Using Calculated Metrics we can calculate the Average Subscribers based on number of days in the below sample (we have used Unique Visitors instead of Subscribers)
Example: In Calculated metric we have used the function Approximate Count Distinct to calculate the number of Days, then we have divied the Unique Visitors (you can use your subscribers metric here) data with that function result.
Do you capture the timestamp in a dimension? If you do, and that timestamp contains the date, then you may be able to create a calculated metric using approximate count distinct. Note that you can use approximate count distinct with a classification of the timestamp dimension, which you'd likely need to do in order to isolate the "day" component. For example, create a "Day Number" classification to extract "05" from "2021.05.26".
This won't give you an average outright, but you can use it on a table with, say, Month on the y-axis to see a trend over time.
Depending on how many customers you have in this segment, it's distinctly possible that they show up every day of the month.
Since I haven't done this before, I'm working on this using my own data to see if it actually works as expected.