Compare events
The Compare events tab lets you analyze multiple events or dates side by side, helping you identify patterns, benchmark performance, and make data-driven decisions for future events.
Accessing comparison
From the Fanz dashboard, go to Reports → Compare events.
Selection sidebar
On the left side you have the selection controls:
Compare mode toggle
Switch between two modes:
| Mode | What it compares |
|---|---|
| Events | Compare entire events (all dates combined) |
| Dates | Compare specific event dates |
Compare button
- Disabled until you select at least 1 event/date
- Enabled when selection is valid (1-6 items)
- Click to load comparison data
Clear selection
When you have items selected, an X icon appears next to the Compare button. Click it to clear all selections.
Selecting events
In Events mode, you see event cards with:
- Checkbox on the left
- Event name
- Number of dates
- Location
To select: Click the checkbox or the card. Selected events are highlighted.
Search and filter
Above the event list:
- Search: Find events by name
- Category filter: Show only events from a specific category
Selecting dates
In Dates mode, event cards work as expandable dropdowns:
- Click on an event card to expand it
- See all available dates for that event
- Click on a date to select it
- Click again to deselect
Date format shown:
- 3-letter month (Jan, Feb, etc.)
- Day number
- Time below
Selection limits
- Minimum: 1 event/date
- Maximum: 6 events/dates
Once you have a valid selection, click Compare to see the results.
Comparison table
After clicking Compare, the comparison data loads on the right.
Note: Events/dates with no sales will not appear in the comparison.
Each selected event/date gets a column with these metrics:
| Metric | Description |
|---|---|
| Tickets sold | Total quantity of tickets sold |
| Sell-through % | Tickets sold as percentage of total capacity |
| Repeat rate % | Percentage of buyers who are returning customers |
| Show rate % | Percentage of ticket holders who actually attended (validated) |
| Net revenue | Revenue after Fanz fees, processor fees, and taxes |
Understanding each metric
Tickets sold
Raw number of tickets sold. Use this to compare absolute demand across events.
How to use it:
- Identify which events generate most volume
- Compare similar events to find what works
- Track growth over time for recurring events
Sell-through percentage
(Tickets sold ÷ Total capacity) × 100
Shows how much of your available inventory you sold.
How to use it:
- 90%+: High demand—consider larger venue or more dates
- 70-90%: Healthy sales—good pricing and marketing
- 50-70%: Room for improvement—review marketing or pricing
- Below 50%: Investigate causes—wrong audience, pricing, timing?
Repeat rate percentage
Percentage of buyers who have purchased from your brand before.
How to use it:
- High repeat rate: Strong brand loyalty—reward them with perks
- Low repeat rate: Focus on acquisition—your events attract new people
- Compare across event types to see which builds loyalty
Show rate percentage
(Validated tickets ÷ Tickets sold) × 100
How many ticket buyers actually attended.
How to use it:
- 95%+: Excellent—committed audience
- 80-95%: Normal range for most events
- Below 80%: Consider overbooking strategies or check if refund policy is too strict
- Low show rates may indicate pricing too low or wrong audience
Net revenue
What you actually receive after all deductions.
How to use it:
- Compare profitability, not just ticket volume
- A smaller event with higher prices might net more than a larger cheap event
- Track to understand your true margins
Sales pace chart
Below the metrics table, there's a line chart showing sales pace over time.
Chart axes
| Axis | Description |
|---|---|
| X-axis | Days before event start (0 = event day) |
| Y-axis | Tickets sold or revenue generated |
Chart controls (top right)
- Time range: Select 7, 14, 21, or 30 days before the event
- Y-axis metric: Toggle between "Tickets sold" and "Revenue generated"
Reading the chart
Each event/date is a separate line. The chart shows how sales accumulated as the event approached.
How to use it:
- Steep early curve: Strong early demand—your marketing worked
- Steep late curve: Last-minute buyers—consider early bird pricing
- Flat line then spike: Waiting until last minute—create urgency earlier
- Compare patterns: See which events sell early vs late
Practical comparison strategies
Compare recurring events
Compare the same event across different editions to track growth:
- Is attendance increasing?
- Are margins improving?
- Is show rate consistent?
Compare similar events
Compare events of the same type (concerts, theater, sports):
- Which venue performs better?
- Which day of the week sells more?
- Which price point works best?
Compare dates within one event
Use date mode to compare different show times:
- Do weekend dates outperform weekdays?
- Does the opening night sell better?
- Which time slot has best show rate?
Next steps
Events or dates with zero sales don't appear in the comparison results. Make sure the events you're comparing have at least some sales.
Yes. The category filter is just to help you find events faster, but you can select and compare events from any category.
It represents the day of the event itself. So tickets sold at "0" are same-day purchases.
A low repeat rate isn't necessarily bad—it means you're attracting new customers. This is common for unique or one-time events. For recurring events, you'd expect higher repeat rates.
The comparison view is for visual analysis. For exportable data, use the Purchases tab where you can filter by event and export to Excel/CSV.
Date comparison is useful when you have multi-date events and want to see which specific dates perform better (weekend vs weekday, afternoon vs evening, etc.).
It depends on your goals. 70-90% is generally healthy. Consistently selling out (100%) might mean you could charge more or use a bigger venue.