ADS Capstone Chronicles Revised

1 Retail Analytics: Understanding Customer Behavior through Transaction Data Jesse Gutierrez Applied Data Science Master’s Program Shiley Marcos School of Engineering / University of San Diego jesusgutierrez@sandiego.edu Sultan Mahmud Rahat Applied Data Science Master’s Program​ Shiley Marcos School of Engineering / University of San Diego​ smahmudrahat@sandiego.ed u Verity Pierson Applied Data Science Master’s Program​ Shiley Marcos School of Engineering / University of San Diego​ vpierson@sandiego.edu

Title Note Retail Analytics: Understanding Customer Behavior through Transaction Data Author Note Jesse Gutierrez, Sultan Mahmud Rahat, and Verity Pierson KEYWORDS E-commerce, customer satisfaction, return on investment (ROI), user experience (UX), personalization, digital marketing. In the rapidly evolving e-commerce landscape, businesses are compelled to constantly adapt to new technologies and shifting consumer behaviors. The surge in online shopping, accelerated by recent global events like the COVID-19 global pandemic, has intensified competition, making innovation a must. As larger competitors increasingly dominate the market, gaining market share and compressing profit margins, our company faces significant challenges in efficiently allocating resources. These challenges include identifying high-value customer segments, optimizing marketing spending, and enhancing the user experience (UX) to foster loyalty. This project seeks to address these challenges by leveraging data-driven strategies to improve customer satisfaction and maximize return on investment (ROI). Our approach involves the 1 Introduction

ABSTRACT The e-commerce landscape is rapidly evolving, presenting significant challenges in resource allocation as large competitors gain market share and reduce margins. To remain competitive and ensure long-term success, it is crucial to retain customers and sustain profitability through innovative and data-driven strategies. This project aims to leverage data to optimize resource allocation, thereby enhancing customer satisfaction and maximizing ROI by tailoring the user experience. Motivated by the need to deliver efficient and cost-effective services, the organization must adopt a holistic approach to optimize business processes and scale operations. The project’s objectives include using consumer data to maximize sales and improve operational efficiency through applications in marketing campaigns, inventory management, price optimization, and sales forecasting. Potential roadblocks include data privacy concerns, integration challenges, and the need for continuous model updates to adapt to changing consumer behaviors. Addressing these challenges will require robust data governance policies and ongoing model refinement. By overcoming these challenges and harnessing the power of data, the company is in a position for success in the competitive e-commerce landscape.

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