Large Scale Data Analytics of Customer Segmentation and Forecasting with Machine Learning

Wang Rui

Abstract

It has been claimed that customer is god, fully fulfill customers’ demand and 100% meet customer satisfaction is an ideal that a company should try to achieve. However, nowadays, customer has more and more customized requirements and it become very hard to analysis or forecast their preference by using manpower. Or we will considerate it is really worthy Spend a large price to hire someone to understand the preferences of each customer. In this paper we study the applicability of machine learning and big data to analysis the customer and forecast their demand, including RFM and LSTM model. The model RFM is used to sort customer into different segments according their purchase behavior, the LSTM is used to forecast the particular customer’s annual demand. show that with the use of RFM model we can identify the potential customer, brands, profitable product items and use information for better customer demand forecast. Due to the generality and flexibility of the model, it also enjoys the potential applicability to other future ne data and other analysis.