Funnel Analysis in Hadoop at Etsy

Hadoop in Practice Great America Ballroom K
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As an ecommerce site with more than 800,000 different sellers, Etsy is particularly interested in understanding how shoppers find the items they seek. Part of this understanding involves attributing successful purchases to specific features on the site. This attribution model allows us to compare and refine Etsy’s features, but also provides valuable signals for A/B testing, search quality, and recommenders. However, the path to a successful handmade purchase often involves multiple features over the course of several visits.

This talk will discuss the challenges of funnel analysis at Etsy and the corresponding deficiencies of several widely used web analytics tools. We’ll then dive into our event sequence matching tool, which we’ve successfully applied to hundreds of millions of visits in a single Hadoop job and is widely used across our big data stack. Finally, we’ll take a look at some of our applications of the tool and compare it to related work.

Photo of Matt Walker

Matt Walker

Simon Data

Matt Walker is a engineer at Etsy, where he is building out their big data stack and researching techniques for search and advertising. Previously, he worked as a researcher at Adtuitive and as an engineer at Pervasive Software. He holds an MS in computer science from UT and received his BS in electrical and computer engineering from Rice University.

Wil Stuckey


Photo of Steve Mardenfeld

Steve Mardenfeld


Steve Mardenfeld is a Data Engineer for the Big Data Team at Etsy, where he uses Hadoop and other tools to process and analyze large data sets. Previously to Etsy, he worked as a Senior Data Analyst for a criminal justice agency, where he focused on utilizing data to help inform criminal justice policy issues.


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