Performance Optimization of an Enterprise using Data-Driven Strategy

Authors

  • Divya Jatain Assistant Professor, Department of Computer Science & Engineering, Maharaja Surajmal Institute of Technology, New Delhi, India

Keywords:

Classification, Customer segmentation, K-Means, Machine Learning, RFM analysis

Abstract

In this digital age, where data is ubiquitous, it is crucial to transform it into information to obtain useful insights that power growth. Considering the need for the appropriate deployment of socio-technical systems to benefit modern businesses, this paper focuses on using customer segmentation backed by Recency-Frequency-Monetary analysis, as its basis in order to attain marketing and sales excellence, understand consumer behaviour, and transform customer success. The project encompasses analysing data of the purchases made through an online retail company over the duration of a year. Thereafter, the customers are segmented using K-Means clustering technique. It is then followed by classification of customers, for which five classification techniques are implemented. The best result is shown by Random Forest classifier which is then used to understand customer behaviour.

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Published

25-11-2022

Issue

Section

Articles

How to Cite

[1]
D. Jatain, “Performance Optimization of an Enterprise using Data-Driven Strategy”, IJRESM, vol. 5, no. 11, pp. 113–117, Nov. 2022, Accessed: Jun. 17, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/2436