IDEAS home Printed from https://ideas.repec.org/a/air/journl/v3y2016i1p61.html

Measuring Customers Satisfaction of E-Commerce Sites Using Clustering Techniques: Case Study of Nyazco Website

Author

Listed:
  • Ali Rezaeian
  • Sajjad Shokohyar
  • Fariba Dehghan

Abstract

Today the use of modern technologies in the daily life for satisfying the needs is unavoidable. Follow the news and searching through the internet has affected organizations to provide platform on the Internet for availability of information for the customers. With the development of e-commerce, online shopping plays an increasingly important role in people’s life. With the use of data mining technique prospect, managers of this site can analyze preferences and purchasing patterns of online customers in order to custom product recommendations. Data mining helps to provide services in accordance with customers’ requirements. The aim of this research is to identify the customers’ requirements in online shopping and cluster these customers based on independent attributes such as gender, product classification, recency, frequency and monetary. For this purpose, the data related to Nyazco website that is an e-commerce website with a variety of products, were examined as a case study in the period of 7 months. The authors of this paper will define four clusters by using k-means algorithm and RFM model by IBM SPSS Modeler 14.2 software. Customers in the third cluster and fourth cluster will be identified as the most important customers. Therefore, providing the demands of these customers should be prioritized.

Suggested Citation

  • Ali Rezaeian & Sajjad Shokohyar & Fariba Dehghan, 2016. "Measuring Customers Satisfaction of E-Commerce Sites Using Clustering Techniques: Case Study of Nyazco Website," International Journal of Management, Accounting and Economics, International Journal of Management, Accounting and Economics, vol. 3(1), pages 61-74.
    • Handle: RePEc:air:journl:v:3:y:2016:i:1:p:61
    DOI: 10.5281/zenodo.17405469
    as

    Download full text from publisher

    File URL: https://www.ijmae.com/article_115230_0c3a47a281c93d17be29146da83fb7c0.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.5281/zenodo.17405469?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:air:journl:v:3:y:2016:i:1:p:61. 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: Dr. Behzad Hassannezhad Kashani (email available below). General contact details of provider: https://www.ijmae.com/ .

    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.