It’s a regular workday, and the head of operations at a growing logistics company has finally set aside an hour to find a new IT provider. Instead of opening ten browser tabs, she types her question into an AI assistant, adding a few details about her team size and budget. A few seconds later, the answer recommends one of your competitors, noting their experience with similar companies and pointing to their strong client reviews. By the time she closes her laptop, she already has a name to call, and your company never came up.<\/p>\n\n\n\n
What makes this moment so easy to miss is that it leaves no trace<\/strong>. There’s no lost visit in your analytics and no dip in your sales reports because she never reached your site in the first place. That’s why more marketing teams are turning to AI competitor analysis, which shows them which companies AI recommends to their buyers, why it selects them, and what it would take to earn a place in those answers.<\/p>\n\n\n\n Choosing the questions is the step many teams rush through, even though it ends up shaping almost everything the analysis tells you. AI only responds to what it’s asked, and buyers tend to write to it the way they’d explain their situation to a consultant, with details about their industry, team size, or budget. Each of those details changes which companies come up, which is why broad questions usually return broad answers that say very little about your market.<\/p>\n\n\n\n Your sales team is the best source for better questions<\/strong> because they hear how buyers describe their problems long before a deal closes. Questions like “Do you work with companies our size?” or “How is this different from what we use now?” reveal the criteria buyers use to decide. <\/p>\n\n\n\n Ten to fifteen questions are usually sufficient, provided they cover both the early stage (when buyers are still defining the problem) and the later stage (when they are comparing providers). Run each question a few times in more than one AI assistant, starting a new conversation each time. Answers shift from one session to the next, and the repeating patterns are the ones worth acting on.<\/strong><\/p>\n\n\n\n As you run each question, log the answers in a simple spreadsheet, noting the question, the companies AI recommends, and their order of appearance. After a dozen questions, the patterns become undeniable. Certain competitors appear in almost every answer, while some questions never include you at all.<\/p>\n\n\n\n The names are just the starting point; the reasons AI gives for each recommendation offer the most insight. It helps to copy those reasons word for word, as phrases like “specializes in healthcare clients,” “known for fast onboarding,” or “praised for transparent pricing” often echo language found in reviews, articles, and the competitor’s own website.<\/p>\n\n\n\n Once grouped, these reasons tend to fall into themes such as specialization, client results, price, or speed. Each theme reveals what buyers in your market value and which competitor has best associated their name with it. If AI consistently describes a competitor as the go-to option for mid-sized manufacturers, and you serve that same market, you know exactly which story you need to tell more clearly and in more places.<\/p>\n\n\n\n Apply the same attention to your own mentions. Appearing fifth with a vague description carries much less weight with a buyer than appearing first with a clear reason to choose you. Therefore, how AI talks about your company matters as much as whether it mentions you at all.<\/p>\n\n\n\n AI competitor analysis shows you which competitors AI recommends, why it recommends them, and what you can do to earn a place in those answers.<\/p>\n<\/div>\n\n\n\n Many AI assistants display the sources behind their answers, usually as links next to the text or listed at the end. Opening these links one by one is one of the most revealing parts of the process, as they show you where AI gathers its information about your market.<\/p>\n\n\n\n This is where competitor analysis for AI search differs most from traditional SEO<\/a>. AI heavily relies on what others publish about a company, such as news articles, reviews, industry roundups, and comparison lists, giving much less weight to what a company says about itself. In practice, a mention in a trusted publication works for AI the same way a referral works for a buyer.<\/p>\n\n\n\n So, when a competitor repeatedly appears, examine where AI found them. They may have been featured in an industry publication, listed in a directory your buyers trust, or included in several “best providers” articles. Each of these sources is a place where your company could also appear, and together they form a clear map of where you need to be present.<\/p>\n\n\n\n Not every question has a clear winner, and these are some of the most valuable to find. As you review your answers, look for moments when AI seems unsure about who to recommend. This usually manifests as:<\/p>\n\n\n\n These open spots tend to appear in the most specific questions\u2014those that mention a particular industry, location, or problem. Consider the difference between these two:<\/p>\n\n\n\n The first question likely has well-known names already, while the second may still be up for grabs. That’s why these gaps are some of the most valuable findings in any AI competitor analysis. Claiming a question that nobody owns yet is usually much faster than dislodging a competitor AI already trusts. There’s also a bonus: buyers who ask very specific questions are often closer to making a decision, meaning the leads they bring tend to be better.<\/p>\n\n\n\n By now, you have a much clearer picture than most companies ever achieve. You know which questions you’re losing, who’s winning them, why AI prefers them, and where it finds its information. The good news is that you don’t need to fix everything at once. In most cases, these three steps will move you forward the fastest:<\/p>\n\n\n\n Show up where AI is already looking.<\/strong> Revisit the publications, directories, and review sites that appeared most often in your analysis, and start there. Each time you get featured, listed, or reviewed in one of those places, AI gains another trusted reason to include you in its answers.<\/p>\n\n\n\n Give AI a clear answer to point to.<\/strong> For every question you’re losing, check whether there’s a page on your site that answers it directly. If buyers want to know whether you work with companies their size and nothing on your website says so, AI has very little to go on. Creating that page is often a quick and meaningful win.<\/p>\n\n\n\n Set the record straight.<\/strong> From time to time, AI will describe your services inaccurately, mention old pricing, or connect you with a market you’ve moved away from. Updating your website, directory profiles, and other public information gives AI the correct details, and those errors tend to fade over time.<\/p>\n\n\n\n After that, it’s worth making a habit of tracking competitors in AI search every few months. Answers change as other companies publish new content and earn new coverage, so checking in regularly helps you see what’s working, who’s gaining ground, and where to focus next.<\/p>\n\n\n\n Doing this analysis by hand takes time, though the first step only takes a couple of minutes. Thallo’s free scan shows you how AI responds when buyers ask about your category and which competitors appear in your place. You can try the free scan here<\/a>.<\/p>\n\n\n\n
\n\n\n\nStart With the Questions Your Sales Team Hears Every Week<\/h2>\n\n\n\n
Note Which Competitors AI Names and the Reasons It Gives<\/h2>\n\n\n\n
The Takeaway<\/h4>\n\n\n\n
Check the Sources Behind Each Answer<\/h2>\n\n\n\n
Look for Questions Where No Brand Stands Out<\/h2>\n\n\n\n
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Decide What to Fix First<\/h2>\n\n\n\n
See Who AI Recommends in Your Place<\/h2>\n\n\n\n