If you want to check whether a customer has stayed below a specific event threshold, such as a certain number of events with the same property within a defined timeframe, you can build this using two aggregates and one filter.
Step 1: Create an aggregate for the most common property value
The first aggregate should count the most common property values for a selected event over your chosen number of days.
This aggregate stores and displays the property value that appears most often in each customer profile.
Step 2: Create an aggregate to count matching events
Once you have the first aggregate, you can use its result in a second aggregate.
The second aggregate counts how many times the event occurred, using the value returned by the first aggregate, which is the most common value found in the customer profile.
Step 3: Create a condition to filter customers
After both aggregates are in place, create a condition based on this setup.
This condition filters all customers who have more than 3 example events with the same value in the index property within the last 7 days, based on the date filter set in the aggregates.
Result
With this setup, you can identify customers whose activity exceeds your defined threshold for repeated event values within a selected timeframe. You can then use this condition in segmentation or any follow-up workflow that depends on repeated event behavior.