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French sporting goods giant bolsters search with machine learning

Decathlon wants to speed up its customers’ online search efforts.

With more than 1,350 stores across more than 40 countries, Decathlon offers its international customer base a wide range of products from shoes to camping gear. However, this broad assortment was taking a toll on its online experience.

The retailer, which recently opened two U.S. locations , struggled to accurately — and efficiently — tag products with the right search terms, an issue that didn’t always generate the proper search results. This was exacerbated by varying search habits across its global customer base.

By integrating artificial intelligence (AI) and machine learning technology by Adeptmind into its online search capabilities, Decathlon is tightening its online search functionality. The self-learning engine uses advanced targeted crawling and deep learning knowledge graph techniques to bridge the gap between offline and online conversations among Decathlon customers. Now customers are able to find exactly what they’re looking for — and in less time.

Since adding the solution, Decathlon has seen more than a 175% improvement in its search conversion rate month-over-month, and search activity increased by more than 123%. The company has also been able to reduce attrition following search queries by 63% month-over-month, and search depth (having to go to page two, three or more to find a product) dropped by 57% month-over-month. The retailer is also reducing the time from start of session to sale by 48%.

“We can better understand customers’ wants to connect shoppers to the right product faster,” said Tony Leon, CTO at Decathlon. “Adeptmind is easy to integrate, improves our e-commerce search and browsing experience, and lets us make our products easier to find. Ultimately, we’re evolving the way we think about the online experience to prepare for the future of shopping.”
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