Evaluating the Effectiveness of Advertising Campaigns in the Fast-Food Industry Using an Analytical Engine

Purpose: The primary objective of this research is to explore the effectiveness of marketing campaigns using an analytics engine capable of processing and interpreting complex data sets. The study focuses on a specific case within the fast-food industry, where traditional marketing strategies are employed to promote new product launches. Design/Methodology/Approach: The methodology employed in this research entails a comprehensive analysis of a dataset titled 'Fast-food Marketing Campaign,' which records sales outcomes from various marketing initiatives across multiple locations. The dataset encompasses market size, location, promotion type, and weekly sales figures, offering a comprehensive view of the campaign's reach and effectiveness. This study utilizes descriptive statistics, predictive modeling through Light GBM (an enhanced decision tree algorithm), and regression analysis to identify key factors that influence the success of traditional marketing campaigns. Moreover, a user-friendly interface was developed using the Dash programming framework, ensuring marketers can easily visualize and interpret the analysis results. Findings: Descriptive analysis highlighted the variability in sales and store characteristics, while predictive analysis showed the model's ability to forecast sales outcomes accurately. Regression analysis further identified the most influential variables affecting campaign success, such as market size and specific promotions. The model's predictions aligned with actual sales data, confirming its effectiveness in capturing underlying data patterns and contributing to strategic marketing decisions. Practical Implications: This research holds substantial practical implications for marketing professionals, particularly in sectors where traditional campaigns continue to be pivotal. The development of an analytical interface enables dynamic data exploration, empowering marketers to make informed decisions based on comprehensive analysis results. This tool can significantly bolster the planning and execution of marketing strategies by providing insights into the factors that most significantly impact campaign success, thereby optimizing marketing investments and strategies. Originality/Value: This study's originality lies in its focused examination of traditional marketing campaigns within the context of a modern data analytics framework. By integrating advanced analytical techniques with traditional marketing data, this research bridges the gap between conventional marketing approaches and contemporary analytical methodologies.