AI Visibility Tracker: Best Picks and How to Track Rank

You can't track a fixed rank in ChatGPT: it writes a fresh answer every time. You can track how often your brand is named across a fixed set of buyer prompts, run repeatedly. That is what a "ChatGPT rank tracker", "LLM rank tracker", AI brand monitoring tool or AI visibility tracker automates: the same prompts on a schedule, so you get a line instead of a one-off checker's single dot.

This guide is based on public documentation as of October 2026; we have not tested any of these products hands-on. Best fit on paper:

• Small team: Peec AI Starter or Trakkr Growth; Otterly.AI Lite as a cheap weekly alarm.
• Agency: Peec AI's agency plans or Trakkr Scale.
• Enterprise: Profound, by quote.
• Google AI Overviews: Search Console's free report, then SE Ranking.
• Free or DIY: a 30-prompt spreadsheet plus Google's and Microsoft's free reports.

Can you track your rank in ChatGPT?

Not as a position. ChatGPT has no results page, so there is no rank to read, only a distribution: the share of runs that name your brand. A tracker that reports one tidy rank is showing you a single draw from that distribution.

How wide? In SparkToro and Gumshoe's study (January 2026; 600 volunteers, 12 prompts, 2,961 runs on ChatGPT, Claude and Google AI; not peer-reviewed), the chance that any two responses from ChatGPT or Google AI named the same brands was under 1 in 100, and the same brands in the same order about 1 in 1,000. The authors conclude that a single "ranking position" is unreliable while visibility across many runs is meaningful.

Presence also beats position. In AEOeye's audit records (127 audits of 27 brands), brands were named in 157 of 892 answers (17.6%), and when named in a ranked list (147 cases) they came first 71.4% of the time. Being named at all is the hard part. The sample is small and self-selected, so test the pattern on your prompts; the aggregates are public.

Which AI visibility tracker fits your team?

Buy the cheapest plan that runs your 30 prompts on the engines your buyers use, not the one with the most engine logos. Entry plans from Peec AI, Otterly.AI and Trakkr all work out to roughly $95 to $100 per 50 prompts a month, so the real differences are engines per prompt, seats and client projects.

A prompt is not a standard unit: Trakkr's 50 run on eight models, Peec AI's on three, so near-equal prices buy different work. Peec AI's figures come from its plan summary dated July 2026 (its pricing page showed no amounts to our fetch); Profound's page listed no self-serve price. More detail: our roundup, buyer's guide and Peec AI review.

What should you track instead of rank?

Track five things per prompt: whether you are named, where, whether your domain is cited, how you are framed, and who else appears. Roll them up into mention rate and AI share of voice; Measuring AI visibility has the formulas and sample sizes.

• Mention rate: answers naming you ÷ answers sampled (17.6% in our records).
• AI share of voice: your mentions ÷ all brand mentions in the same answers. Wikipedia ties share of voice to media spend; classic ad, social and rank tools count spend, posts and positions, not AI answers, so you measure it by asking engines.
• Citation: answers that link your domain, which is not the same as being named (AI citation tracking).
• Framing and accuracy: a repeated old price is a loss, not a win. Yet 144 of our 157 recorded mentions were positive, so invisibility is the usual problem.

Web analytics cannot stand in for a tracker: Pew found users clicked a link inside a Google AI summary in just 1% of visits to pages with one (March 2025 data, 900 US adults), so most exposure there never shows up as a visit.

What should a good tracker show you?

A good tracker lets you freeze your own prompts, repeats each one, shows the raw answer, separates mentions from citations and puts competitors in the same view. If it can't, you are buying a score whose denominator you can't inspect. Ask before you pay:

1. Prompt control. Can you load and lock your own unbranded prompts? Rotating templates break your trend line, and brand-name prompts only test whether engines recognize you.
2. Engines and modes. Which engines, app or API, search on or off? In OpenAI's API search is an optional tool, so a run without it shows memory, not live retrieval.
3. Repeats. How many runs before a rate appears? Evertune says it samples each prompt 100 times across every AI model; SparkToro's team suggests dozens to hundreds. Daily runs are extra samples, not a daily verdict: read weekly averages.
4. Raw answers. A score of 68 can't tell a recommendation from a warning; the full text can.
5. Citations. Which URLs are cited, answer by answer? A stale page cited repeatedly is a fixable gap.
6. Competitors. Same prompts, same view, so share of voice has a fixed denominator.
7. Export and history. Can you leave with your raw answers? Switching tools resets your baseline.

How do you track AI visibility for free?

Use a spreadsheet and 30 fixed unbranded buyer prompts: run your 10 to 15 highest-stakes prompts weekly as an alarm (it catches drops, not trends) and all 30 monthly, three runs each. Then add Google's and Microsoft's free reports for what they see on your own site.

1. Write 30 prompts in four groups: category ("best X for Y"), problem-led, comparison ("A vs B") and a few brand-name checks for accuracy. Mine sales calls, support tickets and Search Console queries. Freeze the wording: in Peec AI's analysis of 37,804 responses (Search Engine Journal), ranking-style prompts lifted average brand visibility by about 20%.
2. Run each prompt three times in a fresh chat on ChatGPT and your buyers' favorite engine. Log one row per answer: date, engine, prompt, named, position, linked, competitors, framing, raw text, and whether search ran.
3. Compute per engine, never pooled: mention rate, share of voice against a fixed competitor set, citation rate. Read monthly: at thirty prompts a 20% rate and a 30% rate overlap (intervals), and a model release means a new baseline.
4. Act, then re-run. Where you are absent or misdescribed, fix the page that should answer the prompt.

Add two free first-party reports. Google's Generative AI performance report in Search Console gives impressions in AI Overviews and AI Mode by page, country, device and date (all sites since 31 August 2026; no query or click data listed). Microsoft's AI Performance report in Bing Webmaster Tools (public preview) counts citations in Copilot, Bing's AI summaries and select partner integrations, plus the phrases the AI used to retrieve your pages, but no clicks or impressions. Neither names ChatGPT, Claude, Gemini or Perplexity, so they supplement the spreadsheet.

Do you need continuous tracking or a one-off audit?

Start with a one-off audit; add a tracker only when you will act on what it shows. An audit gives you the baseline a tracker needs; without one you are watching numbers you can't interpret. Move up when you need daily runs across hundreds of prompts, or several brands or markets outgrow a spreadsheet.

Our stance: the trend over a fixed prompt set beats any single score, and the surest way to ruin it is changing prompts, engines or vendor mid-series; if you must, start a new series.

Where AEOeye fits: the free audit asks three unbranded buyer questions on ChatGPT and shows the full answers; the $29 one-time report covers ten questions across five engines. Both are baselines, not scheduled trackers; our free checker guide lists no-cost starting points.