Leveraging social network data for analytical CRM strategies : the introduction of social BI


Autoria(s): Rosemann, Michael; Eggert, Mathias; Voigt, Matthias; Beverungen, Daniel
Contribuinte(s)

Pries-Heje, Jan

Chiasson, Mike

Data(s)

2012

Resumo

The skyrocketing trend for social media on the Internet greatly alters analytical Customer Relationship Management (CRM). Against this backdrop, the purpose of this paper is to advance the conceptual design of Business Intelligence (BI) systems with data identified from social networks. We develop an integrated social network data model, based on an in-depth analysis of Facebook. The data model can inform the design of data warehouses in order to offer new opportunities for CRM analyses, leading to a more consistent and richer picture of customers? characteristics, needs, wants, and demands. Four major contributions are offered. First, Social CRM and Social BI are introduced as emerging fields of research. Second, we develop a conceptual data model to identify and systematize the data available on online social networks. Third, based on the identified data, we design a multidimensional data model as an early contribution to the conceptual design of Social BI systems and demonstrate its application by developing management reports in a retail scenario. Fourth, intellectual challenges for advancing Social CRM and Social BI are discussed.

Identificador

http://eprints.qut.edu.au/51388/

Publicador

AIS Electronic Library (AISeL)

Relação

http://aisel.aisnet.org/ecis2012/95

Rosemann, Michael, Eggert, Mathias, Voigt, Matthias, & Beverungen, Daniel (2012) Leveraging social network data for analytical CRM strategies : the introduction of social BI. In Pries-Heje, Jan & Chiasson, Mike (Eds.) Proceedings of the 20th European Conference on Information Systems (ECIS) 2012, AIS Electronic Library (AISeL), Barcelona, Spain.

Fonte

School of Information Systems; Science & Engineering Faculty

Palavras-Chave #080600 INFORMATION SYSTEMS #Social network #Business intelligence #Social business intelligence #Data warehouse #Conceptual modeling
Tipo

Conference Paper