Database Development And Data Mining Based On Customer Service Data

Home appliances industry is a very competitive industry in China. When it comes to the key durable products, the competition in this aspect is becoming more obvious. So quality gap in either products or services is getting undistinguishable but homogeneity is tending to close. In this situation, quality is no longer the first priority when choosing a product but individual taste and quality service matter. When a company comes to realize that the customer is the key resource in competitive market, customer relationship management will be given more attention, in which customer satisfaction and loyalty constitute its main part.This paper, based on the customer satisfaction survey, gives the key independent variable and the dependent variable analysis and customer subdivision grounded on customer service satisfaction by using data mining technique to analyze and study history customer satisfaction survey data in order that it can be supportive on service decision-making and promoting its quality. This paper contains the following points:(1) By using AHP (Analytical Hierarchy Process), it finds out how key factors in customers services flow affect customer satisfaction and finally gets its ration, which to some degree diminishes windage in estimating and adopting customer satisfaction value. Also it confirms the practice work and provides theory basis for management and decision-making.(2) By using Statistics theory: it gives the relation between independent variable and the dependent variable. So key factors- door service and hotline service, which determine the home appliance customer service, is found out, demonstrating the main task in proving customer satisfaction in later work. In this way, management efficiency gets improved while twice result come out with half effort.(3) By using decision tree theory: customer subdivision is completed based on the customer satisfaction characteristic. Meantime, it concludes that customer with different age, different occupation, different income and gender have different effects on customer satisfaction service, which providing the basis for offering distinguishing service and establishing specific service policy in the future.