IDEAS home Printed from https://ideas.repec.org/a/prg/jnlaip/v2023y2023i2id220p357-378.html
   My bibliography  Save this article

Segmenting Customers with Data Analytics Tools: Understanding and Engaging Target Audiences

Author

Listed:
  • Tomáš Pitka
  • Jozef Bucko

Abstract

This paper presents a decision support system for identifying customer typology using cluster analysis to segment relevant customers. The approach is demonstrated using data from a company selling nutritional supplements, consisting of approximately 130,000 records from six Central European countries. The analysis results in distinct groups of customers, which are proposed for more effective management of customer relationships. The findings have implications for retailers, helping them focus on the most profitable customer segments to increase sales and profits and build lasting relationships. Furthermore, cluster analysis proves to be an appropriate statistical method for classification and provides valuable insights into patterns and trends in the analysed data. Overall, this paper contributes to development and comparison of methods for customer segmentation and demonstrates their potential for improving economic efficiency and building long-term customer relationships.

Suggested Citation

  • Tomáš Pitka & Jozef Bucko, 2023. "Segmenting Customers with Data Analytics Tools: Understanding and Engaging Target Audiences," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2023(2), pages 357-378.
    • Handle: RePEc:prg:jnlaip:v:2023:y:2023:i:2:id:220:p:357-378
    DOI: 10.18267/j.aip.220
    as

    Download full text from publisher

    File URL: http://aip.vse.cz/doi/10.18267/j.aip.220.html
    Download Restriction: free of charge
    File URL: http://aip.vse.cz/doi/10.18267/j.aip.220.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.18267/j.aip.220?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:prg:jnlaip:v:2023:y:2023:i:2:id:220:p:357-378. 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: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.html .

    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.