Title :
A Framework for Improving Enterprise Services by Mining Customer Edge Data
Author :
Raghavan, Preethi ; Ramanathan, Jay ; Ramnath, Rajiv ; Xu, Zhe
Author_Institution :
Dept. of Comput. Sci. & Eng., Ohio State Univ. Columbus, Columbus, OH, USA
fDate :
June 29 2009-July 1 2009
Abstract :
The dynamic business nature of many organizations makes it necessary to sense and interpret the impact of external customer data on the business environment and the functioning of the enterprise. We present a framework for 1) capturing structure, patterns and trends and analyzing the latent ´voice of the customer´ from unstructured data and 2) intra-enterprise decisions that increase the value to the customer. Thus we demonstrate how an analysis of enterprise edge data using the proposed framework, helps discover and enhance customer value and respond accordingly. A proof of concept implementation using the developed - dasiaopinion mining toolpsila, is used to demonstrate how application of the framework helps improve certain business processes, and achieve the goals listed above, in a news organization.
Keywords :
business data processing; customer satisfaction; data mining; marketing data processing; customer edge data mining; customer value; enterprise services; intraenterprise decision; opinion mining tool; Competitive intelligence; Conferences; Data mining; Decision making; Demography; Information services; Internet; Pattern analysis; Speech analysis; Web sites; business strategy; edge data; opinion mining; sense-respond; voice of the customer;
Conference_Titel :
Enabling Technologies: Infrastructures for Collaborative Enterprises, 2009. WETICE '09. 18th IEEE International Workshops on
Conference_Location :
Groningen
Print_ISBN :
978-0-7695-3683-5
DOI :
10.1109/WETICE.2009.32