Propensity Model for Marketing Campaign in eCommerce Industry

Explore a data scientist's approach to improving marketing campaign targeting in the eCommerce industry through a 27-minute conference talk from ODSC West 2015. Learn how Jing Cheng, Data Scientist and Analytics Manager at eBay, developed a propensity model using machine learning algorithms to predict customer behavior and increase conversion rates. Discover the workflow, key features, correlation analysis, model building, and automation techniques used to create accurate audience segmentation, reduce spam emails, and drive better marketing outcomes. Gain insights into leveraging big data and customer profiles to enhance high-revenue product subscriptions and customize marketing strategies for different audience segments.

Introduction
Workflow
Key Features
Correlation
Model Building
Model Automation