Visibility in AI models isn’t just about your website existing and having good content. It’s just as important whether the models mention it at all, how they describe it, whether they provide accurate information, and what sources they cite instead of your domain. That’s why analyzing what AI says about your website or store should become a regular part of your visibility efforts.
Table of Contents
Step 1-Start with a list of real customer questions
The first step isn’t to open ChatGPT, but to prepare a list of questions your customers actually ask. It’s a good practice to divide them into three groups. The first group consists of brand-related questions-those directly tied to the name of your company or store. The second group includes category-related questions-those about the services, products, or types of solutions you offer. The third group consists of problem-based questions that start with the customer’s need rather than a product or brand name.
With this breakdown, you’ll be able to see whether the AI recognizes your brand, associates you with a specific category, and can recommend your website even when a user doesn’t know your name yet. This is very important because it’s precisely in this third group of questions that the real battle for new traffic and new customers most often takes place.
Step 2 – Test Several Models, Not Just One
Don’t analyze visibility using just one tool. ChatGPT, Google AI Overviews, Perplexity, Gemini, and Claude describe brands differently, use different sources, and respond differently to similar questions. This means your brand may be highly visible in one model but nearly invisible in another.
It’s best to start with the 3–4 most important places where users actually look for information. For many companies and stores, these will be ChatGPT, Google AI Overviews, and Perplexity. If you operate on a broader scale or want a more complete picture, you can also include Gemini and other tools. This ensures your analysis isn’t based on a single instance but on a realistic view of the market.
Step 3-Always Record Responses in an Organized Manner
The biggest mistake is looking at AI responses without documenting the results. After just a few days, you won’t remember exactly what the model said, which sources it cited, or who it compared you to. That’s why it’s a good idea to keep a simple table or spreadsheet from the very beginning.
In this table, record the test date, the model’s name, the question, whether the brand was mentioned, where in the response it appeared, how it was described, what other brands were shown alongside it, and whether the model provided sources. This way, after a few weeks, you’ll be able to see trends rather than just a single impression from one test.
Step 4 – Check Not Only for Presence, but Also for How the Brand Is Described
The mere presence of a brand in the AI’s response isn’t enough. How the model represents you is very important. It may correctly identify the company name but incorrectly describe the offering. It may recommend a store but assign it the wrong product categories. It may also use outdated information that hasn’t been on the website for a long time.
When analyzing the response, pay attention to three things. First-is the description accurate? Second-does the AI highlight your brand’s key strengths and unique selling points? Third, check whether the response contains any inaccuracies that could undermine customer trust. Sometimes, a single piece of incorrect information about prices, returns, or the type of offer can be more damaging than simply omitting the information altogether.
Step 5-Keep track of which sources the AI cites instead of your website
A very valuable part of the analysis begins when you look not only at your own presence but also at the sources the models choose instead of your website. If the AI answers questions about your industry but cites price comparison sites, industry blogs, forums, marketplaces, or competitors’ websites, it means that’s where the context for that category is being established.
This observation yields very practical insights. You may notice that models are more likely to cite a buying guide than a product page, a reviews page than an official product listing, or an extensive FAQ section instead of a store category. This is a signal of what types of content you should develop on your website or where, outside of it, you should strengthen your brand’s presence.
Step 6 – Compare Yourself to the Competition, Not Just to Yourself
Visibility in AI is always relative. Even if your brand appears in the responses, you may still be at a disadvantage if your competitors are mentioned more frequently, higher up in the results, and in a more compelling way. That’s why it’s worth including 3–5 of your most important competitors in your analysis right away.
For each question, note whether the answer includes their names, in what order they appear, and what characteristics are highlighted about them. This will help you see which model attributes are associated with the competition and exactly where you’re falling short. Sometimes the problem isn’t a lack of visibility, but rather that a competitor has secured a stronger mental position for a specific type of question.
Step 7 – Measure a Few Simple Metrics
For the analysis to be meaningful, it’s worth basing it on a few simple numbers. The most important metric is brand presence-that is, the percentage of questions where your company appears in the answer. The second is your share of responses relative to competitors-that is, how often you’re mentioned compared to other brands. The third is citations-that is, how often the AI provides a link to your domain or uses your website as a source.
It’s also worth tracking the quality of the description. You can mark answers as correct, partially correct, or incorrect. This is a very practical metric because it allows you to distinguish between a situation where the brand is visible but described imprecisely and one where it is actually well understood by the AI.
Step 8 – Analyze traffic from AI tools in your analytics
In addition to manually testing responses, it’s worth checking your analytics to see if users are coming to your site from AI tools. In practice, you may see referral sources pointing to domains such as chatgpt.com, perplexity.ai, gemini.google.com, or copilot.microsoft.com. This doesn’t provide a complete picture, but it helps you determine whether visibility in AI is starting to translate into actual visits.
For an online store, it’s worth going a step further and examining not only the sessions themselves but also engagement and conversions. If traffic from AI is becoming more frequent but isn’t leading to sales, it may mean that the models are citing the wrong pages or answering questions too generally. In this situation, you need to refine your content to better support the purchasing decision.
Step 9 – Look for errors on the website that can be corrected
AI analysis only makes sense if it leads to specific changes. If the model describes your offerings incorrectly, check whether your homepage and services page include a clear, simple description of your business. If AI doesn’t recommend your store in response to purchase-related queries, check whether your category pages, FAQs, and guides are sufficiently detailed. If the source of the citation is a competitor, compare the structure of their content to yours.
Very often, visibility issues with AI stem not from a lack of indexing, but from a lack of a clear message. Models better understand brands that clearly explain who they are, who they serve, what they offer, and what sets them apart. Analyzing AI responses helps you identify areas where this message is too weak or vague.
Step 10 – Repeat the tests regularly, not just once
What the AI says about your site today may look different in a month. Models, citation sources, and response logic are constantly changing, so a one-time audit quickly becomes outdated. It’s best to run shorter tests regularly-for example, once a week or once a month-always using the same set of questions.
This way, you’ll see trends rather than just isolated incidents. You might notice that after expanding your FAQs, your brand appears more frequently in the answers; that after updating your product descriptions, the AI better understands your offerings; or that your competitors have started to dominate a new set of questions. This regularity provides a real advantage because it allows you to react before a drop in visibility impacts your business results.
A Simple AI Analysis Template for Your Website and Online Store
Below is a simple layout that you can use in a spreadsheet or monitoring tool:
Question
AI Model
Test Date
Was the brand mentioned? - Yes or No
Position in the response - beginning, middle, end
How was the brand described?
Was the description accurate? - Yes, partially, no
Was a link to your website included? - Yes or No
What sources were cited?
Which competing brands appeared in the response?
Conclusions and Areas for ImprovementThis simple template is enough to move from randomly checking AI responses to a real, structured analysis. Even without paid tools, it allows you to quickly see whether the models understand your brand and whether your website is a valuable source of knowledge for them.