Will Your Favorite New Show Get the Axe?
Want to know if your favorite new show of the season will survive to see a second? A new business that uses prediction market methodology pioneered at the University of Iowa can offer some insight.
The business, Media Predict, is based in New York City and is owned by Iowa City native Brent Stinski. A commercial market, Media Predict runs markets in which traders predict the fate of TV shows premiering in the fall. The markets are a unique new forecasting tool for an entertainment industry obsessed with risk mitigation to protect the tens of millions of dollars that go into developing and producing a TV show or movie. Hollywood employs armies of forecasters who parse data in a thousand different ways hoping to figure out what programs will be a good risk.
But, as the number of failed TV shows and box office bombs shows, they are still looking for good forecasting methods. Stinski thinks prediction markets may offer a new, more effective, and more accurate way of looking ahead. Started in spring 2011, Media Predict already has 15,000 traders who have made more than 220,000 trades, and the company sells its forecasting data to TV networks, studios, and production companies.
“A market is a good way to get better information from people and aggregate that information into a forecast at lower risk than other methods,” says Stinski, pointing out that his market identified two show ideas for the fall 2011 season as potential hits as early as March, before the network even had a chance to take them before test audiences. Their market performance helped the network—which he can’t identify because of contractual obligations—slot the programs on their fall schedule.
“The two shows went on to become two of the biggest hits of the season,” he says.
Stinski said he first became interested in prediction markets in 1990, when he was a student at City High and an economics teacher told him about the still-in-its-infancy Iowa Electronic Markets (IEM). His first attempt at creating a commercial prediction market three years ago was aimed at the book publishing industry, and had traders predicting what still-unpublished manuscript would have the best chance for success. That eventually morphed into Media Predict after he decided a TV series forecasting market would be more commercially viable.
Several corporations have also set up internal prediction markets to help in planning. Motorola and Best Buy, for instance, both used internal markets to help in making marketing, purchasing, and distribution decisions.
But most attempts to commercialize UI’s prediction market research have failed. Nelson said that poor track record is the result not so much because the prediction market itself didn’t work, but because it wasn’t run properly or didn’t ask the right questions. Lack of resources is likely also a reason for shutting them down.
“They are very time consuming to operate properly, and take way too much time to keep them running,” Nelson says.
But Nelson says that from what he’s seen so far, he thinks Media Predict can avoid those pitfalls. He says Stinski has shown he’s committed to keeping his company in business, and he has an impressive list of clients signed up to provide an ongoing revenue stream. He says Stinski also understands prediction markets, asks the right questions, and since he screens traders before allowing them on the market, he makes sure he has only motivated traders. He says that a lack of motivated traders is often a reason that markets fail, because traders are needed to provide the kind of information that a prediction market needs to survive.
The first cancelled show of the current season, by the way, was CBS’ “Made in Jersey.” What were the odds of that? You can buy the data from Stinski.
Contact: Tom Snee, University Communication and Marketing, 319-384-0010