The Use of Clustering Methods and Machine Learning Algorithms in the Trading Enterprise for Customer Segmentation
Mieczyslaw Pawlowski and
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Mieczyslaw Pawlowski: Onninen sp. z o.o., Poland
Jaroslaw Banaœ: Maria Curie-Sklodowska University in Lublin, Poland
In the activity of any enterprise, it is essential to prepare a specific offer tailored to the needs of commercial customers. Large operation scale of businesses often makes it impossible to prepare individual offers for all customers, mainly for economic and logistical reasons. Therefore, it is important to appropriate customer grouping for the preparation of a proper offer to each group. Nowadays, it is difficult to separate the relevant groups characterized by a specific purchasing profile due to the dynamism of events in the modern economy and frequent changes in customer preferences. In order to maintain the current divisions, this classification must be done relatively often. The search for appropriate models and benchmarks is a continuous process. Enterprises use various methods to classify their customers. These methods are characterized by various degrees of complexity and varying effectiveness. This paper presents the results of analyses of customer segmentation in a trading enterprise, using clustering methods.
Keywords: clusters; clustering methods; customer segmentation; customized offer; enterprise. (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:tkp:mklp16:723-730
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