Skip to main content
cancel
Showing results for 
Search instead for 
Did you mean: 

Vote for your favorite vizzies from the Power BI Dataviz World Championship submissions. Vote now!

Reply
juli__sia123412
Frequent Visitor

Customers who bought one-time, first time and returned

Hello all,

 

Hope someone could help me with this case.

I have table 

OrderID - CustomerID - SKU - Purchase date

( in case of two or more sku were bought, it will be few corresponding records with the same orderID & date)

 

I want to create a measure and categorize my orders to:

 - One-time ( bought once and never back)

 - First ( first order in case customer bougth again any time later)

 - Repeated ( next orders ) 

 

Thank in advance!

1 ACCEPTED SOLUTION

@juli__sia123412 ,

 

You may try the calculated column below.

Column =
VAR r =
    RANKX (
        FILTER ( Table1, Table1[Customer ID] = EARLIER ( Table1[Customer ID] ) ),
        Table1[OrderDate],
        ,
        ASC,
        SKIP
    )
        + RANKX (
            FILTER (
                Table1,
                Table1[Customer ID] = EARLIER ( Table1[Customer ID] )
                    && Table1[OrderDate] = EARLIER ( Table1[OrderDate] )
            ),
            Table1[OrderID],
            ,
            ASC,
            SKIP
        ) - 1
RETURN
    SWITCH (
        TRUE (),
        ISEMPTY (
            FILTER (
                Table1,
                Table1[Customer ID] = EARLIER ( Table1[Customer ID] )
                    && (
                        Table1[OrderDate] <> EARLIER ( Table1[OrderDate] )
                            || Table1[OrderID] <> EARLIER ( Table1[OrderID])
                    )
            )
        ), "One-time",
        r = 1, "FirstOrder",
        "Returned"
    )

 

Community Support Team _ Sam Zha
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

View solution in original post

5 REPLIES 5
Ashish_Mathur
Super User
Super User

Hi,

Share some data and show the expected result.


Regards,
Ashish Mathur
http://www.ashishmathur.com
https://www.linkedin.com/in/excelenthusiasts/

For example -

OrderID -  Customer ID  - SKU        - OrderDate  -TYPE

123        -   456                 - SKU1     - 1/1/2019   - FirstOrder  

123       -    456                -  SKU2     - 1/1/2019   - FirstOrder

156       -    267                - SKU 2     - 1/1/2019   - One-time   

1245     -    456               -   SKU3    - 04/2/2019  - Returned

167      -    456                -   SKU1    - 9/4/2019    - Returned

 

 

@juli__sia123412 ,

 

You may try the calculated column below.

Column =
VAR r =
    RANKX (
        FILTER ( Table1, Table1[Customer ID] = EARLIER ( Table1[Customer ID] ) ),
        Table1[OrderDate],
        ,
        ASC,
        SKIP
    )
        + RANKX (
            FILTER (
                Table1,
                Table1[Customer ID] = EARLIER ( Table1[Customer ID] )
                    && Table1[OrderDate] = EARLIER ( Table1[OrderDate] )
            ),
            Table1[OrderID],
            ,
            ASC,
            SKIP
        ) - 1
RETURN
    SWITCH (
        TRUE (),
        ISEMPTY (
            FILTER (
                Table1,
                Table1[Customer ID] = EARLIER ( Table1[Customer ID] )
                    && (
                        Table1[OrderDate] <> EARLIER ( Table1[OrderDate] )
                            || Table1[OrderID] <> EARLIER ( Table1[OrderID])
                    )
            )
        ), "One-time",
        r = 1, "FirstOrder",
        "Returned"
    )

 

Community Support Team _ Sam Zha
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

You're genius.

Thanks! It works perfectly!

Anonymous
Not applicable

I believe this can be accomplished through using a count function and group functionality. 

 

  1.  Create a calculated column
    1. Column = COUNTX(Table, CustomerID)
  2. From there you can create groups in the modeling tab based on the count to create 'bins' based on the quantity. 

Helpful resources

Announcements
Power BI DataViz World Championships

Power BI Dataviz World Championships

Vote for your favorite vizzies from the Power BI World Championship submissions!

Sticker Challenge 2026 Carousel

Join our Community Sticker Challenge 2026

If you love stickers, then you will definitely want to check out our Community Sticker Challenge!

January Power BI Update Carousel

Power BI Monthly Update - January 2026

Check out the January 2026 Power BI update to learn about new features.

FabCon Atlanta 2026 carousel

FabCon Atlanta 2026

Join us at FabCon Atlanta, March 16-20, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.