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Regression Analysis in Global Marketing: A Data-Driven Quantitative Approach to International Marketing Performance

by Ramjeet Singh Yadav
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 64
Year of Publication: 2025
Authors: Ramjeet Singh Yadav
10.5120/ijca2025926085

Ramjeet Singh Yadav . Regression Analysis in Global Marketing: A Data-Driven Quantitative Approach to International Marketing Performance. International Journal of Computer Applications. 187, 64 ( Dec 2025), 42-47. DOI=10.5120/ijca2025926085

@article{ 10.5120/ijca2025926085,
author = { Ramjeet Singh Yadav },
title = { Regression Analysis in Global Marketing: A Data-Driven Quantitative Approach to International Marketing Performance },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2025 },
volume = { 187 },
number = { 64 },
month = { Dec },
year = { 2025 },
issn = { 0975-8887 },
pages = { 42-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number64/regression-analysis-in-global-marketing-a-data-driven-quantitative-approach-to-international-marketing-performance/ },
doi = { 10.5120/ijca2025926085 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-12-18T17:50:14.016450+05:30
%A Ramjeet Singh Yadav
%T Regression Analysis in Global Marketing: A Data-Driven Quantitative Approach to International Marketing Performance
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 64
%P 42-47
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Global marketing presents complex challenges due to variations in consumer behaviour, economic conditions, cultural influences, and competitive dynamics across nations. Multinational corporations must rely on data-driven approaches to optimize advertising, pricing, and promotional strategies for international success. Regression analysis serves as a powerful quantitative method to explore relationships between marketing efforts and performance outcomes. This research utilizes multiple linear regression to assess how advertising expenditure and product pricing impact sales revenue in five countries: the USA, UK, India, Japan, and Brazil. Using the least squares estimation technique, the study determines regression coefficients that best fit the observed data. The resulting model achieves a coefficient of determination (R²) of 0.873, reflecting strong explanatory accuracy and reliability. Step-by-step computations of predicted sales, residuals, and model fit measures further validate the analysis. The findings highlight a significant positive correlation between advertising expenditure and sales performance, while an inverse relationship between product price and sales revenue underscores the sensitivity of global consumers to price variations. Overall, the study confirms that regression modelling is an essential analytical tool for crafting data-driven strategies in global marketing management, offering both theoretical and practical insights for international business decision-making.

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Index Terms

Computer Science
Information Sciences

Keywords

Global marketing regression analysis advertising pricing sales revenue market sensitivity data-driven strategy