This project presents a Power BI Dashboard designed to track and analyse Woolworths Everyday Rewards data across Sydney stores for the years 2023 and 2024. The goal of this dashboard is to provide business insights into customer registrations, transactions, and loyalty behaviour through interactive and visually engaging reports.

The dashboard helps stakeholders understand how the loyalty program performs over time, how customers are engaging with their rewards, and where opportunities exist to improve customer retention and redemption strategies.

KPI Cards

• Customers Registered (2023): 1,000
• Total Transactions (End of 2024): 5,508
• Total Transaction Amount: 876.14K
• Total Points Earned: 874K
• Total Points Redeemed: 42K

These metrics serve as key performance indicators to quickly assess overall loyalty engagement.

1. Line Chart – Customer Registrations Over Time
   Displays a positive growth trend in customer sign-ups across both years.

2. Line Chart – Points Earned vs. Points Redeemed
   Shows customer activity over time, revealing how earning and redemption trends evolve.

3. Tree Map – Points Earned by Store
   Highlights which Sydney stores contributed the most to the total points earned.

4. Donut Chart – Points Redeemed by Type
   Breaks down redemption categories:

   • Shopping Discount: 67.5%
   • Fuel Discount: 20.9%
   • Other Categories: 11.6%

5. Pie Chart – Member Status
   Visualises customer engagement status:

   • Active: 89%
   • Inactive: 5.5%
   • Suspended: 5.5%

6. Bar Chart – Top 10 Redeemers
   Identifies members with the highest points redemption.

7. Scatter Plot – Points Earned vs. Points Redeemed
   Shows the relationship between points earned and redeemed.

I created this dashboard to:

• Track customer growth over time.
• Compare earning vs. redemption trends to evaluate engagement.
• Identify top-performing stores and loyal customers.
• Highlight customer retention through active/inactive membership status.
• Support data-driven decision-making for loyalty program improvements.

• Power BI – Data modelling, DAX calculations, and interactive report design
• Excel / CSV – Source data for customer transactions and rewards
• Data Cleaning – Data transformed and prepared using Power Query