Unsupervised Machine Learning Models for Focused Target Customer Segmentation

This research investigates novel methods for customer segmentation using advanced machine learning models. As digital marketing rapidly expands, accurately identifying target segments is crucial for optimizing campaign reach and enhancing return on investment (ROI). The study utilizes various clustering algorithms to identify the most effective approach. Essential processes include processing and preparing customer data, followed by applying widely-used machine learning algorithms.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-04-21
DOI
https://doi.org/10.52783/jisem.v10i38s.7072
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
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article

Unsupervised Machine Learning Models for Focused Target Customer Segmentation

Blessington Naveen Palaparthi
Journal of Information Systems Engineering & Management
Customer churn and segmentation
article

Unsupervised Machine Learning Models for Focused Target Customer Segmentation

Blessington Naveen Palaparthi
article en

Abstract

This research investigates novel methods for customer segmentation using advanced machine learning models. As digital marketing rapidly expands, accurately identifying target segments is crucial for optimizing campaign reach and enhancing return on investment (ROI). The study utilizes various clustering algorithms to identify the most effective approach. Essential processes include processing and preparing customer data, followed by applying widely-used machine learning algorithms.

Journal of Information Systems Engineering & ManagementVol. 10(38s)
Openalex Percentile: Top 89%
Customer churn and segmentation
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Unsupervised Machine Learning Models for Focused Target Customer Segmentation — Blessington Naveen Palaparthi · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS