Hi folks,
Hoping for some insight again with Analytics! We are a Museum and a super important metric for us is tracking attendance and revenue year-to-date over year-to-date. Our fiscal starts April 1, so essentially, measuring April 1 to today, 2019 vs. April 1 to today, 2018. Is there a way to setup widgets to do this automatically? Essentially, to always look for data from April 1 to today and then match the dates for the previous year?
I know I can filter by month or by day...so hypothetically I could, daily, update the filter to add the next day I need; however, I am hoping there is some type of relative option that might work so that this adjustment always happened automatically when a new day starts.
Simply put, I want a widget that shows me a specific production season's sales from April 1, 2019 to today. And then, if possible, have it also compare that data to April 1, 2018 to the same date as today in 2018,
Hey Derrek,
This sounds like it should be doable. Have you checked out the Membership Sales dashboard in the Memberships folder of Tessitura Dashboards? In there is a Membership Sales Comparison widget that compares years. You might be able to use that as a baseline widget to make your own using Seats and Tickets data for attendance and admission sales. You may even be able to add filtering to break up attendance by price type (assuming your membership admissions use a different price type) to see member admission versus non-member.
That's where I would start as a resource. I often still examples from the Tessitura provided dashboards and augment them for my needs.
- Chris
Thanks Chris! That is literally what I was using as an example. Where I keep getting stuck is that it isn't 'to date'. So for example, on June 1...it shows all of June 2018, but then only June 1, 2019 (as the rest of the month hasn't happened yet). So it doesn't help us know where we are trending vs. the year before until we hit the end of the month.
I will definitely keep playing around with it though and see if there is a way to adjust...
Hi Derrek!
Perhaps something like this could work... A bar chart or column chart, where Category is Attended Date Fiscal Period, Values is either Total Ticket Amount Paid or Attended Count, and Break By is Attended Date Fiscal Year. As for the dynamic part, set a dashboard filter or widget filter for Attended Date Fiscal Year to Time Frame > This & Last Year or This & Last 2 Years.
The result should be 12 months across the bottom, and each month has 2 or 3 bars (one for each fiscal year) so that you can see a each month and how it looked in all fiscal years.
Fiscal Years and Fiscal Periods are defined in TR_BATCH_PERIOD, and in your case you should have April as period 1 every fiscal year, May as period 2, etc. You could also use Attended Date Calendar Month Sort if you prefer that instead.
-Michael Flaherty-Wilcox, Tessitura Network
Thanks Michael! This has been helpful!
Where I am still stuck a bit is on the current month comparison. Does anything come to mind in terms of showing the current month 'to-date' with the exact same period from the year before? Right now it compared June 1-18, 2019 compared to June 1-30, 2018 (ideally, we would want this to be June 1-18, 2018).
This will get easier in a future release, but for now, here's a similar post regarding weeks instead of months:
https://community.tessituranetwork.com/tessitura_software_forums/f/tessitura_shared_reports-9/22047/analytics-weekly-sales-contributions/63423#63423
Adapted to use Month and Day of Month, it should produce month-to-date results.Best,Chris
Chris Wallingford Director, Business Intelligence Tessitura Network Office +1 888.643.5778 ext 553 chris.wallingford@tessituranetwork.com Tessitura Learning & Community Conference July 28-August 1, 2019 #TLCC2019
Thanks Chris! This is a good start, I will start working at this and post again later once I have some success or get stuck (ha!). Looking forward to the future release where this will get a bit easier. I am sure we aren't the only MZA where this will be a key metric.
Derrek, the post Chris is referencing is mine, asking the same question. I had all kinds of issues trying to figure out the formula Chris gave me to understand exactly what is happening. I might hit him up at conference to go over it in detail.
As a more workable solution, what I did was build a line chart. I used the Fiscal Week of the Year as my X axis value, Total Ticket paid as my Y axis, and set the Break By to Season Fiscal Year. The key was in setting the sales to a Running Total. You can find this in the Hamburger Menu / Quick Functions as Running Sum.
The next part that had to be solved was in weeks with no sales, my line broke up with little dots marking the next starting point. Found a post similar, and ended up putting in a ticket with RAMP to figure this out. I had to put some code into my widget to get the lines to work correctly. The post with the fix is here:
https://community.tessituranetwork.com/tessitura_software_forums/f/tessitura_shared_reports-9/22348/broken-line-chart-in-tess-analytics
What I ended up with was a visual of how my sales were tracking year over year. It isn't quite what Marketing wants (they want actual numbers), but I'm working on them trying to see the value in the visual trend lines. Here is a picture of what I ended up with for one of our Orchestra's sales.
You can point at any point in the lines to see the values year over year. This got me the closest to what Marketing wanted without having to deconstruct that formula that Chris posted in my earlier question. What I can't do is show a % ahead / behind prior year in this chart.
Frankly, for me, I don't find this particularly useful information since (as a performing arts venue), our inventory is limited. So, even if we are tracking ahead, if we run out of inventory, we are going to cap out at some point. So, you can see in my chart that we are ahead in 2019 (red) from prior seasons, but notice how each previous season spikes around week 42. That is when the concerts start for this group and day of sales pick up. My concern for 2019 is we are so heavily sold early we may not see the same level of spike. I think the red line, while going up, will just be flatter than 2019 (yellow-orange line).
Your situation might be a little different as a museum. If you are ahead you might stay ahead because sales in the future are not limited by sales in the past. The opposite would be true also. Past sales probably don't have much impact on future sales for you guys.
Hope this helps.
Thanks David! Chris' post, although helpful, was a little too complex for me to apply to a whole bunch of different widgets.I will give this a try and see how it goes, really appreciate. I will post here what I find :)
David Judd
Are you able to share by exporting the .dash file from your instance of analytics? It would be super great to see exactly what you are doing.
--Tom
Here you go. There are lots of widgets on this dashboard that won't apply to other orgs, but you can check out the Comparison Year Ticket Sales and Ticket Counts. Note: we are on 15.1, so this dashboard includes a filter by Price Layer Type.
BRVO--Festival6-3-19.dash
Just coming back to this to say that I ended up doing something similiar to David, but two versions of it. One that is full month over month, and another that breaks this down further by fiscal week so that, we can see more specifically how we are doing in that month to-date.I set this up to have a line graph and then right next to it, the same info and criteria in a pivot table. This way, the precise numbers we need are there, but also visualized in a way that is helpful to see where we are at.
Here are two examples...Full year over year:When using a dashboard filter to a specific month, it automatically becomes this:
That's a great overlay Derek. Would love to see the Dash if you are up for it
Me too....
Heath Wilder and .,,here you go! Hopefully I exported these right haha. One note, I do have these setup use Performance date as the key date factor as we are a Museum and have daily performances, so be aware if that doesn't apply to you. CMHR_WeekvsWeek.dash
This is WAY cool! Thanks for sharing.