Nowadays, marketing researchers are constantly striving to identify consumer behavior and therefore to find appropriate solutions for better and more effective sales and increase market share. In this regard, the purpose of the present study is the role of customer clustering in designing a targeted marketing model. The research method is applied and exploratory. The statistical population of the study was in the qualitative part of sales and marketing managers of IoT companies who were selected by non-random sampling method and 15 people were interviewed. The quantitative part also included all the customers of the companies surveyed. Due to the unlimited population of Morgan Table 384 persons were selected as the sample size. Data gathering tool was interview and questionnaire, which were used to assess the validity of the questionnaire by the opinions of marketing experts and Cronbach's alpha reliability. Content analysis approach was used to analyze the data in the qualitative part and PLS2 software in the structural part. The results showed that the dimensions of the model in the four main clusters were communication factors, behavioral factors, individual factors, and economic factors. Model performance is very high performance.
