# AI brand monitoring: how to track what AI assistants say about you Source: https://outname.now/guides/ai-brand-monitoring Updated: 2026-10-07 By: Outnamed (https://outname.now) AI brand monitoring is the practice of asking AI assistants the questions your buyers ask, many times over, and recording whether your company is named, how it is described and who appears next to it. One answer proves little because assistants rarely give the same list twice, so you track rates across repeated runs, not single screenshots. ## Key points - AI brand monitoring measures what assistants say in their answers, which is different from tracking posts or mentions on social media. - Track four things: whether you are named, how you are described, which competitors appear, and which sources the assistant cites. - Ask each question many times and on each assistant, because one answer is a sample of one. - Wrong or outdated descriptions are usually traceable to a source you can fix or update. - Monitoring only measures. It cannot make an assistant name you. ## What is AI brand monitoring? AI brand monitoring is the routine check of what AI assistants such as ChatGPT, Claude, Gemini and Perplexity say when someone asks about your category, your competitors or your company by name. The thing you watch is the assistant's answer, not posts or articles about you. It matters because buyers now use these tools to build shortlists. The G2 Buyer Behavior Report, June 2026 (1,000+ software buyers), found that 8 in 10 software buyers used an AI chatbot to find recommendations in the last two years. In the same report, 37% say chatbots shape their shortlist most, level with review sites at 38%. If you never look at those answers, you do not know whether a buyer sees you, a competitor, or a description of your product that is two years out of date. ## What should you track? Tracking whether your name appears is the start, not the whole job. An answer can name you and still describe you wrongly, or name you only as an alternative to a competitor. Record these five things for every question you test. - Mention: whether your company is named at all, and how early in the answer. - Description: what the assistant says you do, who you are for and what you cost, checked against your own facts. - Competitors: which other companies are named in the same answer. - Sources: which pages the assistant cites or appears to draw on, when it shows them. - Context: whether the tone is a recommendation, a neutral listing or a warning. ## How do you run a basic check by hand? You can start today with a spreadsheet and an hour. The aim is a small, repeatable record, not a perfect one. 1. Write ten to twenty questions a buyer would really type, such as the best option for a given use case, a comparison of you and a named competitor, and a question about your company by name. 2. Pick the assistants to test. Test each one separately, since they do not answer alike. 3. Ask each question several times in a fresh conversation, with web search on if the assistant offers it. Fresh conversations stop earlier answers from steering later ones. 4. For every answer, log the date, assistant, question, whether you were named, the description used and the other companies named. 5. Copy any sources the assistant shows. Note any claim about you that is wrong. 6. Count. For each question and assistant, work out in how many runs you were named. ## Why is one screenshot not monitoring? Assistants build each answer fresh. Ask the same question twice and the list of companies can change, even within the same hour. A single answer where you appear, or do not appear, is one draw from a spread of possible answers. Several other things also vary. Answers differ between assistants. They can differ with web search on or off. The consumer app and the programming interface of the same assistant may not behave the same way, and how much your location or chat history matters is not public. Assistants are also updated over time, so a result from last quarter may not hold today. That is why the useful number is a rate: the share of runs in which you are named. Example with made-up numbers: if Your company is named in 6 of 30 runs and Competitor B in 21 of 30, you have a gap you can describe and track. Neither the 6 nor the 21 tells you what the next answer will be. ## How do you read the results? Start with the questions where you are named rarely or never, and check which companies fill the space. Then read the sources. If an assistant describes you wrongly, there is usually a page behind it: an old review, a directory listing, a forum thread or your own outdated page. Assistants do not disclose exactly how they pick sources, so treat this as a lead, not proof. Then sort what you find into three kinds of problem. - Missing: no page of yours answers the question directly, so there is nothing clear to draw on. - Wrong: a claim about you is outdated or incorrect, and a source you can fix or update carries it. - Weak: you are named, but reviews or community threads on Google reviews, G2, Capterra, Trustpilot, Yelp or Reddit paint a mixed picture. ## Which metrics belong in a monthly report? Keep the report short enough that someone reads it. The table shows a workable set. **A basic monthly set of AI brand monitoring metrics** | Metric | What it tells you | How to record it | | --- | --- | --- | | Mention rate | How often you are named for a buying question | Runs naming you divided by total runs, per assistant | | Competitor share | Who is named when you are not | Count each competitor's mentions per question | | Description accuracy | Whether the assistant states your facts correctly | List each wrong or outdated claim and its likely source | | Cited sources | Which pages shape the answers | Copy shown sources and tally repeat domains | ## How often should you monitor, and where does Outnamed fit? Monthly is a sensible rhythm for most companies. Answers move over time, so a single check goes stale, but daily checks mostly record noise. Re-run the same questions each time so the months can be compared, and add new questions when your buyers start asking different ones. Outnamed does this measurement for you: it asks each buying question thirty times across ChatGPT, Claude, Gemini and Perplexity through their official programming interfaces with web search on, and counts who is named. It then writes answer pages for your site from your own facts, which you approve before they go live. Nobody can promise a mention, because the assistants decide. ## Questions people also ask ### Is AI brand monitoring the same as an AI visibility tool? A tool is one way to do the monitoring, not a different thing. What matters is the method behind it: how many times each question is asked, on which assistants, and whether web search is on. Check those before you rely on any number. ### Can I just ask an assistant what it thinks of my company? You can, and it is a fair first check of how you are described. But it is one answer, and a question that names your company is easier than one where a buyer asks for options without naming anyone. Test both kinds, and repeat them. ### Do I need to monitor every assistant? Start with the ones your buyers are likely to use, and keep each assistant's results separate. They draw on different sources and can name different companies for the same question. Averaging them hides those differences. ### How many times should I ask each question? More runs give a steadier rate. There is no public number that is right for every case. Outnamed asks each question thirty times. By hand, even a handful of runs per question shows whether your result is stable or swings. ### Can I get a wrong claim about my company removed? You cannot edit an assistant's answer directly. What you can do is correct the sources behind it: update your own pages, fix listings, and respond to or correct outdated reviews. Whether and when an assistant's answer changes is not something anyone can promise. ### Will monitoring get my company mentioned more often? No. Monitoring shows where you stand and what to fix first. Changes in how often you are named come from the work you do afterward, and even then the assistants decide. Sources for the figures on this page: G2 Buyer Behavior Report, June 2026 (1,000+ software buyers); Ahrefs, own traffic over 30 days. These are their figures, not a forecast for your company.