Measure
Are we in the answer?
Understand
Why do they pick someone else?
Fix
What do we change first?
By team
Built for the people who own the answer
By need
Start from the question you have
Learn
Guides and definitions
Proof
How we measure
Compare
MentionX side by side
Company
Who builds MentionX
Local and specialty care see growing AI-mediated discovery. MentionX tracks mentions, citations and competitor presence on care-seeking prompts.
Nobody scrolls ten blue links any more. The answer is the shortlist, and the shortlist is the market. In healthcare, a name that is not in it is not in the room.
Most tools stop here and tell you whether you appeared. That is the easy question.
In one small usability study, people expected hours, phone numbers, ratings and booking options from AI answers about clinics, and often did not get them. Complete, consistent listings give engines something to use.
Every gap becomes an ordered fix. Do them in order, rescan, and watch your name climb the shortlist.
The question leadership asks is never “are we mentioned”. It is what the fix is worth. Each gap is tied to the revenue it touches, so the order of work has a number next to it.
No. It measures how AI recommends care providers and which sources it cites.
Yes. Local prompts are discovered from your URL.
Thin. We label it directional until your scans show what is true for your category.
Stored engine answers before scores. No fabricated query volumes.