High Value Customer Acquisition & Retention Modelling - A Scalable Data Mashup Approach

2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)(2019)

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摘要
Identifying valuable customers as well as retaining them has become key component for any business to succeed in this competitive market. Businesses have also realized that relying solely on its own transactional data, might not be sufficient any longer, to meet the required objectives. There is a need to partner and leverage the power of big data available from the external data sources to add more value. In this paper, we are detailing the methodology of mashing up Mobilewalla's high scale mobile consumer data with one of the world's largest online food delivery company in order to revamp their retention and acquisition strategy. In this deployment, Mobilewalla has helped the client, a) to identify the new potential high impact customers from Mobilewalla ecosystem, and b) to predict the unfavorable transitions such as high impact customers getting churned or falling into low impact category. We observed that correctly identified high impact customers by Mobilewalla' customer acquisition model had 21.41% higher average revenue per user (ARPU) than the expected ARPU from high impact customers. Further, the customer retention model can help the client to spend 80% of their retention budget dollars optimally.
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关键词
Data Mashup, Customer Acquisition, Customer Retention, Churn Prediction, RFM, User behavior
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