Churn Model for Paid Listings
Predicting churn to retain paying agents & developers.
At eBay Classifieds (Mexico & SA), Arturo built churn model combining listing, traffic, quality, and marketing data to optimize retention strategy.
The Challenge
Paid customers (agents & developers) churning despite heavy ad spend.
Our Approach
Compiled dataset from Hadoop, Databricks, Google Analytics, and ProTool, used R for churn modeling and Tableau dashboards, and re-ran monthly to measure impact.
The Outcome
15% retention lift, optimized campaigns, improved listing quality, better ROI for paying customers.
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