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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