The objective of this case study is to provide actionable insights for a retail business based on their transactional data. These insights will inform strategic decision-making, enabling the business to optimize operations, enhance customer satisfaction, and increase profitability.
The dataset consists of retail transaction records, including details such as invoice number, stock code, quantity, price, invoice date, customer ID, and country.
Objective: Understand product popularity. SQL Query: Identify products with the highest total sales quantities. Business Meaning: Guide inventory management and marketing strategies.
Objective: Compare monthly sales to the average. SQL Query: Calculate monthly sales and compare to the overall average. Business Meaning: Identify trends, seasonal fluctuations, and areas needing attention.
Objective: Identify high-spending customers. SQL Query: Rank customers by total spend and filter for those spending over 1000. Business Meaning: Target marketing efforts and loyalty programs to high-value customers.
Objective: Identify top revenue-generating products. SQL Query: Rank products by total revenue generated. Business Meaning: Optimize inventory and pricing strategies.
Objective: Understand customer purchasing habits. SQL Query: Calculate the average time between purchases for each customer. Business Meaning: Identify loyal customers and optimize marketing strategies.
Objective: Segment customers based on recency, frequency, and monetary values. SQL Query: Implement an RFM model to categorize customers. Business Meaning: Tailor marketing strategies and retention efforts to different customer segments.
Objective: Identify the maximum number of consecutive days a customer makes purchases. SQL Query: Calculate the maximum consecutive days each customer made purchases. Business Meaning: Understand customer engagement and loyalty.
Objective: Analyze the average time for customers to reach a spending threshold. SQL Query: Calculate the average time or transactions for customers to reach a spending threshold. Business Meaning: Optimize marketing strategies and promotions to encourage quicker spending.
Objective: Segment customers into predefined groups based on their recency, frequency, and monetary values. SQL Query: Implement a Monetary model to categorize customers into predefined groups. Business Meaning: Identify customer segments for targeted marketing and retention efforts.
This case study demonstrates the use of SQL queries to analyze retail transaction data and extract actionable insights for a business. The insights gained from these queries can help the business optimize its operations, improve customer satisfaction, and increase profitability.