Lucky Charms: Leveraging Consumer Data Analysis for Strategic Decision-Making at General Mills

Abstract

This undergraduate thesis examines the application of data analytics in sales strategy and consumer insights from the perspective of a summer internship at General Mills. It gives an overview of the company’s background, industry position, and intern’s role within the sales organization. It outlines the personal learning objectives established before the internship and how they evolved through practical experience. A central focus of the summer internship was the analysis of consumer demographics within the cereal category to enhance sales performance and optimize retail execution. Using the Data Science Analytics Process as a framework, this thesis details the problem statements, methodologies, and analytical approaches employed to complete the intern projects. By leveraging demographic data, purchasing patterns, and market segmentation, insights were generated to drive more effective product positioning and promotional strategies. A literature review contextualizes the project within existing research, evaluating relevant methodologies in sales analytics and their applicability to the internship assignment. Results highlight key insights gained, the impact of data-driven decision-making on sales operations, and recommendations for improving business performance. The analysis was conducted using Walmart Luminate, NielsenIQ, and E2Open, three business intelligence tools that provide data on consumer behavior, market trends, and sales dynamics. These tools enabled insights into sales performance and competitive positioning that were shared cross functionally with brand and supply chain teams. This thesis also discusses the challenges encountered in working with large-scale retail data and the strategic implications of these data-driven decisions. This thesis contributes to a broader understanding of how data analytics can be used to understand consumer behavior, optimize sales strategies, and drive growth within the cereal market. It offers a practical intern perspective on the growing role of data science in the corporate sales environments, particularly within the consumer-packaged goods (CPG) industry