Three great product search experiences powered by machine learning

“1) Improved product search for misspelt words

  • On average, 25% of all ecommerce search queries are misspelt, and the modern shoppers won’t take the blame for typing the wrong command
  • Zalando decided to tackle this problem using deep learning. With the help of machine learning, Zalando can now parse 300,000 products in two seconds and deliver on-point product suggestions despite inaccuracies.

2) Voice shopping experience guided by AI

  • Customers in the UK and US can also call Asos’ Enki Chatbot using the Google Assistant app or Google Home Speaker to browse the 85,000 products on the website and cherry-pick personalised suggestions.

3) Camera-powered visual search

  • Boohoo, an apparel brand targeting image-oriented Millennial and Gen Z consumers, clearly took note. The company recently partnered with Syte – a startup offering image recognition technology for retailers – to add visual search functionality to their mobile website. The Camera Button added to the search bar, allows users to upload their pictures and discover the most visually similar products in stock. Shoppers are then presented with a selection of relevant products, additionally populated with even more similar styles and “Shop the Look” curated picks.
  • BooHoo also reported a 135% increase in pages viewed per session and a 12% increase in average order value”

https://econsultancy.com/examples-product-search-machine-learning-ecommerce/

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