Hi @robdhondt,
Thank you for the help 
Unfortunately that does not work for me, and it’s close to something I had already come up with. Let’s take the second formula, I had already tried something similar using:
distinct_countIf({User}, truncDate('MM', {First_Purchase}) = truncDate('MM', {_Date}))
The problem with these formulas is that I get:
| First Purchase Date | 2022-05 | 2022-06 | 2022-06 |
|---|---|---|---|
| 2022-05 | 200 | NULL | NULL |
| 2022-06 | NULL | 150 | NULL |
| 2022-07 | NULL | NULL | 250 |
This is because the formula is counting the distinct user who were first time purchasers and the month of first purchase was the same as the date.
What the data should look like is:
| First Purchase Date | 2022-05 | 2022-06 | 2022-06 |
|---|---|---|---|
| 2022-05 | 200 | 200 | 200 |
| 2022-06 | NULL | 150 | 150 |
| 2022-07 | NULL | NULL | 250 |
This is why I was thinking that here I’d need a level aware aggregation.
I need to check the other formula, since what I need is that the user is a purchaser in the current month (based on the column) AND was a first time purchaser based on the row.
In the meantime thank you again!
Ciao,
Massimo.