Define the buying questions
Agree on category, target market, language, platforms, competitors, and representative prompts. Separate brand searches from actual product decisions.
REVIEWABLE OUTPUT
Question map and written measurement scope
OUR APPROACH / EVIDENCE BEFORE CLAIMS
From buyer questions
to useful answers.
A repeatable working method for AI search visibility. Every stage produces something your team can review, approve, and use.
THE FOUR STAGES
Work you can inspect.
We work with the information you control and document the answers you observe. The final plan depends on your catalog, access, and market.
Capture the baseline
Record the exact question, date, platform, answer, mentioned products, cited URLs, and accuracy issues. Check the product pages and independent sources behind the answer.
REVIEWABLE OUTPUT
Answer and source log with a prioritized gap list
Improve useful information
Verify product claims with your team. Revise approved pages and comparisons, fix confusing catalog information, improve internal links, and prepare relevant editorial materials.
REVIEWABLE OUTPUT
Approved content or developer-ready handoff
Check again and decide
Run the agreed questions again and compare observations with the baseline. Review referral and inquiry data when available. Recommend what to maintain, expand, or stop.
REVIEWABLE OUTPUT
Change log, follow-up findings, and next scope
WHAT WE SEPARATE
Visibility has
different meanings.
A page can be accessible without being cited; a brand can be mentioned without earning a click; a referral can arrive without a sale.
Discoverability
Can systems reach relevant, accurate pages and product information?
Answer presence
When and how is the brand mentioned, described, or linked in a defined question set?
Business impact
What can available analytics say about referral visits and qualified inquiries?
Begin with one category.
Bring us the buyer questions and product facts that matter most.
Scope an audit