Title: Machine learning based classification and segmentation techniques for CRM: a customer analytics

Authors: Narendra Singh; Pushpa Singh; Krishna Kant Singh; Akansha Singh

Addresses: GL Bajaj Institute of Management and Research, Knowledge Park-III, Greater Noida, Uttar Pradesh, 201306, India ' Delhi Technical Campus, Knowledge Park-III, Greater Noida, Uttar Pradesh, 201306, India ' KIET Group of Institutions, Delhi-NCR, Ghaziabad, Uttar Pradesh, 201206, India ' ASET, Amity University, Uttar Pradesh, Noida, 201313, India

Abstract: Machine learning and data mining help companies to build a tool that can make and take actions based on customer knowledge and information. Customer information is the base of maintaining long term relationship with customers and also known as customer relationship and management (CRM). Classification and segmentation of customer data set is utilised to maintain efficient relation with customers and subsequently increase the profitability and productivity. In this paper, author proposed customer segmentation based on demographic properties like gender, age and spending score and analysed the data set for interesting fact. The derived attribute data set is investigated for classification. Classification is used to categorise each customer into a number of classes, i.e., 'gold', 'silver', 'elite' and 'occasional'. Comparison of different classification algorithm is simulated by WEKA tool. Multi-layer perceptron (MLP) is found as the best classification algorithm with an accuracy of 98.33% compared to Naïve Bayes, regression and J48.

Keywords: machine learning; classification; segmentation; customer relationship management; CRM; WEKA; multi-layer perceptron; MLP.

DOI: 10.1504/IJBFMI.2020.109878

International Journal of Business Forecasting and Marketing Intelligence, 2020 Vol.6 No.2, pp.99 - 117

Received: 06 Jan 2020
Accepted: 08 Jun 2020
Published online: 28 Sep 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article