MusicMaster Blog
Coding Analysis posted on November 4th, 2019
By Paul Ziino
We’re all familiar with Turnover Analysis, which you can access by clicking the blue circling arrow icon in the Toolbar or the menu Dataset/Analysis/Turnover Analysis. It allows us to see predicted turnovers of the songs in our categories. There’s a cool little button in this part of the software that allows us to see the predicted turnovers of our coding called “View Coding Analysis.”
Click that icon and select the field you’d like analyzed. Let’s start with Gender.
This tells us we have 45 F-Female coded songs in the library and that we should expect to hear approximately 79 plays of Female coded songs per day, 558 per week, and generally expect about 15 minutes between plays. Its density in the library is 20%. As we look at the screen we see that the density between Male and Female, when totaled, is greater than 100%. Why? Because some songs in the library may have both codes listed representing a male/female duet.
Next, I ran analysis on my Sound field.
This tells us we don’t have many ballads, Dance/Disco, New Wave, or Urban songs in the library, and as such we shouldn’t be hearing very many of those songs. Again, the Density totals to be more than 100% because songs have more than one code assigned.
You can even analyze keyword fields. By default they will be sorted alphabetically, but you can click on any column header to sort by it. In the following, I’ve sorted Artist Keywords by the Count column.
Here we see in this database that John Mellencamp is our most-used artist keyword and that we can realistically expect his songs to appear every hour and a half. That’s followed closely by Phil Collins and Huey Lewis. Why does Van Halen have seven songs but we expect to hear that artist every 1:33 whereas we have eight songs by Huey Lewis and can expect to hear that artist every 1:46? It’s because the categories with Van Halen rotate faster than those containing Huey Lewis.
Using the Coding Turnovers can really help when it comes to building rules. For example, we can’t expect MusicMaster to be able to sustain a rule that says we have to be 50% Rock when only 30% of our library contains that code. We can’t expect a five hour artist keyword separation rule to work when we have artists that should be playing every 90 minutes.
When you look at all the information MusicMaster can provide, it will really help you set up your rules and rotations. For more help, contact your MusicMaster Scheduling Consultant.