The Classification of Internet Shop Customers based on the Cluster Analysis and Graph Cellular Automata

摘要

A key aspect of successively maintaining a store on the market is the analysis of customer typology. By understanding individual segments of consumers, entrepreneurs are able to make big profits. This article proposes the methodological approach of the decision support system for identifying Internet customer typology. The conceptual framework was developed and on this basis a prototype of an online shop for conducting experiments was developed. A group of randomly selected users was isolated, and on the basis of the obtained data their clustering was performed by cluster analysis. The typology of online shop users has been created. Additionally, by introducing a prediction mechanism based on the mathematical model of the Graph Cellular Automaton, the new customer can be quickly adjusted to the defined group of shop customers.