01 / THE NUMBER
+31%
Traffic from AI answers

The Fragrance Square, cited by assistants

Fragrance retail · Innovate
Visit thefragrancesquare.com ↗
02 / CONTEXT

The Fragrance Square is an online fragrance retailer competing against larger stores for the same buyers and the same search queries.

03 / IN THEIR WORDS
“People ask assistants for scent recommendations, and our products never come up.”
04 / WHAT WAS BROKEN

The real diagnosis.

01

Product pages listed attributes but answered none of the questions buyers actually ask.

02

No comparison or guide content for assistants to draw from.

03

Thin metadata gave models little to cite.

05 / THE ARCHITECTURE
SOURCESDBs · APIsfiles · eventsCOREclean data+ softwareVALUEagents+ automationINNOVATEweb · store+ AI searchCUSTOMERSpeople & themodels they askDATA INVALUE OUT
06 / WHAT IT DOES NOW

Restructured product and guide content (notes, comparisons, and buying guidance written to be quoted) so assistants recommend the store’s products directly.

07 / THE RESULT
+31% traffic from AI answers
  • +Products cited in assistant recommendations for scent-family queries.
  • +Higher intent: buyers arrive already sold.
08 / IN THEIR WORDS
We’re getting buyers who say an assistant recommended us. That never used to happen.
Director, The Fragrance Square
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