What Determines Primetime TV Ad Prices? A Reader Runs The Numbers

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As much as I’d like to think of myself as a numbers guy, my education is so far in the past that I’ve forgotten 90% of what I think I once knew. Not so with reader Brendan, he’s in the thick of it right now and produced a backward looking analysis of what factors seem to determine advertising prices for primetime broadcast shows. While it will appeal to only a fraction of our readers, for them it may make their day.

Here is his summary, but you can read his entire paper here.  The  text below is all from Brendan:

I love poring over the yearly Advertising Age survey that estimates the cost of a 30 second advertisement for each primetime show. So I did a statistical analysis on what factors influenced these estimated ad prices for the 2009-2010 season.

I examined the following factors for 65 returning shows:

  • total viewers (2008-2009 seasonal average in ratings points)
  • 18-49 viewers (2008-2009 seasonal average in ratings points)
  • age skew (the ratio of 18-49 viewers to total viewers)
  • affluent viewers (whether or not the show was among the top ten “upscale series with highest indices” according to a recent MediaPost article)
  • day of the week (when the show airs)
  • network (where the show airs)
  • timeslot (what time the show airs)
  • scripted (whether the show is scripted or unscripted)
  • DVR viewers (whether or not the show had one of the top twenty 18-49 demo increases due to DVR)

I concluded that the following combination of factors best explain the ad cost for a given show: the amount of 18-49 viewers, how young the show skews, the affluence of the viewers, whether the show is scripted or unscripted, and whether or not the show airs during the 10:00 hour. The other factors (notably DVR viewers) did not seem to have a significant effect.

18-49 viewers

If you visit the site often, it should be obvious that ad cost would be mostly determined by how many 18-49 viewers the show can attract each week. Advertisers seem willing to pay about $50,000 for each demo point. This factor effectively sets a “base price” for ad costs, while other factors may be worth paying a little more for.

Age skew

Advertisers also seem to favor shows that skew young, as an advertisement on a show with a higher percentage of 18-49 viewers will cost more. From the data, it appears that shows with more total viewers tend to skew older, so I believe this just indicates that the most efficient way to reach 18-49 year olds is to advertise on shows that skew young.

Affluent viewers

The application of the data I obtained to evaluate affluence is dubious, but the results correspond with intuition. Essentially, an advertisement on a show with a more upscale audience is pricier than a comparable show with less affluent audience (by about $10,000).

Scripted or unscripted

Likewise, advertising time for a scripted show is pricier than that of a comparable unscripted show (by about $10,000). My best guess is that this is an indication of a higher viewer engagement with scripted shows.

10:00 PM time slot

The data suggests that a show that airs at 10:00 PM will earn more than a comparable show in another time slot (about $5000-$10,000 more). This confused me at first, but I do have a (perhaps tenuous) hypothesis as to why this might be. If advertising buyers predicted low ratings from The Jay Leno Show and thus decreased competition in the time slot five nights a week, they may have expected 10:00 shows on the other networks to benefit from increased ratings. This is a bit of a reach, so I welcome any better explanations.

This study was fairly simple, and not particularly rigorous, so I would not recommend reading too much into it. Having said that, I do think it is safe to base estimates of the value of a show almost entirely on 18-49 ratings and that (at least for this season) each 18-49 ratings point is worth about $50,000 per 30 second ad.

Methods

I used gretl, a statistical software package, to create and evaluate various linear regression models. The final concluded model is a weighted least squares regression that attempts to account for heteroskedasticity given by:

Ad Cost = -68.22 + 47.63(18-49 Viewers) + 0.91(Age Skew) + 10.81(Affluent Viewers) + 12.73(Scripted) + 7.53(10:00 Timeslot)

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