Forum Discussion
Dynamic benchmarking calculation based on slicer selection
Hello,
I have a dataset that looks something like this:
| Campaign | Mailing List | Date | Open Rate |
| A | Subscribers | 01/05/2016 | 15% |
| B | Competition | 03/09/2016 | 17% |
| C | Competition | 25/11/2016 | 23% |
| D | Subscribers | 08/12/2016 | 14% |
| E | Competition | 04/01/2017 | 19% |
| F | Subscribers | 15/01/2017 | 29% |
What I'm trying to achieve (and failed so far) is to dynamically compare the Open Rate of a specific campaign that is chosen via a slicer in the report, against campaigns with similar characteristics, for example:
- Similar mailing list (e.g. if I choose Campaign F in the filter, I want to compare its Open Rate against the average Open Rate of all campaigns that went to Subscribers)
- YTD (e.g. if Campaign F is selected, compare its Open Rate against all campaigns that ran in 2017)
Any help is much appreciated!
Many thanks,
George.
Anonymous
Hi George,
I've used your "Similar Mailing List" example, but similar logic should apply for your other example.
Before getting into the DAX, you need a measure that:
- Captures the Mailing Lists of currently selected Campaigns and adds to the filter context
- Clears the Campaign filter
- Calculates the Average Open Rate in this modified context
If I call your table Data, this sort of pattern would work:
Open Rate Average = AVERAGE ( Data[Open Rate] ) Open Rate Average for Same Mailing List as Selected Campaigns = CALCULATE ( [Open Rate Average], SUMMARIZE ( Data, Data[Mailing List] ), ALL ( Data[Campaign] )
)Notes:
- SUMMARIZE ( Data, Data[Mailing List] ) could be replaced with VALUES ( Data[Mailing List] ) since there is just a single table here, but SUMMARIZE would be needed if Mailing List was in a lookup table.
- The columns specified in SUMMARIZE determine the common attributes over which you want to calculate the average, so you can tweak this to whatever attributes you want.
- I cleared only the Campaign filter using ALL, so any other filters (date etc) are still applied. You could tweak this to clear more filters if you needed to.
Hope that helps as a starting point.
Cheers,
Owen :)
2 Replies
Anonymous
Hi George,
I've used your "Similar Mailing List" example, but similar logic should apply for your other example.
Before getting into the DAX, you need a measure that:
- Captures the Mailing Lists of currently selected Campaigns and adds to the filter context
- Clears the Campaign filter
- Calculates the Average Open Rate in this modified context
If I call your table Data, this sort of pattern would work:
Open Rate Average = AVERAGE ( Data[Open Rate] ) Open Rate Average for Same Mailing List as Selected Campaigns = CALCULATE ( [Open Rate Average], SUMMARIZE ( Data, Data[Mailing List] ), ALL ( Data[Campaign] )
)Notes:
- SUMMARIZE ( Data, Data[Mailing List] ) could be replaced with VALUES ( Data[Mailing List] ) since there is just a single table here, but SUMMARIZE would be needed if Mailing List was in a lookup table.
- The columns specified in SUMMARIZE determine the common attributes over which you want to calculate the average, so you can tweak this to whatever attributes you want.
- I cleared only the Campaign filter using ALL, so any other filters (date etc) are still applied. You could tweak this to clear more filters if you needed to.
Hope that helps as a starting point.
Cheers,
Owen :)