Challenges in Merchandising, Recommendation, and Search for Local Delivery Commerce
Challenges in Merchandising, Recommendation, and Search for Local Delivery Commerce


Consumers’ appetite for delivery of all goods instantaneously through a few taps on their smartphones is fueling the local delivery commerce. The demand is spreading rapidly from prepared food to grocery, convenience items, and beyond. Providing intuitive user experience to meet this consumer demand poses significant challenges for merchandising, recommendation, and search. In this talk, we will describe a number of these significant challenges and discuss how DoorDash is addressing these using data science and machine learning.


Han Shu leads DoorDash’s Consumer and Merchant Data Science teams, working to optimize consumer experience, increase merchant supply, and the balancing of supply and demand for the online marketplace. Han earned his PhD in Computer Science and Electrical Engineering from MIT, focusing on speech recognition. He built the winning system for the DARPA-sponsored Hub-5 Mandarin Chinese Speech Recognition evaluation at BBN. He co-founded Vlingo after MIT, which at one time supplied speech recognition technology to Apple’s Siri. Vlingo’s flagship product became Samsung S Voice, running on over a billion mobile phones. Subsequently, he co-founded Wyth, a company facilitating get-togethers among friends, which was acquired by Airbnb. Prior to joining DoorDash, he led data science teams at Airbnb for Customer Support, Consumer Experience, and Growth & Marketing.

Open Data Science




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