knowledge management
Automatic Customer Segmentation for Social CRM Systems
Adam Czyszczoń and Aleksander Zgrzywa
Politechnika Wrocławska, Faculty of Computer Science and Management,
Institute of Informatics,
Wybrzeże Wyspiańskiego 27, 50370 Wrocław, Poland
{adam.czyszczon,aleksander.zgrzywa}@pwr.wroc.pl
http://www.zsi.ii.pwr.wroc.pl
Abstract. This paper attempts to address the problem of the automatic customer segmentation by processing data collected in Social Customer Relationship Management (Social CRM) systems using Kohonen networks. Presented segmentation approach comprises classic loyaltyprofitability link model that is explicit for CRM, and new social media components direct to Social CRM. The result of presented approach is an analysis tool with data visualization for managers which significantly improves the process of customer segmentation. Presented research is supported by implementation of proposed approach by which experiments were conducted. Additionally, the experimental results showed that proposed method performed very close to k-means algorithm which indicate the correctness of the proposed approach.
Keywords: customer segmentation, CRM, Social CRM, clusterization,
SOM, unsupervised learning, ANN, data mining.
1
Introduction
To acquire competitive advantage many companies use the strategy of Customer
Relationship Management (CRM) what can be observed in growing interest in this domain. However, in recent years new element of strategic importance appeared called social media. In order to meet the changing expectations of customers needs, Social CRM (SCRM) systems represent new branch of CRM systems which is oriented on the use of social media.
With the emergence of a new family of CRM systems, there has arisen the need for developing tools supporting these systems. Although both CRM and SCRM systems have many analytical tools, still a lot of them impose the necessity of extensive data management and using external software packages
Adam Czyszczoń and Aleksander Zgrzywa
Politechnika Wrocławska, Faculty of Computer Science and Management,
Institute of Informatics,
Wybrzeże Wyspiańskiego 27, 50370 Wrocław, Poland
{adam.czyszczon,aleksander.zgrzywa}@pwr.wroc.pl
http://www.zsi.ii.pwr.wroc.pl
Abstract. This paper attempts to address the problem of the automatic customer segmentation by processing data collected in Social Customer Relationship Management (Social CRM) systems using Kohonen networks. Presented segmentation approach comprises classic loyaltyprofitability link model that is explicit for CRM, and new social media components direct to Social CRM. The result of presented approach is an analysis tool with data visualization for managers which significantly improves the process of customer segmentation. Presented research is supported by implementation of proposed approach by which experiments were conducted. Additionally, the experimental results showed that proposed method performed very close to k-means algorithm which indicate the correctness of the proposed approach.
Keywords: customer segmentation, CRM, Social CRM, clusterization,
SOM, unsupervised learning, ANN, data mining.
1
Introduction
To acquire competitive advantage many companies use the strategy of Customer
Relationship Management (CRM) what can be observed in growing interest in this domain. However, in recent years new element of strategic importance appeared called social media. In order to meet the changing expectations of customers needs, Social CRM (SCRM) systems represent new branch of CRM systems which is oriented on the use of social media.
With the emergence of a new family of CRM systems, there has arisen the need for developing tools supporting these systems. Although both CRM and SCRM systems have many analytical tools, still a lot of them impose the necessity of extensive data management and using external software packages
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