Investigating customer loyalty of a heavy duty car using data mining techniques

نوع: Type: thesis

مقطع: Segment: Masters

عنوان: Title: Investigating customer loyalty of a heavy duty car using data mining techniques

ارائه دهنده: Provider: Zahra Tolou

اساتید راهنما: Supervisors: Dr. Hamidreza Dezfoulian

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr. Javad Behnamian, Dr. Nafiseh Soleimani

زمان و تاریخ ارائه: Time and date of presentation: 2022

مکان ارائه: Place of presentation: Faculty of Engineering

چکیده: Abstract: Customer Relationship Management is a strategy for better understanding the needs and behavior of customers with the objective of developing and cementing relations with them. customer loyalty is one of the most important topics in this area. The benefits of having loyal customers have led researchers to examine their customers ' loyalty and understand their loyalty. in this study, using service representation data after sales of a heavy car company that is related to the three years period, customer group has been used to group customers to identify them at different levels of loyalty. First, loyal customers were determined based on the company's definition of loyalty. then the segmentation of customers was done using data mining techniques. first, customers were formed by customers and then customers were examined in 4 cases. The first case is related to all the data in the time period, including all agents. in this case, two - step clustering techniques and کا - mean clustering methods were performed. The second case was the clustering of four representative agents who had the most in reference. The third case was performed on customers of two automobile models that did the most in reference. Finally, the fourth case is related to the customers who are in their warranty period. in these three cases, the clustering methods used are two - step and کا methods. finally, we used apriori algorithm to determine rules based on customer behavior. The algorithm is also used for the previous states except the case where customers are in their infancy. by comparing the results, the best agency and best model of the vehicle were determined in terms of performance. also for each group of customers based on their loyalty levels, the group features were explained and suggestions given to the characteristics of each group were presented. according to the results of the use of mixing management discussions with the customer and data mining, it has resulted in each group of customers of marketing strategy tailored to the characteristics of that group. in this way, service delivery is one of the most important factors of attraction and customer behavior in the service sector after.

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