I'm trying to come up with something to track the amount (or percentage) of "recurring" customers.
What I want to do, is check through a table of reservations that occured, and determine
1) How many unique customers had reservations
2) How many of these customers, also had a reservation in the 90 days prior to their start date.
Example:
I know how to get the count of the 8 distinct customers in the list shown above, but I'm stumped on how to loop through the table again to see if they had a different reservation no more than 90 days prior.
Solved! Go to Solution.
@MPetramalo214 Maybe:
Measure =
VAR __Table =
ADDCOLUMNS(
ADDCOLUMNS(
SUMMARIZE(
'Table',
[Owner Id],
"__LastDate",MAX([Check-In Date])
),
"__PreviousDate",MAXX(FILTER(ALL('Table'),[Check-In Date]<[__LastDate] && [Owner Id]=EARLIER([Owner Id]),[Check-In Date])
),
"__Diff",([__LastDate] - [__PreviousDate]) * 1.
)
RETURN
COUNTROWS(FILTER(__Table,[__Diff]<90))
@MPetramalo214 Maybe:
Measure =
VAR __Table =
ADDCOLUMNS(
ADDCOLUMNS(
SUMMARIZE(
'Table',
[Owner Id],
"__LastDate",MAX([Check-In Date])
),
"__PreviousDate",MAXX(FILTER(ALL('Table'),[Check-In Date]<[__LastDate] && [Owner Id]=EARLIER([Owner Id]),[Check-In Date])
),
"__Diff",([__LastDate] - [__PreviousDate]) * 1.
)
RETURN
COUNTROWS(FILTER(__Table,[__Diff]<90))
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