GlobalMart has plenty of customer data, but it’s scattered across
customers, orders, transactions, and returns, making it hard to see how each customer really behaves. You will be
wearing the hat of a Data Analyst and building the
SQL backbone of a
customer loyalty program from scratch.
You will :
- Join multi-table data into a clean customer-level summary using INNER/LEFT JOINs, GROUP BY, WHERE vs HAVING, and CTEs to manage complex logic.
- Compute loyalty-ready metrics like total orders, total returns, average basket size, average basket value, length of stay, and purchase frequency.
By the end, you’ll have a working customer profile query that a marketing team could plug directly into real-world loyalty campaigns, retention initiatives, and high-value customer analysis, exactly the kind of SQL work analysts are trusted to deliver on the job.
TM
