Predicting Content Preferences with Data
Data is the most powerful thing. How will these services we can use that data that we talked about just a minute ago to understand you’re a male or a female, you’re in a certain age strata. So we’re going to put content in front of you. But that makes the most sense. And the way that we’re doing that is we have more data than ever before to pull in, analyze, and apply and then to move it to a second, but to be more predictive and to help our customers understand how to program and what the audiences want to see or not see. So there’s no more need to silo AVOD, PVOD, SVOD date. You can put it on the same system and programs that way. You got to look at the customer historically, too, not just at behavioral content consumption, but payment history, social data. Right now we can look into Twitter, things like that, and the outputs more valuable. Right we can like I said, we can provide predictive insight. It’s going to churn when and why we have all the data to show us. we can see a trend line or data that begins to surface that and show that trend. We can use some of that to stop the churn from happening. And then lastly, integration. know, what gets me and our customers really excited is what happens when we start layering all those findings. We we can use a product to develop and learn from accounting that they never know what would happen if Enterprise data were still dispersed across 15 different systems. Now everyone has access to the data and can work as a team to help build, manage, maintain systems, reduce churn, understand what the audience is doing.