an integrated entropy/vikor model for customer clustering in targeted marketing model design (case study: iot technology services companies)

Today, marketing researchers are constantly trying to carefully examine consumer behavior and accordingly, provide appropriate solutions for better and more effective sales, which in turn will lead to an increase in their market share. in this regard, the purpose of this study is to investigate the role of customer clustering in the design of a targeted marketing model. the research method is applied and exploratory. the statistical population studied in the qualitative section was sales and marketing managers of companies providing internet of things technology services, and 15 people were selected for interviews by non-random and available methods. in the quantitative section, all the customers of the studied companies were included, and due to the unlimited nature of the society with morgan's table, 384 people were selected as the sample size. the data collection tools in this study were interviews and questionnaires, which used the opinions of marketing experts and reliability of cronbach's alpha to examine the validity of the questionnaire. in order to analyze the data, first decision methods such as entropy and vikor were used and then to analyze the results, structural equations obtained with pls2 software were used. the results showed that the dimensions of the model in question fall into four main clusters, communicational factors, behavioral factors, individual factors and economical factors that customers are classified according to the characteristics of using the services provided, are classified in these clusters.