I am trying to figure out, I have a use case where customers get loyalty points when they buy stuff.
We 3 levels of loyalty:
Not yet Qualified – 0 - 2500 points
Base – between 2500 - 20000 points
Executive – > More than 20000 points
I am able to achieve how many customers are in different category by using dynamic grouping.
but now I want to find how many customers are close to get to the next level. Something like:
Within 0 - 10% to get to Base (which means points greater than 2250 but less than 2500)
Within 10 - 20% to get to Base (which means points greater than 2000 but less than 2250)
Within 20 - 30% to get to Base (which means points greater than 1750 but less than 2000)
Within 0 - 10% to get to Executive (which means points greater than 18,000 but less than 20000)
Within 10 - 20% to get to Executive (which means points greater than 16,000 but less than 18,000)
Within 20 - 30% to get to Executive (which means points greater than 14,000 but less than 16,000) so on and so forth.
I put the sample file here:
Just to give an example: In this example, 4 are executive, 33 are base and 761 are not qualified.
For e.g.: In base category, there is 1 customer who is within the threshold of 10% to achieve Executive status (3584605). I want a count that customer in that bucket.
Hi @rit372002. It looks like you’re well on your way already. I’d think if you create another disconneted table for your second-level groupings (e.g., [Within 0 - 10% to get to Base, Min > 2250, Max <= 2500]; [Within 10 - 20% to get to Base, Min > 2000, Max <= 2250)]; etc.) then another [My Groupings 2] measure that uses this new disconnected table, you’ll get what you want. Give this a try, and, if you’re still having issues, upload the revised PBIX for the forum members to review along with a marked-up screenshot of the current visual or Excel mockup showing the desired outcome.
Greg
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