Bill uses ratings to build a predictive index – all based on the insight that you don’t have to outrun the cancellation bear, you just have to outrun the other guy! By comparing a set of ratings against the network average, Bill can deduce which shows are likely to be renewed, on the bubble, or cancelled.
The usefulness of a predictive algorithm is in how accurate the predictions are.
The index is better at predicting if shows will be renewed than it is at predicting cancellation, however, 77% recall really isn’t bad.
(We’re talking about imperfect executives making imperfect decisions, we’re not talking about chemicals predicting the presence of other chemicals in a sample.)
That’s pretty neat isn’t? And the site is pretty useful too. Thanks Bill!
I’m Christopher Berry.
I tweet about analytics @cjpberry
I write at christopherberry.ca