Providing a New Method for Customer Satisfaction Data Analysis (Case Study: Automotive Industry: Logan Car)

This research aims to provide a hybrid model based on econometrics and clustering to analyze customer satisfaction data. The statistical population of the research,Logan car owners and a sample of 177 customers from Pars Khodro agencies. The researcher, along with ISQI's research team, identified the current needs of customers of all vehicles from post-sales services and by designing a customer satisfaction questionnaire, the effect of each variable on the overall satisfaction of customers according to the high-income group, middle income and low income is measured. Factors affecting overall customer satisfaction based on all income groups include six variables: Provision of parts on time; Description presented when vehicle clearance; Ease of access to dealers; periodic service quality; Quality of repairs; Cost of payment and in the high-income group, three variables are described: Cost of payment; Record mentioned Items by the receptionist at the time of admission; Description presented when vehicle clearance and In the middle income group, four variables are described: Provision of parts on time; Quality of repairs; Description presented when vehicle clearance; Cost of payment and and in the low-income group, it includes four variables: Description presented when vehicle clearance; Provision of parts on time; Quality of repairs; Ease of access to dealers. To run this research of software EViews and Spss is used.