Incorporating Customer Preference Information into the Forecasting of Service Sales

Abstract

Customers change their preferences while getting more familiar with services or being motivated to change their buying habits. Different sources of motivation induce customers to change their behavior: an advertisement, a leader in a reference group, satisfaction from services usage and other experiences, but usually those reasons are unknown. Nevertheless, people vary in susceptibility to suggestions and innovations, and also in preference structure change dynamics. Historical information about the preference structure gives additional information about uncertainty in forecasting activity. In this work the conjoint analysis method was used to find customer preference structure and to improve a prediction accuracy of telecommunication services usage. The results have shown that prediction accuracy increases about by one percent point, what results in a 20 percent increase after using proposed algorithm modification.