You wouldn't build an SEO strategy around ten random keywords and call it done. So why do so many brands track ten random prompts in AI search and call that reporting?
TL;DR: STAT Search Analytics lays out a four-step process for building an AI search prompt set that actually tells you something: segment by business vertical, categorize by intent and brand, expand with a deliberate mix, then monitor patiently. Skip any of these and your AI visibility data ends up misleading instead of useful.
🧭 Your Prompts Are Probably Working Against You
Tracking prompts in AI search isn't the same job as tracking keywords in traditional search, even though it feels like it should be. A keyword captures a search term. A prompt captures how someone actually talks to an AI system, and that difference matters more than it sounds like it should.
How do you know your current prompt set needs a rebuild? A few warning signs: your visibility looks stable but the data never leads to any real decision, your prompts are outdated or overloaded with your own brand name, you've added new products or business lines that nothing is tracking, and you're not watching competitors at all. If two or three of those sound familiar, it's time for an audit.
🪤 Fix It With Four Steps
Segment Your Prompts by Business Vertical
Start by breaking your prompts into the actual verticals that make up your business, not one flat list. A fast food brand might split into core menu, breakfast, and drive-through. A financial services company might split into banking, loans, investing, and mortgages.
This matters because a blended view hides exactly the trends you need to see. You want to know how you're doing in "breakfast" specifically, not just "food" broadly.
Categorize Each Prompt by Intent and Brand
Once verticals are set, sort prompts into four categories: branded (includes your name), competitor (includes theirs), informational (no brand name, general topic), and comparison (invites the AI to weigh options). Branded and competitor prompts are useful, but tracking too many of either can quietly inflate how visible you actually think you are.
Informational and comparison prompts are where your real, unprompted visibility shows up. If you want to know whether you're winning new attention or just talking to people who already know you, this is the split that answers it.
Expand Your Set With the Right Mix
With structure in place, add more prompts, aiming for at least 20 per vertical. STAT suggests a rough mix: 40-50% informational, 30-40% comparison and competitor, 15-20% product mentions, and no more than 15% pure brand name.
That ratio keeps your data honest. A prompt set that leans too heavily on your own brand name will always make you look more visible than you actually are to someone who's never heard of you.
Monitor Patiently, Not All at Once
After refreshing your prompts, expect a dip. Removing inflated branded terms often makes your visibility numbers drop briefly, and that's the data correcting itself, not a real decline. Wait about two weeks before drawing conclusions.
When you do review, look at each AI engine separately instead of one blended average, since an average can hide real gaps between how you show up on different platforms.
Hit reply
Have you actually gone back and audited your AI-tracked prompts, or are you still running the list you started with months ago?
Did You Know? STAT recommends waiting roughly two weeks after refreshing a prompt set before reviewing results. The dip you'll likely see right after the update is expected, not a sign something went wrong.
One thing I'm thinking about: prompt tracking is going through the same growing pains keyword research went through years ago, when people first learned that ten vanity keywords don't make a strategy.
It's a little strange watching an entire discipline relearn that lesson in a completely new context, but it's a good sign the industry's taking this seriously instead of just bolting AI tracking onto old habits.
Till next time,
