A Precision Marketing Strategy of e-Commerce Platform Based on Consumer Behavior Analysis in the Era of Big Data

In order to develop a more efficient and accurate marketing strategy for consumers’ purchase behavior, this paper establishes user value model by modeling learning the historical data of e-commerce enterprises. The improved K-means algorithm is used cluster behavior users, customer matrix constructed from two dimensions consumption frequency average amount. Finally, users are classified into four categories marking points. test results show that stable efficient, analysis clustering characteristics helpful strategies.