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Product Categorization for Social Marketing Applying the RFC Model and Data Science Techniques

Author

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  • Myint Zaw

    (Department of Computer Engineering, Faculty of Engineering, Prince of Songkla University, Thailand)

  • Pichaya Tandayya

    (Department of Computer Engineering, Faculty of Engineering, Prince of Songkla University, Thailand)

Abstract

Currently, it is the age of social market due to the growth of internet technologies. The marketers require the complete information of customer perspectives on products and services comparing with others. The RFM (recency, frequency, and monetary) model is a technique to measure a comparison of information, especially in traditional market analytics. Over the past decade, social market big data (SMBD), especially feedback, has been used to understand customer satisfaction. This paper proposes a new approach to classify the products from feedbacks, called the RFC (recency, frequency, and credit) model. The model focuses on the social market information and product categorization applying the natural language processing (NLP), opinion mining (OM), and data mining (DM) techniques.

Suggested Citation

  • Myint Zaw & Pichaya Tandayya, 2020. "Product Categorization for Social Marketing Applying the RFC Model and Data Science Techniques," International Journal of Business Analytics (IJBAN), IGI Global, vol. 7(4), pages 43-62, October.
    • Handle: RePEc:igg:jban00:v:7:y:2020:i:4:p:43-62
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