If you want to know whether ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews actually mention your brand, you need a tool that watches all of them at once and reports it in plain numbers. This guide compares ten of them on model coverage, refresh rate, prompt volume and price, then shows you how to audit your own brand in an afternoon.

You already feel the shift. People ask ChatGPT or Perplexity a question, get a confident answer, and never click a single link. If your brand is not inside that answer, you are invisible to a growing slice of your market, and a rank-tracking dashboard will not warn you.

Analytics dashboard showing colorful data visualization charts and KPI metrics on a computer screen

Why did AI visibility become a budget line in 2026?

The math changed. Google AI Overviews now appear on roughly 48% of tracked queries, up from about 31% a year earlier, according to BrightEdge data compiled by Stackmatix. When an answer sits above the links, plenty of searches end without a click at all.

That is the part finance teams finally noticed. A page can rank first and still lose the click to an AI summary that quotes three other brands. So the question stopped being "where do we rank" and became "does the machine mention us."

Tracking that answer takes tooling, because you cannot check every model by hand every day. A category that barely existed two years ago now has funded startups, suite add-ons from Semrush and Ahrefs, and free graders from companies like HubSpot. When a line item has this many vendors chasing it, it has graduated from experiment to budget.

What do AI visibility tools actually measure?

Good tools go past a single vanity number. They watch four signals across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews:

  • Mentions. How often a model names your brand in an answer, with or without a link.
  • Citations. How often it links to your site as a source, which is the version that sends traffic.
  • Share of voice. Your mentions as a percentage of the total for a topic, measured against named competitors.
  • Sentiment. Whether the model describes you in positive, neutral or negative terms.

The mechanics are simple once you see them. The tool sends a set of prompts to each model on a schedule, reads the answers, and records who got named. Run enough prompts often enough and you get a trend line instead of a lucky screenshot.

Prompt volume and refresh rate are where cheap and serious tools separate. A tool that runs 15 prompts weekly gives you a blurry photo. One that runs a few hundred prompts daily gives you something you can actually manage against. If you want the deeper mechanics, this companion piece on how AI-powered SEO tools work under the hood walks through the plumbing.

Which ten AI visibility tools are worth comparing?

Here is the current field, grouped by what they are built for. Prices are the publicly listed starting points and move up quickly with more engines and prompts.

Dedicated AI visibility platforms

  1. Profound. Tracks ChatGPT, Perplexity, Gemini, Claude and AI Overviews with daily refresh. The category's best-funded player and the most enterprise-shaped. Entry tiers start around 99 dollars a month, with growth plans in the mid hundreds and enterprise pricing well beyond that.
  2. Peec AI. Daily tracking across the major models with a strong sentiment and prompt-stability angle for spotting real trends. Starts in the low hundreds per month.
  3. Otterly.AI. The friendliest budget entry, with a lite tier around 29 dollars a month, plus a public API and MCP server for teams that want to pull data into their own stack. Gemini and AI Mode are paid add-ons.
  4. Scrunch AI. Leans into content diagnostics, telling you why a model cites a competitor and not you. Positioned in the mid-market range.
  5. Goodie AI. The widest coverage on this list, watching close to a dozen engines including Copilot, Meta AI, Grok and DeepSeek, with a commerce and attribution focus. Pricing is custom.

SEO suites with AI visibility add-ons

  1. Semrush AI Visibility Toolkit. Bolts a daily 0 to 100 AI Visibility Score onto an existing Semrush plan for about 99 dollars a month on top. Handy if you already live in Semrush.
  2. Ahrefs Brand Radar. Built on one of the largest prompt indexes in the category, so prompt discovery is a real strength. Realistic cost lands in the several-hundred-dollars-a-month range once you add platforms.
  3. SE Ranking AI Visibility. A budget all-in-one that folds AIO, ChatGPT and Perplexity tracking into its wider subscription. Less depth, lower cost.

Diagnostic and specialist tools

  1. HubSpot AI Search Grader. Free. A one-off grade across the major engines, ideal for a first snapshot and for getting a skeptical boss to care.
  2. Nightwatch AI add-on. Pairs classic rank tracking with AI visibility across four models and offers geo-level granularity, which suits local and multi-location brands. Starts around 79 euros a month.

Tracking versus fixing: which tools report and which change the answer?

Here is the split that catches most buyers. Almost every tool above is a measurement tool. It shows you the scoreboard in beautiful detail and leaves the playing to you.

A dashboard telling you that Perplexity keeps citing a competitor instead of you is useful once. After that, it is just a recurring reminder of a problem you still have to fix by writing and publishing better source material.

Fixing means producing content the models want to quote, on your own domain, consistently, on the topics where you are losing. A few platforms now attach a content-generation layer to their tracking, and a purpose-built engine like Bunzy sits on the fixing side: it learns your brand voice and winnable keywords, then writes and publishes structured, citation-friendly articles to your domain on a schedule, complete with Key Takeaways and FAQ blocks that answer engines like to lift. What closes the gap is publishing against it, week after week, so the models have fresh reasons to name you.

How do you run a first AI visibility audit in an afternoon?

You do not need a paid tool to start. You need 20 good prompts and two hours.

  1. List 20 buyer prompts. Write the actual questions a customer would type, like "best CRM for a two-person agency" or "how to fix a leaky tap." Mix category questions, comparison questions and problem questions.
  2. Ask every model by hand. Paste each prompt into ChatGPT, Claude, Perplexity, Gemini and a plain Google search that triggers an AI Overview. Note whether your brand appears and whether it is cited with a link.
  3. Score it simply. Tally mentions and citations per model. That percentage is your starting share of voice. Screenshot the misses.
  4. Find the pattern. Look at the pages the models did cite. They are almost always clear, well-structured, recently published and directly on-topic. That is your content brief.
  5. Grade and benchmark. Run a free tool like HubSpot's AI Search Grader for a second opinion, then decide whether the gap justifies a paid tracker.

Do this once and the whole category stops feeling abstract. You now know exactly which prompts you lose and roughly why.

What does good AI visibility look like by company size?

There is no single target, because share of voice depends on how crowded your category is. Judge yourself against your size and your competitors, not a made-up benchmark.

  • Solo founders and local businesses. Getting mentioned at all for your top five buyer prompts is a real win. Aim for consistent citations on long-tail, specific questions where big brands are not fighting.
  • Small and mid-size teams. Target a measurable, rising share of voice against your three named competitors on your core money topics, and treat sentiment as a second priority.
  • Enterprise brands. You should expect to lead share of voice in your category and be watching sentiment and citation quality, not just presence.

The one benchmark that applies to everyone is direction. A slowly climbing line beats a high number that is quietly sliding. That is the honest lesson from the last decade of search, and it holds here too: the teams that win are the ones that keep publishing after the novelty wears off, long after the one-off audit is forgotten. The bottleneck was never whether you could write a good page. It was whether you would still be shipping them in month six.

If you want a realistic on-ramp for that kind of steady output, the 0 to 30 posts a month sprint plan lays out a schedule you can actually keep.

Start with the free afternoon audit this week. Once you know which prompts you are losing, pick one tracking tool and one way to keep publishing against the gap, and let the line climb.