# AA test simulations issue for revenue-like metrics

**URL:** <https://discourse.pymc.io/t/aa-test-simulations-issue-for-revenue-like-metrics/16467>\
**Category:** v5\
**Tags:** modeling\
**Created:** [January 30, 2025, 11:06am UTC](https://discourse.pymc.io/t/aa-test-simulations-issue-for-revenue-like-metrics/16467 "2025-01-30T11:06:36Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![alievvlad](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/alievvlad/32/8962_2.png) [@alievvlad](https://discourse.pymc.io/u/alievvlad)\
**Post date:** [January 30, 2025, 11:06am UTC](https://discourse.pymc.io/t/aa-test-simulations-issue-for-revenue-like-metrics/16467/1 "2025-01-30T11:06:36Z")

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Hi all!  
I am a newbie in the topic of Bayesian AB testing and tried to follow the example for revenue-like metrics (Beta+Gamma distributions) from [here](https://www.pymc.io/projects/examples/en/latest/causal_inference/bayesian_ab_testing_introduction.html).  
I encountered a problem that AA test simulations (100 sims, 500k users in group per simulation) on the data I have show significant differences too often. From 30% to 50% of simulations shows 0 out of HDI (depends on selected prior)  
I think it’s because of the data structure - very right skewed.  
Conversion to target action - 1%, so data contains 99% of zeroes.  
For users with target action metric’s histogram looks like this:

 ![image](https://canada1.discourse-cdn.com/flex036/uploads/pymc3/original/2X/5/5c233d2c62054e99cccd9a9934ee40c2b8a12f3c.png)

What steps should I take to reduce False Positives?