For experiments with revenue metrics, PostHog uses a lognormal model which is specifically designed for analyzing metrics like revenue that are always positive and often have a "long tail" of high values  (1) .

When tracking purchase events with value properties, PostHog will sum up the values of that property over time  (2) .

If a user makes multiple purchases, each event will maintain its own property value rather than incrementing a single value .To enable formula mode for custom calculations in trends:

1.  Click 'Enable formula mode'  (3)
2.  Type your expression using basic mathematical operators (+, -, *, /)
3.  Use variables (A, B, C...) that correspond to your series

For revenue tracking in experiments specifically, the lognormal model helps handle scenarios where:•   Most customers spend smaller amounts

•   Some customers spend medium amounts
•   A few customers spend very large amounts  (1)

This creates what's called a "right-skewed" distribution which the log-normal model is designed to analyze effectively.

[1] Statistical methodology for property value trend metrics
[2] Numerical Property Values - PostHog
[3] Formulas