This thesis aims to describe the theoretical principles of customer segmentation using modern methods of cluster analysis and their practical verification in a commercial environment of utility company. The theoretical part of the thesis describes the principles of clustering analysis using K-means algorithm and hierarchical clustering algorithms. The SW support chapter deals with the possibilities of R, Rapid Miner and KXEN software tools. For the purpose of data processing the theoretical part describes SEMMA, 5A and CRISP methodologies. The practical part is focused on the analysis of homogeneity/heterogeneity of the energy market in the household segment in the utility company EON. Using data from company´s customer system, available external data and programming language R a hierarchical cluster analysis is processed. Through the analysis of gained clusters there are identified the main characteristics of particular clusters which are consequently examined from marketing usage perspectives.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:136527 |
| Date | January 2012 |
| Creators | JOANIDIS, Filip |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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