Web usage mining to improve the design of an e-commerce website: OrOliveSur.com

Web usage mining is the process of extracting useful information from users history databases associated to an e-commerce website. The extraction is usually performed by data mining techniques applied on server log data or data obtained from specific tools such as Google Analytics. This paper presents the methodology used in an e-commerce website of extra virgin olive oil sale called www.OrOliveSur.com. We will describe the set of phases carried out including data collection, data preprocessing, extraction and analysis of knowledge. The knowledge is extracted using unsupervised and supervised data mining algorithms through descriptive tasks such as clustering, association and subgroup discovery; applying classical and recent approaches. The results obtained will be discussed especially for the interests of the designer team of the website, providing some guidelines for improving its usability and user satisfaction.

► We present a complete analysis of web usage mining in the website OrOliveSur.com.
► Clustering, association rule and subgroup discovery techniques have been applied.
► Results show to the webmaster team interesting conclusions to improve the design.