PropheZy ‑ A Television Case Study

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:

  • Audience numbers;
  • Broadcast time;
  • Channel;
  • Genre.

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:

  • Black text comes from Peaktime;
  • Blue text are numbers we altered;
  • Red text is predicted by PropheZy.

Peaktime Forecasts - BCastTime as Class.xls

Peaktime Forecasts - Channel ID as Class.xls

Peaktime Forecasts - Genre ID as Class.xls

Peaktime Forecasts - Audience Number as Class.xls

Taking each programme in turn:

  • Bagpuss - we used this to predict itself, thus no blue numbers - perfect;
  • Breakfast - we changed the day of broadcast from Sunday to Monday - decreased share from 8.2% to 7.6%, except when audience numbers was the prime dimension where share went up to 11.7%;
  • Animal Hospital - we changed the day of broadcast from Wednesday to Sunday - share increased from 4.6% to 7.05%, except when audience numbers was the prime dimension where share went down to 6.65%;
  • As Time Goes By - we changed show time from 14:45 to 14:00 - share went up from 9.4% to 10.5%;
  • Arrest and Trial - we didn't fill in the channel and PropheZy rightly predicted Channel 5;
  • Art Now - we changed the broadcast time from 17:11 to peak time 21:00 - share went up from 11.9% to 18.05%, except when audience numbers was the prime dimension where it hit 24.9%;
  • Cash in the Attic - we moved from BBC1 to C4 - was 40.4% and then decreased markedly to 4.8%;
  • Casualty - like Bagpuss, a direct test - hit 26.0% accurately.

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

  • Straight through processing exceptions for investment bank trading, also very similar to anti-money-laundering applications;
  • Trading price anomalies to benchmark against quantitative trading units;
  • Price-your-audit for accountancy firms and finance directors;
  • Customers likely to buy or prospects worth mailshots;
  • Data cleansing (using PropheZy to fill in blanks in data);
  • Credit risk predictions;
  • Reserve level requirements;
  • Grant-giving success;
  • Medical analytics;
  • Performance measurement setting (PropheZy can predict what you "ought" to achieve despite variables such as geography, assets, input quality) for property managers and, full circle, television producers.

Anyway, this gives you some background to open up discussions with Z/Yen!

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