Walgreens improves digital search and discovery with Algolia AI Search
Walgreens' prior search provider gave the digital team few controls to act on, and reliance on development resources created long lead times and a growing backlog, preventing agile improvements to the customer experience.
The previous open source search provider lacked configurability and business-user controls, keeping the digital experience team dependent on developer involvement for every change.
Walgreens completed the Algolia implementation in approximately 16 weeks — one of its fastest implementations — and the digital experience team can now review real-time data, react quickly to customer demands, and iterate without development being the bottleneck.
Frequently asked questions
What did this team achieve with this AI workflow?
Walgreens completed the Algolia implementation in approximately 16 weeks — one of its fastest implementations — and the digital experience team can now review real-time data, react quickly to customer demands, and ite…
What tools did this team use?
Algolia, AI Synonyms, AI Reranking, Personalization.
What results were reported?
Implementation time: approximately 16 weeks; implementation speed relative to other Walgreens projects: one of our fastest implementations at Walgreens; Customer product findability: improved the ability for Walgreens customers to find products and services; Time to value: fast time to value and return on investment (source-reported, not independently verified).
What failed first in this deployment?
The previous open source search provider lacked configurability and business-user controls, keeping the digital experience team dependent on developer involvement for every change.
How is this ecommerce ops AI workflow structured?
Customer search on website or app → AI Synonyms and AI Reranking applied → Personalization connects customers to products → Business team iterates via dashboard.