Research on the classification and application of precision marketing based on big data e-commerce platforms

Abstract

Abstract This paper proposes and improves the traditional K-means algorithm, utilizes the HC-Kmeans algorithm to deeply analyze the marketing status quo of the M e-commerce platform, and constructs the overall framework of precision marketing based on big data technology. The RFM model is used to measure customer value and segment customer behavior. Formulate marketing strategies that correspond to the consumption habits and preferences of different categories of users. The data from 40 consecutive days of observation is used to verify the precision marketing effect of the A/B testing method, and the final results show a good improvement in the click rate, order rate, payment rate, and order amount. During the Double Twelve Shopping Festival, compared with the traditional mode, the payment amount of M Company’s product recommendation increased by 64,604 yuan, and the order increased by 301 units, so the implementation of the precision marketing strategy was effective.