At a recent Analytics Coffee meet-up, I asked for ideas on creating a widget that would calculate incremental revenue for price increases for all price types. I couldn't use Seat Order Date Base Value because that only pulls the order date value of the base price type and I have more than one price type. Based on feedback, research, and a tip from Chris Wallingford's intermediate analytics workshop at TLCC2023, I came up with a solution that I wanted to share. If there are other ways of doing this, please share!
Challenge:
Show incremental revenue for price increases for both subscription price type AND full price type (single ticket sales).
Solution:
Use Ticket Paid Amount as a row to get data for each price point.
To calculate incremental revenue, I needed to compare revenue for each increase with what it would have been at the original price. To do so, I needed the minimum price for each price type/zone combination, and I landed on using this for the Original Price formula:
( [Min Ticket Paid Amount] , [Ticket Paid Amount] )
(Shout-out to Chris Wallingford's workshop where he covered this concept - using a filter in a value formula but filtering to "all" (prices in this case), so that the original value remains the same irrespective of the price point of each row.)
Then I used that formula in the calculations for the price increase and incremental revenue formulas.
The only thing I wish I could get here is a grand total that isn't zero. But I'm guessing that's not possible for this?
- Odele
This is the formula I use. sum([Total Variance to Ticket Home Value])I filter the widget to exclude editable price types. I also filter on "variance to home value" greater than 1.