Title :
Analyzing Relative Importance of Service Quality Components from Enterprise CRM Data
Author :
Chauhan, Himanshu ; Gupta, Ajay ; Verma, Ashish
Author_Institution :
IBM Res., New Delhi, India
fDate :
March 29 2011-April 2 2011
Abstract :
Rapid growth of the services industry over the past few years has led to increased number of research efforts in the area of service quality improvement. However, analyzing service quality and determining the factors inuencing consumer´s perception of service quality is a challenging problem. Our work explores a data driven approach to analyze the comparative inuence of the two primary aspects ´experience´ and ´outcome´, on service quality. With our novel approach, we analyze a large number of customer satisfaction feedback records using text analytics techniques. We apply simple statistical and machine learning techniques to study the dynamics between occurrence frequencies of keywords related to both experience and outcome in user comments and the corresponding customer satisfaction scores. Based on our analysis we observe that in the context of customer support centers, service experience has stronger inuence on perceived customer satisfaction and service quality.
Keywords :
call centres; customer satisfaction; learning (artificial intelligence); service industries; statistical analysis; text analysis; customer satisfaction feedback records; customer support centers; enterprise CRM data; machine learning techniques; relative importance analysis; service quality components; services industry; statistical analysis; text analytics techniques; Customer satisfaction; Data mining; Dictionaries; Driver circuits; Industries; Pipelines;
Conference_Titel :
SRII Global Conference (SRII), 2011 Annual
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-61284-415-2
Electronic_ISBN :
978-0-7695-4371-0
DOI :
10.1109/SRII.2011.91