Title :
Email Analytics for Support Center Performance Analysis
Author :
Ranjan, Kunal ; Dey, Lipika
Author_Institution :
Innovation Labs., Tata Consultancy Services, New Delhi, India
Abstract :
Despite the growth of social networks, emails still continue to be the building blocks of formal communication within any business organization. For many organizations, email-based information exchange provides the backbone for customer support centers. Analyzing these conversations can provide insights into domain process related lacunae and loopholes in that division and identify actionable methods to improve them. In this paper we present a framework along with several methods and metrics that provide insights about its current performance measures as well as identify the bottlenecks and their causes. We have also presented a new method for grouping emails according to the similarity of their content to derive problem-specific performance statistics.
Keywords :
customer relationship management; electronic mail; social networking (online); business organization; customer relationship management; customer service and support; customer support center performance analysis; email analytics; email-based information exchange; emails similarity; formal communication; lacunae; loopholes; problem-specific performance statistics; social networks; Algorithm design and analysis; Cascading style sheets; Clustering algorithms; Data mining; Electronic mail; Performance analysis; Postal services; Email-Analytics; clustering; performance analysis;
Conference_Titel :
Data Mining Workshop (ICDMW), 2014 IEEE International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4799-4275-6
DOI :
10.1109/ICDMW.2014.74