5 Best Practices for D2C Streaming Revenue Growth

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Think about the tools that you use and how efficient if you’re being honest with yourself, how efficient you are within those tools. We just we visit with so many various customer categories who tell us I’m really in a bind with these different silos and my team having to go from here to there. And, you know, over this thing in that thing. And like I mentioned earlier, you know, there are browser tabbing themselves to death and copying and pasting. So if you can identify a way to again, I jokingly say, like, no homogenize the data so that you can leverage it very effectively. Do that and think about simplifying those workflow tools. And I think just to kind of interject there on point one, you know, one of the tools that we hear most often used here is Excel and Excel is great and it can do the job that you need it to do. But when you start to get to the volume of data that we’re talking about it, it just becomes unmanageable and often it’s single threaded as well. So hard to share that data between groups. And so Excel kind of can get you so far. Yeah and to dovetail on of that, Joe, I mean, we’ve heard stories from folks who run services who, you know, come in on a Monday morning and say, I want to see how this show perform because we just let it. We dropped it on Friday and being able to come into a UI with fields that make sense, that are colorful and visually represent that data and again, help it tell the story, as opposed to going into a flat spreadsheet and finding the right column and the right value, and then maybe doing some more calculations. The feedback from the users and the people who see these tools is I’d much rather have things be normalized and simplified presented to me in a way that at a glance, I can understand how that show performed. And I can let the boss know, too, because they’re clamoring for that information as it plays out. So we talked about the different data sets that these services have to work with again, payment gateways, authentication gateways and information to playback data in a variety of other data sets, APIs and things that you have to account for. Again, different, different data fields can look different on different platforms, so there is a step where we normalize that data so that it can be viewed at viewed it in one lens so that things make more sense, as opposed to, again going between platforms and understanding what a particular value means to that data set. And then that helps to see those stories within the data, right, Joe showed us some graphs where you can see the visual representation of, you know, peaks and valleys across the surface, where shows episode series do well or not, given particular market conditions, given particular trends, time of the year, those types of things. So being able to visualize what’s happening with that content on a particular service or across multiple services is paramount for programmers today. We hear it every day. I talked about it. Joe talked about it. Understand your content, understand how it performs. Leverage that content affinity. So if an audience of males between the ages of 25 to 54 is over indexing on a service and they’re watching the wire, for example, you’re going to know that there are other shows in your catalog that are likely going to appeal to that group of audience. So again, take that into consideration when you promote that content on your service and then also use that data as we can to plug into the back end of marketing platforms and systems so that instead of sending the generic email to the audience saying, you know, go watch the latest episodes of Alf that just dropped on peacock, you can say you watch the libéria. Therefore, you might like the blacklist, right? Because of some of those trends that you’re seeing in the data. And then last but not least, the point we bring at home that we mentioned earlier is when you get into these types of workflows and tool sets being Saas based, you are nimble as a byproduct.