The page that helps AI recommend your product may start with a spreadsheet your
By Brandon Fishman · November 10, 2026 · Curated by George's Blog
The page that helps AI recommend your product may start with a spreadsheet your team already owns.
Take replacement air filters. Hypothetical example.
A shopper asks AI, "Which filter fits my purifier?"
Your product team has the compatibility list. Support knows which models people confuse. Returns tell you where customers keep ordering the wrong one.
I'd use that information to build a page answering the buying question.
List the exact model numbers, the filter each one takes and the products it doesn't fit. Include photos showing where customers can find their model number.
Publish the answer in readable text on a page search engines can access.
That gives AI a specific source it could use when helping someone choose a filter. Publishing it doesn't guarantee a citation.
Casey Hill's Ramp example shows the content idea. Ramp uses merchant data to build pages explaining unfamiliar credit card charges. It turned information it already had into public answers.
For a product brand, I'd start with one recurring buying question the team can answer with evidence.
Then check what AI recommends for that question and which pages it cites. Keep checking after your page goes live.
Auden saves those answers and sources so our team can see whether your page is being used and whether the product details are right.
DM me "AUDEN" for a demo.