Probably the best way to think of PropheZy in action is to look at an application. We have numerous ones, but predicting television audiences is a relatively easy example to understand. Our data comes from Peaktime, a French company, who are sort of the "Reuters" of television data in Europe. The data covered 1 December 2002 to 15 December 2002 06.00-24.00 on a day-by-day basis for UK television channels BBC1, BBC2, ITV1, Channel 4, Five and Sky 1. The available columns were Channel, Title, Date, Time of Broadcast, Duration, Genre, TVR (televisualrating), Audience in 000's and Share %.
We started prototyping predictors one afternoon. We built four different predictors from the data that afternoon. Each predictor used a different prime dimension:
Each predictor tries to predict "audience share %". Naturally the desired predictor can change. Audience numbers is not a particularly good prime dimension, as you'll see later, unless we do some analytical work.
The predictors work in Excel. For instance, having built the predictor and saying you want the most confidence about "broadcast time" you can then alter one or more parameters and get the new predicted audience share %. You can partially supply data and get that filled in, rather than audience share %.
Four output sheets from each of the four predictors are attached. For the output sheets we took 8 programmes - Bagpuss, Breakfast, Animal Hospital, As Time Goes By, Arrest and Trial, Art Now, Cash in the Attic and Casualty - and used them to play with the predictors. You will see that the four output sheets are broadly in agreement, indicating that the data is probably quite good for this type of application. For ease of reference:
Taking each programme in turn:
However, Excel is really just the development environment. You can build an HTML front-end to interrogate your model in a few minutes and roll it out globally across the internet. We have built numerous predictors
Anyway, this gives you some background to open up discussions with Z/Yen!