IDEAS home Printed from https://ideas.repec.org/h/tkp/mklp16/723-730.html
   My bibliography  Save this book chapter

The Use of Clustering Methods and Machine Learning Algorithms in the Trading Enterprise for Customer Segmentation

Author

Listed:
  • Mieczyslaw Pawlowski

    (Onninen sp. z o.o., Poland)

  • Jaroslaw Banaœ

    (Maria Curie-Sklodowska University in Lublin, Poland)

Abstract

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.

Suggested Citation

  • Mieczyslaw Pawlowski & Jaroslaw Banaœ, 2016. "The Use of Clustering Methods and Machine Learning Algorithms in the Trading Enterprise for Customer Segmentation," Managing Innovation and Diversity in Knowledge Society Through Turbulent Time: Proceedings of the MakeLearn and TIIM Joint International Conference 2016,, ToKnowPress.
    • Handle: RePEc:tkp:mklp16:723-730
    as

    Download full text from publisher

    File URL: http://www.toknowpress.net/ISBN/978-961-6914-16-1/papers/ML16-133.pdf
    File Function: full text
    Download Restriction: no
    File URL: http://www.toknowpress.net/ISBN/978-961-6914-16-1/MakeLearn2016.pdf
    File Function: Conference Programme
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tkp:mklp16:723-730. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Maks Jezovnik (email available below). General contact details of provider: http://www.toknowpress.net/proceedings/978-961-6914-16-1/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.