Data Analysis Using Cluster and Logistic Regression Analysis (A Case Study)

Authors

  • Puspa Byanjankar Department of Computer Science and Engineering, Kathmandu University, Nepal
  • Kabindra Marhatta Department of Computer Science and Engineering, Kathmandu University, Nepal
  • Yushma Himanshu Department of Computer Science and Engineering, Kathmandu University, Nepal

DOI:

https://doi.org/10.58776/ijitcsa.v1i1.14

Keywords:

business clients, logistic regression, cluster analysis, consulting services and training product, purchase

Abstract

Customer loyalty has been a concern to C&M. C&M implements logistic regression and cluster analysis to tackle customer churn on consulting services and products. Logistic regression analysis predicts whether chemical manufacturers and small personal services will purchase consulting services and training products with discount reduction in 18 months. Their pur-chase choices every 18 months are influenced by discounts or non-discount. Cluster analysis groups purchase power based on the age group. It forecasts business client’s transaction through purchase duration and frequent purchase on consulting services and items. Thus, C&M builds a long-term relationship with chemical manufacturers and small personal ser-vices by creating customer satisfaction on our consulting services and products.

Author Biographies

Puspa Byanjankar, Department of Computer Science and Engineering, Kathmandu University, Nepal

 

Kabindra Marhatta, Department of Computer Science and Engineering, Kathmandu University, Nepal

 

Yushma Himanshu, Department of Computer Science and Engineering, Kathmandu University, Nepal

 

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Published

14-01-2023

How to Cite

Byanjankar, P., Marhatta, K., & Himanshu, Y. (2023). Data Analysis Using Cluster and Logistic Regression Analysis (A Case Study). International Journal of Information Technology and Computer Science Applications, 1(1), 1–10. https://doi.org/10.58776/ijitcsa.v1i1.14

Issue

Vol. 1 No. 1 (2023): January - April 2023

Section

New Submission

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Copyright (c) 2023 Puspa Byanjankar, Kabindra Marhatta, Yushma Himanshu

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