Generative Shopping Copilot for a Specialty Home Goods E-tailer
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Problem
Shoppers couldn't articulate searches
A specialty home-goods e-tailer with 85,000 SKUs found that shoppers who couldn't name what they wanted simply left: search demanded exact keywords, category menus ran seven levels deep, and 68% of sessions ended without a single product page view. Questions like 'something to soften a dark hallway' returned no useful results.
Solution
Catalogue-grounded generative copilot
We built a generative shopping copilot that lets customers describe their need in plain language and returns three curated suggestions with plain-English reasoning. The assistant retrieves from a vector index of the full catalogue, grounds every answer in live product and stock data to prevent invented items, and hands off to human support for order issues.
Measurable Impact
What changed after launch
41% of copilot conversations ended in a product-page visit, against 12% from keyword search
Sessions that used the copilot converted at 2.6x the site average
Zero-result search experiences reduced by 57% as the copilot absorbed vague queries
Average order value on copilot-assisted purchases came in 19% above the site average
Tech & Tools Used
What powered the build
Ready to Build your Home Goods Ecommerce Business with AI Copilots & Assistants
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