Co-op scales search and improves customer experience with Algolia
As Co-op rapidly scaled its online grocery business during the pandemic, its existing search system proved too limited — unable to tag products or be easily modified — and could not provide customers with real-time inventory visibility or useful alternatives when products were out of stock.
Co-op's prior search solution was too limited to tag products or accept easy modifications, and required extensive manual rule management to maintain relevance.
Algolia delivered a 39% conversion rate increase, a 45% increase in people adding to basket, and 6% larger basket sizes with £2 higher spend.
Recommendations for out-of-stock products drove a 7-percentage-point lift in add-to-basket rates and 6% higher basket spend, while Dynamic Re-ranking saved merchandising team time.
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Frequently asked questions
What did this team achieve with this AI workflow?
Algolia delivered a 39% conversion rate increase, a 45% increase in people adding to basket, and 6% larger basket sizes with £2 higher spend.
What tools did this team use?
Algolia, Algolia Recommend, Dynamic Re-ranking, AI-based Synonyms.
What results were reported?
Basket size increase: 6%; Basket spend increase (absolute): £2; People adding to basket: 45%; Conversion rate increase: 39% (source-reported, not independently verified).
What failed first in this deployment?
Co-op's prior search solution was too limited to tag products or accept easy modifications, and required extensive manual rule management to maintain relevance.
How is this ecommerce ops AI workflow structured?
Customer searches for products → Live stock data synced to Algolia → Dynamic re-ranking improves results → Recommend alternatives for out-of-stock items.