Researching and analyzing - user behavior on websites that sell fruit, giving solutions for supporting smart business decisions

Abstract

The phrase “Data is the new oil” implies the abundance of both resources: Oil and data. However, if both remain in their “raw” states, they bring little value. Therefore, accurate data collection and thorough analysis form the core value of data. Simultaneously, this process helps organizations classify and clarify customer needs, leading to innovative breakthroughs in business. To optimize the analysis of data from its raw components, clustering methods are employed as an approach to better engage with the inherent values they offer. This article explores clustering methods using the K-Means algorithm. The analysis is based on over 1,000 orders, resulting in clusters of customers with similar shopping behaviors. Consequently, through this classification process, organizations can develop distinct business strategies tailored to each customer group, as well as adopt effective approaches to the broader service industry.