Reinforcement Learning E-Commerce Cart Targeting to Reduce Cart Abandonment in E-Commerce Platforms
Keywords:
Reinforcement learning, e-commerce, E-commerce cart targeting, feature extraction, feature scoring, purchase response rate (PRR), footprint of cart abandonment (FCA), abandonment mitigation cost (AMC).Abstract
E-commerce has gained wide acceptance with rapid penetration of internet. Though E-commerce creates higher user visits and strong purchase intention among the consumers, only a fraction of product selected by user passes through sales tunnel and rest remain in cart. Recent studies have pointed 50% of total transactions are abandoned. There can be various reasons for cart abandonment like price, product specific features, and failures during purchase and lack of purchase options etc. This work proposes a reinforcement learning based solution which is able to predict the reasons for cart abandonment from click stream analysis and dynamically learn strategies to reduce cart abandonment rate. Different from existing method of frequent unsuccessful remainder, this work proposes personalized strategy with higher success rate. .
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