Loyalty Statistics & Analytics

To wrap up the loyalty course, this lesson covers how to evaluate the performance of your loyalty program. Understanding the distinct differences between your analytics data and your statistics data allows you to track customer behavior, monitor outstanding point liabilities, and identify which rewards are driving the most engagement.

Key Takeaways

• Analytics vs. Statistics: The dashboard splits your program performance tracking into two distinct frameworks:

  • Analytics: Measures how your customers interact with your program (e.g., participation and redemption rates). These metrics are fixed to a rolling 30-day period.

  • Statistics: Focuses on the program's absolute numbers (e.g., total transactions and point balances). These metrics can be filtered using fully customizable date ranges.

• Evaluating Customer Analytics: The Analytics tab provides a 30-day snapshot of community engagement:

  • Active Contacts & Participation: Shows the total number and percentage of your database actively engaging with the program.

  • Repeat Loyalty Participation: Tracks how many members perform a loyalty transaction or activity more than once.

  • Top Redeemed Rewards: Pinpoints exactly which perks your customers prefer, giving you insights into what drives real engagement.

  • Time to First Redemption & Reactivation Potential: Measures how quickly new users claim their first reward (lower time indicates better onboarding friction). It also highlights inactive contacts who currently hold unused points, identifying prime targets for win-back marketing campaigns.

• Monitoring Program Statistics: The Statistics tab lets you dig into historical data using tailored date ranges and location filters:

  • Outstanding Balance: Displays the total volume of points your customers hold that have not yet been redeemed—representing your current point liability.

  • Average Monthly Spending: Calculates the average monthly revenue generated per member over a selected timeframe.

  • Points Issued vs. Redeemed: Tracks the volume of points entering circulation against those being spent.

  • Granular Transaction Types: Breaks down data by the number of unit point transactions and direct point transactions.

• Location-Based Benchmarking: Most statistics can be filtered down to specific business profiles or brick-and-mortar storefronts (e.g., filtering data strictly for an Amsterdam store). This allows you to benchmark performance across different locations and see which shops are driving the highest active participation.

Dashboard Checklist

1. Navigate to Loyalty > Analytics to review your rolling 30-day customer behavior metrics, tracking your top-performing rewards and inactive lists.

2. Switch to the Statistics tab to monitor overall program totals and point liabilities.

3. Use the date selector to input a custom date range (such as comparing January against February) to observe performance trends over time.

4. (Optional) Click the location drop-down menu to isolate statistic fields to a single store profile.

5. Click Calculate after adjusting any dates or locations to instantly refresh and update the on-screen data.