Real-time, Contextual and Personalized Recommendations

Apr 10, 10:00AM PDT(05:00PM GMT).
  • Free 172 Attendees
Levi Strauss and Co has always been at the helm of innovation with their classic denims and seasonal takes on the future of denim . We would like to enable users who visit our website, receive our emails and visit our stores to have the most personalized experience with easier product discovery.
To enable this, I have built recommendation systems based on live and past user behavior and with minimal infrastructure. The talk would feature two main areas:
  • How to work with minimal data , implicit feedback and business to build recommender systems that satisfy users needs while keeping in mind overarching business KPIs
  • How to use real stream of events and past indications to give a completely personalized experience that can keep updating based on user interaction with minimal architectural requirements..
  • Dhivya Rajprasad

    Dhivya is the lead data scientist at Levi Strauss and Co. At Levis, she is focused on improving customer experience by working on challenging and diverse ML problems such as building recommender systems, personalizing user journey, inventory forecasting for wholesale, optimizing margins etc. When she is not crunching numbers, she loves to plan and travel!
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