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

Myint Zaw and Pichaya Tandayya
Additional contact information
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

International Journal of Business Analytics (IJBAN), 2020, vol. 7, issue 4, 43-62

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.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJBAN.2020100104 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jban00:v:7:y:2020:i:4:p:43-62

Access Statistics for this article

International Journal of Business Analytics (IJBAN) is currently edited by John Wang

More articles in International Journal of Business Analytics (IJBAN) from IGI Global
Bibliographic data for series maintained by Journal Editor ().