As the size of mobile Internet users grows, the cost of acquiring customer data increases. It is important to develop targeted acquisition, retention and re-attraction strategies for different levels of users. The consumer lifecycle can be divided into three stages: 1) customer acquisition stage, focusing on attracting new customers; 2) enhance customer value stage, focusing on strengthening consumption vitality and repurchase; 3) customer retention stage, mainly through retention and return measures. Different stages of customer contribution to the enterprise is different, so enterprises should adopt different strategies. In this paper, we use Python to analyze and model the data, and implement targeted marketing for different categories of customers by evaluating the market competitiveness of the enterprise, customer classification, and user profiles.

Hao Qin. User Life Cycle Research Based on User Consumption Data. Academic Journal of Business & Management (2023) Vol. 5, Issue 18: 147-156. https://doi.org/10.25236/AJBM.2023.051823.

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