Al-Futtaim Group drives 206% search revenue growth and 221% order increase with Algolia AI Search
Al-Futtaim Group faced poor search relevancy from their out-of-the-box onsite search algorithm, a drastic mismatch between category page and search results, and a fully manual merchandising process that prevented teams from focusing on planning and optimization.
The out-of-the-box onsite search algorithm delivered poor search relevancy, with a drastic difference between category page results and search results.
After adopting Algolia across Al-Futtaim Group's retail sites, ACE search sessions increased by 128%, search revenue by 206%, search CVR by 41%, and search orders by 221%.
In ACE UAE specifically, search usage jumped from 8% to 18% with a threefold increase in search revenue, indicating customers can now find products more effectively.
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Frequently asked questions
What did this team achieve with this AI workflow?
After adopting Algolia across Al-Futtaim Group's retail sites, ACE search sessions increased by 128%, search revenue by 206%, search CVR by 41%, and search orders by 221%.
What tools did this team use?
Algolia, AI Synonyms, Dynamic Re-Ranking, Query Categorization, Personalization, NeuralSearch, Algolia Recommend.
What results were reported?
ACE search sessions: 128%; ACE search revenue: 206%; ACE search CVR: 41%; ACE search orders: 221% (source-reported, not independently verified).
What failed first in this deployment?
The out-of-the-box onsite search algorithm delivered poor search relevancy, with a drastic difference between category page results and search results.
How is this ecommerce ops AI workflow structured?
Customer search on PLP or search page → AI synonyms and query categorization → Dynamic re-ranking and personalization → A/B testing refines strategies → Optimized search results delivered.