Islamic Azad University (Tehran, Iran)
Islamic Azad University (Tehran, Iran)
Along with increasing competitiveness in the service industry to increase the number of customers and gain competitive advantage by creating customer satisfaction, using data mining concepts has attracted the attention of the researchers and the industries as a new tool for this purpose. In this regard, fast food industry, as an industry having an increasing growth during recent years, is considered as a very attractive market for the customers. The current study aims to utilize data mining algorithms to categorize the customers in fast food industry and propose marketing strategies tailored to each group of customers identified. The statistical population of this research includes the records submitted in the integrated system of Perperook chain restaurants, which is over 3000 records. Furthermore, the data mining algorithms, specifically decision tree and Quest algorithm, have been used in this study to categorize customers according to the orders submitted in the system. The results of this study indicate that the customers of Perperrok fast food can be categorized into three main groups: healthy, voluminous, and free-living customers. At the end of the research, detailed results and strategies associated with any of the main groups of customers are presented along with practical suggestions.
Keywords: customer relationship management, data mining, Apriori algorithm, decision tree
JEL Classification: M30, M31, M39.
Cite as: Kashani, F. & Shahmirzaloo Z. (2017). Developing marketing strategies using customer relationship management and data mining (case study: Perperook chain restaurants). Marketing and Management of Innovations, 3, 135-148. https://doi.org/10.21272/mmi.2017.3-13
This work is licensed under a Creative Commons Attribution 4.0 International License
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