Impact of Advertising Media on Sales Using Linear Regression Analysis
Abstract
Advertising plays a crucial role in influencing customer purchasing behaviour and enhancing overall business revenue. This study examines the relationship between advertising expenditure across three major media channels—TV, Radio, and Newspaper—and product sales using a supervised machine learning approach. A linear regression model is developed to predict sales performance based on the allocated advertising budgets. The dataset used in this study comprises 200 observations and four variables. Various techniques such as exploratory data analysis, model training, performance evaluation, and data visualization are applied to gain meaningful insights. The findings reveal that TV and Radio advertisements have a significantly stronger impact on sales compared to Newspaper advertisements. Overall, the proposed model demonstrates satisfactory prediction accuracy and offers valuable insights to support effective marketing decision-making.
Authors
Neeraj Mittal, Aman Kumar, Amarjeet Singh, Amit Kumar, Amit Raj
Institution
Noida Institute of Engineering & Technology (MCA Institute), Greater Noida

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