Sunanda Parthasarathy

Superior Customer Service with AI: Personalization at Wayfair

With an ever-expanding catalog of products that are inherently harder to buy with just an online description, Wayfair has a unique challenge in personalizing a customer’s journey to find their one special piece of home furnishing among zillion things home. In this talk I will go over multiple case studies where we have successfully demonstrated the benefit of applying ML and AI techniques to personalize a customer’s touchpoint, both onsite and off it. Starting from using reinforcement learning techniques that help send the right content to customers via emails, to applying computer vision and neural network methods to help curate the right kind of products onsite, the talk will aim to share the challenges we faced en-route to creating one of a kind online furniture shopping experience. Attendees can hope to take away key insights on how best to translate cutting-edge data science technology into real business decisions and typical challenges faced in scaling these technologies.

Sunanda KP, is an Assoc. Dir. of Data Science at Wayfair Inc where she leads a team of data scientists and engineers to build ML solutions that lead to a better shopping experience for all Wayfair customers. Prior to this, she was leading innovation R&D projects at the AdTech startup DataXu, that spanned the spectrum of Multi-Touch Attribution to developing new analytical product solutions that helped clients achieve optimum Marketing ROI. Through her career in data science she has enjoyed focusing her quantitative expertise in mathematical modeling to business questions that has led to multiple high-revenue analytics products. Her current passion is to develop an intelligent system that recommends the optimal product/message exposure to customers to make their online shopping experience very personal and enjoyable. Before entering the data science world, she was a Princeton Postdoctoral fellow, working on the forefront of the next generation quantum materials that will replace silicon in a computer chip. Prior to that she received her PhD in physics from Purdue University working on solving open problems in the field of transport physics. Her research accomplishments have been recognized in the form of many awards including the H.Y.Fan Award for excellence in physics research. She is an active member in the local start-up, tech and data science community and is the co-organizer of one of the oldest meetup groups in Boston- The Data Scientist. She enjoys bringing together leading minds in the field of data science and AI, to engage in thought leadership in this nascent field.

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