Work

Data-Driven Profit Maximization in Marketing Campaign: A Logistic Regression Approach.

Year: 2024

Type: conference-paper

Abstract: This paper investigates the application for predicting consumer responses in marketing campaigns using a comprehensive dataset encompassing demographic, behavioural, and purchasing data. Through extensive feature engineering, followed by constructing and evaluating a logistic regression model. Key predictors influencing consumer response are identified, shedding light on their impact. The findings underscore the significance of income levels and specific spending behaviours, particularly on products like fish and wine, in influencing consumer perceptions and campaign responses. Insights from this research contribute to refining marketing strategies aimed at maximizing consumer engagement and satisfaction.

Source: International Conference on Industrial and Business Engineering (ICIBE)

DOI: 10.1145/3716097.3716117

Author: Chongsen Ma

Institution: Monash University

Language: English

Topic: Customer churn and segmentation

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W4409869731

FWCI:

Cites: 19

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Related to: 10