Analysing Segmentation and Behavioural Dynamics in Customer Purchase Behavior

Consumer behavior is one of the most vital aspects of business, given the need to make an enterprise competitive in the market by improving marketing efforts and the product range. The project goes further into the actual segmentation and analysis of consumer behavior in relation to purchase through data analytics and machine learning for the identification of significant trends and patterns. The most important outcome of this phase is that a mere 1% of customers are able to fairly estimate delivery timings, hence showing the most room for further advancement. The implementation also takes place of an intelligent product recommendation system that personalizes product recommendations for a greatly enhanced customer experience. The paper provides strategic recommendation for optimal promotion, steering clear of purchase slumps, e.g. on Saturdays. The outcome is tangible insight for businesses by which they can fine- tune strategies adopted to elevate customer satisfaction. Keywords: Consumer Behaviour, Segmentation, Machine Learning, Data Analytics, Patterns of Purchase, Marketing strategy

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2024-08-31
DOI
https://doi.org/10.55041/ijsrem37271
Primary Topic
Consumer Retail Behavior Studies
Type
article
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article

Analysing Segmentation and Behavioural Dynamics in Customer Purchase Behavior

Ms. Aangi Khandhar, Sweety Garg
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Consumer Retail Behavior Studies
article

Analysing Segmentation and Behavioural Dynamics in Customer Purchase Behavior

Ms. Aangi Khandhar, Sweety Garg
article en

Abstract

Consumer behavior is one of the most vital aspects of business, given the need to make an enterprise competitive in the market by improving marketing efforts and the product range. The project goes further into the actual segmentation and analysis of consumer behavior in relation to purchase through data analytics and machine learning for the identification of significant trends and patterns. The most important outcome of this phase is that a mere 1% of customers are able to fairly estimate delivery timings, hence showing the most room for further advancement. The implementation also takes place of an intelligent product recommendation system that personalizes product recommendations for a greatly enhanced customer experience. The paper provides strategic recommendation for optimal promotion, steering clear of purchase slumps, e.g. on Saturdays. The outcome is tangible insight for businesses by which they can fine- tune strategies adopted to elevate customer satisfaction. Keywords: Consumer Behaviour, Segmentation, Machine Learning, Data Analytics, Patterns of Purchase, Marketing strategy

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 08(008)
Industry, innovation and infrastructure
Openalex Percentile: Top 80%
Consumer Retail Behavior Studies
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Analysing Segmentation and Behavioural Dynamics in Customer Purchase Behavior — Ms. Aangi Khandhar, Sweety Garg · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2024) | TGRS Research Map | TGRS