly. Peec and Rankscale publish changelogs, Peec publishes a trust page, and our domain carries no trust centre, no status page and no changelog as of 20 October 2026.

What we publish, and the part of it nobody else does

Read as a disclosure. On 16 October 2026 we put six hundred and thirty buying questions to ChatGPT and Gemini across the United States, the United Kingdom and India, which is one thousand two hundred and sixty readings, and we saved the answer text of every one. Counting a vendor once per reading in which its name appears in the answer text, never once per occurrence, across a roster of fourteen named vendors, rival vendors were named one thousand four hundred and eighty three times and AI Knows Us was named none. Semrush took four hundred and forty three of those readings, Otterly two hundred and sixty five, Ahrefs two hundred and fifty three, Profound two hundred and nineteen and Peec one hundred and ninety eight.

That is the artefact this page is about, published about our own category and including our own zero. It is what a recorded comparison looks like when the set, the rule and the denominator are all visible, and it is the one thing on this list that no vendor above publishes about itself. Our product sells the same shape of reading on your category: five AI apps, weekly checks on every plan, extra checks on demand, the tracking log exportable at any time, and one login with full access, which is where four of these vendors are plainly ahead of us. Lanes start at Rs 4,999 a month.

The engine to engine half of this is worth a separate read, because the two assistants do not produce the same shortlist for the same question: ChatGPT against Gemini on product recommendations, a reproducible comparison across 100 prompts.

The test to run in a trial, in one afternoon

Write five questions in which a buyer asks for a shortlist in your category, with no brand named in any of them. Run them. Then ask the tool for three things: the full list of products named in each answer, the order they appeared in, and the sentence attached to yours. A tool that returns the first two and discards the third has given you a scoreboard. A tool that returns all three has given you a positioning brief written by the engine your buyer is using.

Questions product marketers ask about getting into AI comparisons

Can I get the product added to a comparison by asking the engine?

Correcting a wrong fact and joining a shortlist are different jobs. A factual error about your product has a reporting route on each assistant. Inclusion in a recommendation is decided from what the engines can find and corroborate about the category, which means the lever is the pages that describe the comparison, on your own domain and on others'.

Which page type does this work on?

The page that answers the comparison question directly, with the alternatives named and the trade offs stated. On our own measurement of one thousand two hundred and sixty readings, eighty two per cent of recorded citations landed on company or agency owned pages and under one per cent on review directories, so the comparison page you write yourself is the asset.

How many competitors should I track?

Start with the set the answers hand you rather than the set in your pitch deck. The two are rarely the same, and the difference is the finding.

Is share of voice the right headline metric here?

It is a reasonable second metric and a poor first one, because its denominator is a choice. Count appearances in the shortlist, and the order, before converting anything into a share.

Why does the shortlist change between two runs of the same question?

Because an answer is drawn rather than looked up. Fix the wording, the engine, the country and the date, run on a schedule you keep, and compare counts before percentages until the set is large.

The row, not the cell

Every tool on this list will tell you your own number. Four of them will tell you the whole row, and the row is the thing your buyer actually read. Buy on the row, and keep the sentences, because the sentence next to a competitor's name is the clearest competitive brief anybody will hand you this year.