The Data Mining Of Customer Relationship Management In Consulting Firm

With the development of service industry, as one kind of service industry, the consulting industry has been more valuable. As acquiring new customers has been more and more expensive, in order to survive in the increasing competitive management consulting industry, the consulting firm pays more attention to their existing customers. The consulting firm has retained much detailed data about their customer’s trading behavior, how to explore potential customers, important customers and identify low-value customers from the data then get the cross-selling opportunities toward these customers has become a important topic.This thesis discusses the theory and practices about the method of the consulting firm using data mining identify the value of customers and implement cross-selling with CRM system. The research firstly introduce the consulting firm and customer relationship management system, analyze the necessity, advantages and disadvantages of implementation of CRM based on the summary of the characteristic of the consulting industry, expound the consulting firm’s choice model and implementation characteristics of the CRM system. Then I analyzed the usage of data warehouse and data mining in CRM and pointed out the data mining can be mainly applied to the consulting firm’s customer classification and cross-selling. Based on the mentioned analysis, I propose the customer classification model and cross-selling model. Finally, I make a detailed empirical analysis about the Y-consulting firm case, introduce Y firm’s existing customer segmentation and sales strategy, design the CRM for Y firm and then reclassify their customer reanalyze their sales strategy, I point out the customer classification and sales strategy must be based on the scientific method.