Based On The Fuzzy Clustering Of Fmcg Customer Behavior Research

Fast Moving Consumer Goods (referred to as the FMCG) is an industry of intense competition. In many product categories, the fast moving consumer goods is a relatively with lucrative profit margins, large sales and fast development. Over the years, agencies and market watchers are close tracking the industry trend. It is a huge market with wide range of consumer groups, low barriers to entry, and all of the above cause the fierce competitive status of the market.For an enterprise, to grasp the consumers’demand is essential to ensure winning a place in the fierce market. In order to understand customer needs and tap their potential value, data mining is a vital tool.Cluster analysis is an important branch of data mining. By analyzing the consumption of customer, we can measure the preference of customer furthermore from the existing dada, to predict consumer’s next reaction to the fast changing market, and thus make miscellaneous decisions of production and marketing.Fuzzy Cluster Analysis is especially suitable for the objects that have fuzzy and uncertainty features. It can fit the FMCG company’s needs to analyze the consumer behavior data.The research is based on data of real customer behavior, and using the Fuzzy Cluster Analysis. The result has provided valuable information in practical application for FMCG companies.This paper contains six chapters. The first chapter introduced the background and structure of the research; the second chapter introduced the FMCG industry; the third chapter introduced fuzzy cluster analysis and how it was used on FMCG analysis model; the fourth part was the implement and code for fuzzy cluster on FMCG consumer behavior analysis; the fifth chapter gave the practical application in customer behavior analysis using fuzzy cluster the last chapter was the conclusion and future research plan.