RFM-BASED CUSTOMERS CLUSTERING FOR PRECISE INDUSTRIAL MARKETING STRATEGY FORMULATION
Abstract
In the information age, digital marketing which covers data processing and spreading of digital information is an effective marketing strategy alternative. In industrial sector, marketing is one of the costly activities, therefore, it needs to be carried out accurately. This study discusses an accurate industrial marketing strategy formulation based on customers purchasing behaviour. Customer sales data were analysed by a well-known method, namely Recency, Frequency, and Monetary (RFM) combining with data analytics technique. Results indicated that data analytics could improve the preciseness of the conventional RFM by considering non-profit customers and provide real-time data. This research gives another insight on improving conventional RFM analysis effectiveness as a simple and widely used tool for marketers.
Downloads
Authors who publish with this journal agree to the following terms:
- Authors transfer copyright to the publisher as part of a journal publishing agreement with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after the manuscript is accepted, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
