The Role of Customer Segmentation in Engineering Innovation: A Green Approach

ABSTRACT In this digital era the behaviour of customers has undergone a profound transformation due to easy accessibility of internet and smart engineering technologies. Many industries, businesses, companies and organizations are offering the services to them. The market is very competitive so there is a need to adopt a technology as per customer expectations to cope up with these problems. The customer segmentation is one the best way to rectify these problems. This method is based upon to grouping customers based on similarities to tailor offerings and experiences. With the help of these segments, they can better meet specific needs and can build a best customer relationship. This paper explores how traditional and advanced customer segmentation methods such as K-Means Clustering, Principal Component Analysis, decision Tree Classifier, Elbow Method etc. to engineering innovation and highlights the intersection of customer analytics and engineering design, provide customize solutions. Keywords: Customer Segmentation, K-Means Clustering, Principal Component Analysis (PCA), Decision Tree Classifier, Marketing Strategy.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-24
DOI
https://doi.org/10.55041/ijsrem48679
Primary Topic
Big Data and Business Intelligence
Type
article
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article

The Role of Customer Segmentation in Engineering Innovation: A Green Approach

Sunil Issar
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Big Data and Business Intelligence
article

The Role of Customer Segmentation in Engineering Innovation: A Green Approach

Sunil Issar
article en

Abstract

ABSTRACT In this digital era the behaviour of customers has undergone a profound transformation due to easy accessibility of internet and smart engineering technologies. Many industries, businesses, companies and organizations are offering the services to them. The market is very competitive so there is a need to adopt a technology as per customer expectations to cope up with these problems. The customer segmentation is one the best way to rectify these problems. This method is based upon to grouping customers based on similarities to tailor offerings and experiences. With the help of these segments, they can better meet specific needs and can build a best customer relationship. This paper explores how traditional and advanced customer segmentation methods such as K-Means Clustering, Principal Component Analysis, decision Tree Classifier, Elbow Method etc. to engineering innovation and highlights the intersection of customer analytics and engineering design, provide customize solutions. Keywords: Customer Segmentation, K-Means Clustering, Principal Component Analysis (PCA), Decision Tree Classifier, Marketing Strategy.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Openalex Percentile: Top 81%
Big Data and Business Intelligence
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