Industry Session 2: Novel Approaches

Date: Tuesday, Sept 17, 2019, 14:00-15:30
Location: Auditorium
Chair: Kim Falk

Groupon Finally Explains Why We Showed Those Offers

by Sasank Channapragada, Harshit Syal and Ibrahim Maali (Groupon)

Groupon has a large inventory of offers as varied as local taquerias, massages, concert tickets, and trips to Costa Rica. Our Search & Recommendations team continues to develop algorithmic recommendations systems, machine-learned query understanding models, and increasingly sophisticated personalization and sales conversion estimations. Across an inventory of millions of offers, including many highly localized and geographically-specific ones unique to Groupon’s Local business, we strive to balance inventory exploration and matching our users with the exact right item. Our Recommendations models take a variety of factors into account so that we can make the most relevant suggestions to our customers in their neighborhood, or while traveling in one of our hundreds of domestic and international markets. Our system must index millions of items, including the many specific to a user’s location; score the deals based on estimated conversion; and finally make adjustments for personalization, exploration, and diversity before delivering our ranked list of inventory to the platform. Yet despite our efforts, many of our customers are unaware of how highly considered their Groupon App and Emails are. In numerous customer interviews we found a huge perception gap that had to be addressed. Customers expressed that our central scrollable home feed felt ‘cluttered’, ‘disorganized’, and ‘like a garage sale’. It was clear to us that the next great sophisticated recommendation feature meant nothing if our customers couldn’t appreciate it.

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