Telecom Market Segmentation Using the K-mean Algorithm and the Recency, Frequency and Monetary Value
Telecom Market Segmentation Using the K-mean Algorithm and the Recency, Frequency and Monetary Value

Summary/Abstract: Mobile phone operators aim to retain a large number of loyal subscribers. As a consequence, Relationship Marketing should have a central role in their activity. Operators seek to offer quality services, which cater to their subscribers‘ needs, so that subscribers not only show a great degree of satisfaction, but also return to the same provider in the future. To design and implement successful strategies and marketing programmes, these companies must segment their customers according to relevant criteria. The present study aims at identifying the different subscriber segments within a subscriber database according to the time of the last recharge, the recharge frequency over 2 months and the associated value. Thus, although the RFM model variables were used to segment the database, the K-mean cluster analysis was also employed. To estimate cluster internal cohesion, the Average Sum of Squares Error Indicator was used. Furthermore, to determine the difference between clusters, an ANOVA and a Tukey post-hoc test were used. The analyses returned a result of eight subscriber segments, each showing evidence of a different behaviour. The results are relevant for Telecom companies in that they must adapt their marketing strategies and programmes to their subscribers‘ needs.

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