Effective Marketing Strategy Determination Based on Customers Clustering Using Machine Learning Technique. (February 2020)

• Record Type: Journal Article
• Authors: Andi Purnomo, Muhammad Ridwan; Azzam, Abdullah; Uswatun Khasanah, Annisa
• Is Part Of: Journal of physics. Volume 1471(2020)
• Publication Date: 2020-02
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1471/1/012023
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Marketing is one of the high cost activities in product sales. Therefore, effective marketing is a must in a company and it should be able to encourage customers to purchase more products. One of the efforts to determine effective marketing strategies is clustering the customers and formulating correct actions for every customer cluster. Today, most of companies have digital data including customer transaction data. Techniques to analyse digital data to discover knowledge behind the data is also developed from time to time. One of the techniques in digital data analysis that receives major attention from researchers is machine learning; a technique to enable computer to do learning in analysing the data. This study presents the process of customer clustering to determine effective marketing strategy using a machine learning technique. Customers would be analysed based on 3 parameters, which are last date of coming (recency/R), purchase frequency (frequency/F) and total money spent for product purchased (monetary/M). Such method is known as RFM method. Result of this study shows that the proposed machine learning could be used to cluster the customers and the customer clusters could be used as the basis for marketing manager to determine suitable marketing strategy for every customer clusters.