Hello!
I know there are a number of resources for ascertaining the number of first-time buyers. I'm wondering if anyone has anything that gives the accurate number first time buyers from a specified year that returned this year?
So, of the number of first-time buyers in <insert previous year here>, I want to know how many came in 2023. It doesn't necessarily matter if they came in another year between <previous year> and this year, just that their first time coming to the Festival was <previous year>. That said, if you have a way to get that number (# of first timers from <previous year> coming back for first time this year), I would not turn it down.
I've tried a couple ways to get at it, but I don't feel like the numbers are accurate. When I use the formula in a jump-to constituent dashboard, it just gives me all ticket buyers for the season, so it's not helping me verify.
Any insight from this crowd is always greatly appreciated. Thanks!
-Michael
Hi Michael,
I have a couple of formulas that might help you with this concept. I created them to look overall at the return rate of first time buyers and what they were coming to next. I wonder if you could adjust things in these formulas to look more at specific years.
The summary widget is filtered to select different production seasons and then I have the following formula to calculate how many have since returned:
count ( [Constituent ID], if ( min ( ddiff ( [Days in Date],[Days in First Performance Date])) = 0 and ( [# of unique Production Season ID], all ( [Production Season])) > 1, max ( [Constituent ID]), null))
count ( [Constituent ID],
if ( min ( ddiff ( [Days in Date],[Days in First Performance Date])) = 0
and ( [# of unique Production Season ID], all ( [Production Season])) > 1,
max ( [Constituent ID]), null))
The first part of the formula recognizes if they are a first time buyer, and then the second part adds in whether they have come to anything else.
Taking this formula, I then add onto it to create a proportion of how many are returning:
(count ( [Constituent ID], if ( min ( ddiff ( [Days in Date],[Days in First Performance Date])) = 0 and ( [# of unique Production Season ID], all ( [Production Season])) > 1, max ( [Constituent ID]), null))) / ( count([Constituent ID], if ( min ( ddiff ( [Days in Date] , [Days in First Performance Date])) =0, max ( [Constituent ID]), null)))
So the denominator here just gets a total count of first time buyers, as in the first part.
I have another widget that then that looks at what they are coming to next designed as a bar chart. This widget is filtered by the first performance name. The formula I use here probably could have also been used in a variation in the above calculations.
count([Constituent ID], if ( min ( ddiff ( [Days in Date] , [Days in First Performance Date])) >0, max ( [Constituent ID]), null))
For this formula, I started with the formula for first time buyers, but then looked at anything that they have come to since that first performance date. I have categories for season and production season, but if you just want to look more broadly at who came back in a certain season, you could probably just use season.
You won't be able to use a jump-to with these formulas, but you could always add a constituent ID to a pivot table to download and import as a manual list to verify.
I hope that gives you some ideas or formulas to start with.
Happy Analyzing!Christine
Would you be willing to share your .dash Christine Wingenfeld?
I'd like to see if too if possible. pfitz@cnu.edu
Thank you, Christine! Certainly, if you're willing to share, it would be awesome to see what you've created. But you've given me all the tools I need to get the data I need. Thanks for taking the time and sharing your expertise.
Hi everyone, happy to share the .dash file. There are a few other widgets that you might have fun with in here too.
FirstTimeBuyerWidgetIdeas.dash
Happy analyzing!Christine
Thank you!
Thank you so much for this!