Madison claims success with programme prediction tool

Media agency Madison's Programme Predictor (MPP) claims to have accurately predicted ratings for nearly 70 per cent of new programme launches in the last two years.

The MPP is a Madison proprietary tool that predicts initial rating size (one to six weeks) of new shows that helps in making the critical 'Go' or 'No Go' decisions, using the simulation technique. MPP uses state of the art Genetic Algorithm (GA) to analyse and run the simulation.

Madison conducted studies to predict show ratings, which according to the agency, is a product of People Using Television (PUT) and Channel Share.

Increase in channel share post programme launch

Channel     Programme     Increase in channel share

Star Plus     KBC     2111%

Star Plus     KSBKBT     483%

Star Plus     Kangan     127%

Zee TV     Kohi Apna Sa     83%

Sony     Kkusum     63%

Star Plus     Kasauti Zindagi Kay     29%

Zee TV     Choti Maa....     0%

Star Plus     Jee Mantriji     -50%

While PUT is estimated as TVR values for all channels, channel share is the share of the market that the programme is able to garner. The study, says Madison, demonstrated that PUT base is fairly consistent for a target audience and a time slot, specially for smaller timeframes of 13 weeks, while channel shares tend to be more volatile. These, the study found, were affected by

* existing channel share

* loyalty of competing programmes

* audience flow.

The study noted that if the share of cable and other channels are higher, it is easier for new programme to garner higher share. Similarly, if programmes on competing channels have high loyalty scores, it is intuitive to understand that the new show will have lower initial rating, the study observed.

The agency selected the hugely popular Kyunkii Saas Bhi Kabhi Bahu Thi to understand MPP, as the predictor does not rely on a single equation but is entirely dependent on the competitive environment that exists in the slot. While the channel share prior to KSBKBT was highly fragmented, its competing programmes had relatively low loyalty scores. Analysis of audience flow indicated that 30 per cent of existing viewers switch off television and another 30 per cent move to other channels in a random manner.

The MPP, applied to KSBKBT, predicted a huge increase with the help of simulation. The MPP distribution output also indicated that the trend is towards a rising channel share, and that the actual performance of KSBKBT was not significantly different from the forecast.

MPP, however, says the agency, cannot be used accurately for shows launched with unprecedented hype like KBC and Sawaal Dus Crore Ka since it does not explicitly quantify the influence of programme promotion. Madison's study also observed that MPP could not forecast ratings of live primetime telecast of India playing in cricket matches. It also found that while MPP was fairly accurate in forecasting events like Zee Cine awards, but was not very effective for 'hyped up' events like the Hrithik show on Sony. It also does not explicitly capture programme details like genre, storyline and production quality.

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