Package Analytics
Track session package performance, usage patterns, and revenue to optimise your service offerings.
Who This Is For
Coaches who sell session packages and want to understand which packages perform best, track usage rates, and make data-driven decisions about pricing and package structures.
What This Feature Does
Package Analytics provides detailed insights into your session packages, including sales volume, session utilisation, revenue per package type, and client retention metrics. Use these insights to refine your offerings and maximise revenue.
Sales Tracking
See how many of each package type you've sold over time.
Usage Rates
Track how quickly clients use their purchased sessions.
Revenue Analysis
Compare revenue generated by different package types.
Why This Feature Exists
Understanding which packages sell best and how clients use them helps you optimise your pricing strategy. You might discover that smaller packages have higher margins, or that larger packages improve client retention. Data-driven decisions lead to better business outcomes.
Key Metrics Explained
Packages Sold
Total number of each package type purchased within the selected period.
Session Utilisation Rate
Percentage of purchased sessions that have been used. Low rates may indicate clients are buying more than they can commit to.
Average Sessions Per Week
How frequently clients use sessions from their packages on average.
Revenue Per Package
Total revenue generated by each package type, helping identify your most profitable offerings.
Renewal Rate
Percentage of clients who purchase another package after completing one.
Expiration Rate
Percentage of packages that expire with unused sessions.
How to Access Package Analytics
Navigate to Analytics
Go to your coach dashboard and select "Analytics" or "Financial Reports" from the sidebar.
Select Package Tab
Choose the "Packages" tab to view package-specific analytics.
Filter by Date Range
Use the date picker to analyse specific periods (e.g., last month, last quarter, year-to-date).
Export Data
Download reports as CSV or PDF for offline analysis or record-keeping.
Client Retention Insights
Package analytics can reveal which package structures lead to better client retention. Clients on larger packages often show higher commitment and renewal rates.
The analytics dashboard shows:
- Clients who have renewed vs those who didn't
- Average client lifetime value by package type
- Common drop-off points (e.g., after first package expires)
- Package completion rates by client demographics
Optimising Your Packages
High Expiration Rate?
Consider offering packages with longer validity periods or fewer sessions. Clients may be overcommitting.
Low Renewal Rate?
Review client feedback and consider adding incentives for renewals, such as loyalty discounts or bonus sessions.
One Package Dominates Sales?
Evaluate whether other packages are priced or structured competitively. Consider retiring underperforming options.
Limitations & Important Notes
Analytics reflect data from bookings made through the platform only. Sessions booked externally are not tracked unless manually logged.
- Historical data is available from the date you started using packages
- Refunded packages are excluded from revenue calculations
- Expired unused sessions are tracked separately from used sessions
FAQs
Can I see which specific clients bought which packages?
Yes, you can drill down from the analytics overview to see individual client purchase history for each package type.
How often is the data updated?
Analytics are updated in real-time as bookings are made, sessions are completed, and packages are purchased.
Can I compare different time periods?
Yes, you can select two date ranges to compare performance side-by-side, such as this quarter vs last quarter.
Are subscription clients included in package analytics?
No, subscriptions have their own analytics section. Package analytics focus specifically on session packages with defined session counts.
Review package analytics monthly to identify trends early. Small adjustments to pricing or package structure can significantly impact your bottom line over time.