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From visual search to computer vision, natural language processing to predictive modelling, machine learning underpins all kinds of innovations that are levelling the playing field by giving retailers of all sizes access to the same tools as behemoths like Amazon – and allowing them to develop cutting-edge online and in-store experiences.

This in-depth briefing will look closely at a number of different applications for machine learning in retail, accompanied by examples of how retail brands are putting them into practice and how they translate to improvements in sales, processes, customer engagement, and the customer journey. It will examine both ecommerce and bricks-and-mortar retail, noting the differences in how machine learning is used in digital versus offline environments, before finally considering how this usage might evolve in the future.

Contents:

  • How are retailers applying machine learning in ecommerce?
    • Product discovery
    • Personalisation
    • Forecasting & optimisation
    • Sentiment analysis & customer feedback
  • How is machine learning changing bricks-and-mortar retail?
    • In-store technology
    • Inventory & merchandising
  • What’s next for machine learning in retail?



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