4 Replies Latest reply on Oct 21, 2018 1:05 PM by Phil Ju

Creating One Dimension with Multiple Calculated Measures

Hello,

I have a data set that looks like the following. Each row represents a unique lead, which week they signed up, and any subsequent dates of events after signup (events 1 and 2).

Event 1
Event 2
A1MarApr
B2
C2AprJul
D3Jan
E4
F4Oct

I would like to achieve the following view. I would like to create a new calculated field called "Conversion" where it calculates the conversion rates from Signup --> Event 1 and then Event 1 --> Event 2, through the lens of each Signup week.

For example:

• In Signup week 1, 100% of the Signups converted to Event 1, and 100% of Event 1s converted to Event 2
• In Signup week 2, 50% of the Signups converted to Event 1, and 100% of Event 1s converted to Event 2
• In Signup week 3, 100% of the Signups converted to Event 1, and 0% of Event 1s converted to Event 2
• In Signup week 4, 50% of the Signups converted to Event 1, and 0% of Event 1s converted to Event 2

Conversion

Signup week

1

Signup week

2

Signup week

3

Signup week

4

Event 1 Conversion100%50%100%50%
Event 2 Conversion100%100%

Thank you!

• 1. Re: Creating One Dimension with Multiple Calculated Measures

Can you please explain..It is bit confusing

• 2. Re: Creating One Dimension with Multiple Calculated Measures

Hi,

Sorry for the confusion. Maybe this will clear it up.

I want to be able to create a calculated field called Conversion that:

1. Divides the number of Event 1 dates (4) by the number of Signups (6). Call this Event 1 Conversion.

2. Divides the number of Event 2 dates (2) by the number of Event 2 dates (4). Call this Event 2 Conversion.

But I'd like to do these calculations by each Signup week.

• 3. Re: Creating One Dimension with Multiple Calculated Measures

Phil,

I have union the same data twice.

Attached is the workbook.

Thanks,

Ankit Bansal

• 4. Re: Creating One Dimension with Multiple Calculated Measures

Thank you Ankit. This works, but I'm wondering if there is a way without having to alter, or union, the data set.