Customer segmentation with cluster analysis based on CRM applications for digital marketing activities in the pharmaceutical industry

Nowadays, digital marketing activities in the pharmaceutical industry have become a strategic tool. Besides, in the pharmaceutical industry where digitalization has accelerated in recent years, companies aim to reach out their customers easily and quickly using their digital marketing practices together with various data mining algorithms. This study's aims are, segmentation and analysis of the customers of a leading multinational Pharmaceutical company in Turkey using data mining algorithms. With emphasis on the main focuses of the study which are, digital marketing and CRM. Concepts of data mining and algorithms are examined in detail. The data set was used in this study shows the accessibility of the healthcare professionals who were based in Turkey according to the digital marketing channels. K-means and two step algorithms were used to be able to segment the healthcare professionals in reference to times of access to the digital marketing channels. The data set was run in SPSS Clementine program for 3 different models and it was aimed to analyze the clusters obtained and to decide which digital marketing channel to approach to which customer set. This clustering study was found to be very useful in the sector as it facilitates the applicability of the analysis to a large number of data sets and saves time. With the outputs obtained from this analysis, the company has benefited from the ease of selection of the digital marketing activities to be applied to the customer clusters. In terms of the privacy principles, no demographic data or personal information was used to protect confidentiality of the healthcare professionals and only the numbers of access to the marketing channels were used. In the application, SPSS Clementine program was used to analyze the data set. Keywords: Data Mining, Clustering, Digital Marketing, Clustering in the Pharmacetical Industry, SPSS Clementine, K-Means, Customer Clustering.