A machine learning-based predictive approach in evaluating consumer behavior

Bhoyar, Sanjay; Bhoyar, Punam; Shah, Mushtaq Ahmad

doi:10.47974/JSMS-1131

Open Access Research Article

A machine learning-based predictive approach in evaluating consumer behavior

Sanjay Bhoyarsanbhoyar@yahoo.comDepartment of Construction Management NICMAR UniversityDepartment of Construction Management National Institute of Construction Management and ResearchPune, Maharashtra, 411045, India0009-0009-4488-9212View full profile → , ^*Punam BhoyarCorresponding authorpunam.bhoyar@yahoo.comDepartment of MBA Indira Institute of ManagementDepartment of Management Indira Institute of ManagementPune, Maharashtra, 411033, India0009-0001-3116-7597View full profile → , Mushtaq Ahmad Shahggumushy@gmail.comSchool of Management and Commerce Lovely Professional UniversityPunjab, IndiaView full profile →

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pp. 1955–1963Vol. 26Issue 8November 2023DOI: 10.47974/JSMS-1131XML

Received:: 04 Apr 2023
Published Online:: 27 Nov 2023
Article type:: Research Article
Language:: EN
Article no.:: JSMS-1131
Pages:: 1955–1963

Abstract

Organizations today want to be extrapolative; they want to gain information and insights on every minutia of customers. Predictive analytics is one of the tools which has proved to be a cornerstone in customer centricity. Though analytics is used for performing customer analysis for decades, the manual approach to data management and analysis has constrained the functionalities. Professionals now leverage the individual information from demographics to purchase history and perform predictive analytics for optimal decision-making, business marketing and thus business growth. Here we apply the ensemble learning method for classification based on the monthly income and spending behaviour of customers. Secondly, we analyse customer satisfaction by applying an unsupervised learning clustering method based on similarity through different performance measures.

Keywords

Predictive analytics Customer segmentation K-means algorithm Classification algorithm Consumer behaviour

Subject Classifications

62H3091C20

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