Hi!, Welcome to the Retail Analytics Project! This project explores and analyzes the rapidly increasing and growing retail sector, businesses continously seek innovative strategy to stay ahead of competition, improve customer satisfaction, and optimize operational efficiency.
This case study focuses on a retail company that has encountered challenges in understanding it's sales performance, customer engagement and inventory management. Through a comprenhensive data analysis approach, the company aims to identify high and low sales product.
The Retail Company has observed stagnant growth and decline customer engagement metrics over the past quarters. Initial assessments indicate potential issues in product performance variability, ineffective customer segmentation, and lack of insights into customer purchasing behavior. The company seeks to leverage its sales transaction data, customer profiles, and product inventory information to address the following key business problems:
Product Performance Variability: Identifying which products are performing well in terms of sales and which are not. This insight is crucial for inventory management and marketing focus.
Customer Segmentation: The company lacks a clear understanding of its customer base segmentation. Effective segmentation is essential for targeted marketing and enhancing customer satisfaction.
Customer Behaviour Analysis: Understanding patterns in customer behavior, including repeat purchases and loyalty indicators, is critical for tailoring customer engagement strategies and improving retention rates.
This repository provides a detailed walkthrough of the data analytics project, from data acquisition and cleaning to SQL analysis and insights generation. It serves as a practical example of integrating SQL for data-driven decision-making in retail analytics.
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