||For most industries, customers are important assets for the enterprises. The emergence of new customers and the loss of existing customers are inevitable. Hence how to build up the long-term relationship between company and customers by giving them appropriate care, or to sacrifice a certain level of those low profitable customers in order to increase maximum profit has always been the aim of customer relationship management (Customer Relationship Management, CRM). |
With the evolution of the times and technology, data analysis has become an important part of customer relationship management. Once transactions were generated, the enterprises will be able to use the records to calculate the customer lifetime value (Customer Lifetime Value, CLV). In other words, the value can be utilize by the enterprise to predict customers’ future contribution level via customers’ previous consumption behaviors. Enterprises could develop different CRM based on different CLV.
In recent years, customer relationship management has been widely used in the financial industry, insurance industry, general retail industry, etc. However, this study will focus on the development of CRM in hairdressing industry. In addition to the feature of physical channels and a fixed frequency of consumption of customers, the loyalty of customers will be lessened by hair designers, which could not be seen in other industries. Therefore, how to increase customers’ loyalty to companies is an important key of the development CRM.
Through a case study and background research of company A, this study further analyze the customer transaction records between 2009 to 2016 by applying NES model to segment customers. Using regression analysis to predict CLV of each segmentation, and giving different strategic advices based on the regression analysis and the customer management matrix proposed by Kumar and Rajan to develop and retain customers for company A. This study will provide a set of customer relationship management practices that can be used effectively in Taiwan's hairdressing industry. It is advisable for Taiwanese managers in hairdressing industry, when they are making marketing strategies by data.