Application of Big Data Marketing in Customer Relationship Management

Abstract

Policy decisions and marketing models have a great impact on the specific application of customer relationship management. In various fields of marketing, big data marketing is gradually popularized as a combined product. The so-called big data marketing refers to collecting a large amount of behavior data through the Internet, primarily helping advertisers find out the target audience to analyze the content, time and form of advertising and finally complete the marketing process of advertising. The big data marketing can also be used for effective customer relationship management, which not only effectively enhance customer stickiness and reduce enterprise operating costs, but also has great significance for deeply mining the potential value of existing customers, predicting the future demand trend of customers, discovering new market growth points and developing new customer groups. Taking the large FMCG company A as the research subject, its sales is grim and stagnant: the purchase quantity of products is low; the price is lower than the cost; simple reproduction is difficult to continue. In order to change the current situation of company A, first of all, we cooperate with the marketing team to determine the business needs, using SQL and python to conduct exploratory data analysis (EDA) on 110k + e-commerce transaction data, and generate Data-Driven Insights on purchasing behavior and product sales; secondly, we use Python to establish RFM model (recent degree, frequency, currency), classify customers and calculate. Finally, according to the above customer analysis, a feasible listing strategy is proposed, which is expected to increase the retention rate by 3.5% and the monthly sales by 6%. Through big data marketing calculation, we come to a solution for the current situation of company A, which will have a good influence on many other companies.