summary stats

Hi Anonymous ,

You can create a Type table first then create a measure to count the number of customer in each type.

Type = 
DATATABLE(
"Type", STRING,{
{"New"},
{"Increase +200%"},
{"Increase 150 - 199%"},
{"Increase 0 - 149%"},
{"Decrease"},
{"Lost"}
}
)

Measure:

Measure = 
VAR _ADD = 
ADDCOLUMNS('Type',"COUNT",
SWITCH('Type'[Type],
"New",CALCULATE(COUNT('Table'[customer name]),'Table'[Increase/Decrease $] = "New"),
"Lost",CALCULATE(COUNT('Table'[customer name]),'Table'[Increase/Decrease $] = "Lost"),
"Decrease",CALCULATE(COUNT('Table'[customer name]),'Table'[Increase/Decrease %] < 0),
"Increase 0 - 149%",CALCULATE(COUNT('Table'[customer name]),FILTER('Table','Table'[Increase/Decrease %]<>BLANK()&&'Table'[Increase/Decrease %] >= 0&&'Table'[Increase/Decrease %]<=1.49)),
"Increase 150 - 199%",CALCULATE(COUNT('Table'[customer name]),FILTER('Table','Table'[Increase/Decrease %] >= 1.5&&'Table'[Increase/Decrease %]<=1.99)),
CALCULATE(COUNT('Table'[customer name]),FILTER('Table','Table'[Increase/Decrease %] >= 2))
)
)
RETURN
SUMX(_ADD,[COUNT])

Result is as below.

Best Regards,
Rico Zhou

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.