Improving the predictive accuracy of commercial testing

There is an interesting blog written yesterday http://business2.blogs.com/business2blog/ regarding possible subtexts to the Google purchase of YouTube. They suggest that Google is coming out with ways to help advertisers determine in which commercials will succeed and fail through online testing via something like YouTube.

There is no question that the advertising needs to improve its accuracy in commercial development if it is going to be more effective. Something on the order of 10% of the cost to produce a commercial is spent to test it before it is made. And untold dollars are lost by placing the ads in the wrong places where the granularity is too broad to ensure that you are reaching your demographic.

The YouTube model has a number of challenges:

  1. You cannot be certain of the profile of the viewers. YouTube could claim that 1000 men under the age of 24 watched a given commercial 20 times each over a 3 day period, but there is no way to ensure that these viewers were really 24 and male. As in the case with most registration functions, there is no plausible authentication mechanism to ensure quality.
  2. There is no way to plausibly ascertain that there is not artificial viewing going on, similar in nature to click fraud, which remains a dirtly little secret in the industry. While it may be implausible, competitors could disrupt testing results via this channel, just as competition in retail has often attempted to wreck regional promotion programs.

But there are better approaches coming to increase the “qual” and “quant” of the commercial testing process – leveraging existing processes with better technologies that more accurately reflect the potential buyer interest and hence downstream commercial activity.

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