AI Visibility tracking is set up per workspace, based on a set of queries relevant to your brand and category. This article covers how to configure it and how to read the results.
Setting up your query set
Start by defining the questions you want tracked — a mix of category questions that don't mention your brand by name, direct comparison questions against known competitors, and use-case questions phrased the way a real customer would ask them. The quality of your query set matters more than its size; a focused set of realistic questions produces more useful trends than a large set of generic ones.
Reading your visibility score
Your AI Visibility score summarizes presence, position, and comparative standing across your tracked queries into a single trend line, with the underlying detail available per query. Because individual AI-generated answers can vary, the score is designed to be read as a trend over weeks, not judged from any single check.
Accuracy flags
If a tracked query surfaces a clearly inaccurate description of your product, pricing, or positioning, it's flagged separately from the presence and position score, since accuracy issues usually call for a different response — typically clearer, more explicit content addressing that specific claim directly.
Adjusting your query set over time
As your product, positioning, or competitive set changes, revisit your query set rather than leaving it static indefinitely. A query set built a year ago may no longer reflect how customers currently talk about your category.