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

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

Myint Zaw, Pichaya Tandayya
Copyright: © 2020 |Volume: 7 |Issue: 4 |Pages: 20
ISSN: 2334-4547|EISSN: 2334-4555|EISBN13: 9781799808169|DOI: 10.4018/IJBAN.2020100104
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MLA

Zaw, Myint, and Pichaya Tandayya. "Product Categorization for Social Marketing Applying the RFC Model and Data Science Techniques." IJBAN vol.7, no.4 2020: pp.43-62. http://doi.org/10.4018/IJBAN.2020100104

APA

Zaw, M. & Tandayya, P. (2020). Product Categorization for Social Marketing Applying the RFC Model and Data Science Techniques. International Journal of Business Analytics (IJBAN), 7(4), 43-62. http://doi.org/10.4018/IJBAN.2020100104

Chicago

Zaw, Myint, and Pichaya Tandayya. "Product Categorization for Social Marketing Applying the RFC Model and Data Science Techniques," International Journal of Business Analytics (IJBAN) 7, no.4: 43-62. http://doi.org/10.4018/IJBAN.2020100104

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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.

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