Hi everyone,
I'm trying to build a sales curve that compares our subscription sales season over season, and I've hit a roadblock trying to figure out the right way to get the date I want for the x axis. The goal is for "day 0" (the start date) to be the day we put packages on sale, which we store as appeal start date, and end on appeal end date. Here's an example of what we've been building in Excel, based on pulling data manually from T-Stats:
Sorry it's so small! Basically the y axis is cumulative package sales $$ (blacked out), the x axis is days from appeal date, and each colored curve is a different package season. Since appeal date isn't an accessible option in Analytics, I've been wracking my brain trying to find somewhere else to store this date. Our finance dept uses campaign date for fiscal year stuff, so that's not an option, and otherwise I'm kind of out of ideas. Does anyone have any thoughts or creative solutions?
Could you use order date instead? Would there be a big discrepancy between the date you put them on sale and the date of the first order?
Have you looked at Order Days Prior to Performance or Order Day Since Onsale?
As long as the Order Day Since Onsale is set with the day your packages go on sale the reporting should work I'd guess.
Is "order day since onsale" an option in the Seats and Tickets cube in Analytics? That sounds like exactly what I need, but it's a metric I'm not familiar with.
It is. If you put onsale in the search box it pops up. Would you mind sharing the whole screen shot so I can see how you built this curve? I'm interested in trying to replicate it (for use here and to help with your issue) and I can't figure out how to make it cumulative.
Here is my attempt to do something like this.
The sales curve for yesterday's Sales.
7128.HockyStickSalesChart.dash
Oh thank you! The data looks a little funky for some of our older seasons but I can probably find that in Tess and adjust it. I made it cumulative with the running sum quick function on the field "Total Ticket Original Paid Amount." Here's my setup for that:
I messed with this a little differently. Since we have gone on sale a different times, depending on our Marketing Manager at the time, but our performance dates were fairly consistent, the issue Marketing cared about was sales run rates compared to prior seasons. So, rather than using Order Day Since Onsale or Order Days Prior to Performance, I ended up using Fiscal Year Week along my Y axis and cumulative sales on the X axis and grouped by Fiscal year. I ended up with a chart that looked pretty much like yours above. I could tell when we went on sale for various events (Donor On Sale / Packages / Singles) each year by looking at the spike in a given week of the year. Overall, though, since I knew my performances start at roughly the same fiscal week, I could see my run rates as I got closer to that week and where I stood compared to prior season, even though on sale dates were different. This solved my particular problem. Might or might not help you, but just something to consider.
Thank you!
Good work. The "Onsale" date in "order day since onsale" for each curve is set by the first MOS start date, so you can fiddle with where they start on the x axis for historic records by adjusting that MOS.
I've been playing further with this and breaking within an individual season by Returning, Renewing, and Lapsed/Reengaging folks using the Custom Categories and it looks great so far.
Please share any really cool dashboards you create. I know that I'd love to see what folks are working on.
--Tom
Here is a a similar one to Krystle's with Total Sales, Subs and Single Tkts but split out with the Custom Category New, Renew, and Lapsed/Reengaging. That custom category is created from 3 Constituencies that are applied to the 2019 patrons using the Manage Constituency Report.
Heath Wilder
How are you breaking up the constituencies so that the chart is broken by these values? I'm guessing that you have more than 3 constituencies in use.
Does anyone know if the Tessitura Analytics Constituency bug where constituency end_dt < start_dt is still a problem? And if not in what version was this fixed.
I use those 3 constituencies in the one custom category
Then I guess it's time to learn how to create "custom categories.
I also not that you have point along your lines not every point along the lines. Is there a significance to these points?
They'd normally be the data points in isolation but I've used the piece of Java from the forums to connect the blanks. I think it was Ragan's code.
Custom Catagories are easier than you might think. Similar to output set elements IMHO. I've got 3 constituencies in Custom Category 1 and it lets me select some/all/none for a Break By or Filter or what have you. It's great for looking at what NEW buyers are purchasing by Discount Price Type Category/Source vs Returning folks.