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ComScore has been rolling out the new system for months and says it can now use it to report on 25 percent of the 50 biggest sites on the Web. Another 50 percent of the top sites have agreed to work with the system, Abraham says.

ComScore lets publishers who are already clients participate in the program for free. But it will charge everyone else $10,000 a year, which the company says helps cover the cost of new servers and other equipment it needs to process the new deluge of data.

Gawker/Valleywag says it more bluntly “Comscore Blackmail: Pay Us $10,000 or We’ll Keep Under-Reporting Your Traffic”. Because the figures are consistently biased downwards in the legacy reporting, it creates a distinction in traffic reporting between those who place the tracking codes on their site and those who don’t, that is very correlated with higher ad revenues today (hence the idea of “blackmail”). Most sites won’t ever pay $10,000 so this means only the largest sites will even consider doing it, lessening the burden for comScore’s (probably not very efficient) infrastructure for doing so. This distinction in the costs to participating vs. not exists in a very different way with Quantcast, although the compensation and benefits a publisher gives up are a bit more subtle in their case since there is no cost for participating with them – namely that Quantcast will use their aggregate data to help marketers find similar audiences. By no means a small or easy task and kudos to Quantcast for taking that on. Reporting is one thing – but actionable data based on reporting is quite another.

Three points worth making, though this is interesting and there are many more to think about:

1) the “size = more ad revenue” should (but will take some time still to) become less meaningful, as more centralized inventory access and price discovery is possible. A good reason to work with three big sites versus thirty small- or medium-sized sites is that trafficking and setting up ad buys with people takes time and is grossly inefficient. And we’re all nothing if not lazy in the media business.

2) there is no doubt that the panel approach undercounts data, especially for the at-work and university-type audiences amongst others. I worked at Nielsen NetRatings and the most common argument we used if we ever gave any credence to these arguments was that most sites were consistently underreported. Hmmm yes. Of course. So it begs the question – if you are being trusted as someone to measure, report on and (often) opine on the health, status and metrics of an industry, don’t you want to be as good as possible which in turn leads to more trust, more business and more money? It is unclear in this case.

3) The capacity and desire for sites to implement a lot of different companies’ javascript code on their site is limited. Sites don’t want to break if any of these third-party pieces is messed up. Use firebug/firecookie or Charles and see what all is loading on the typical large site. Risks increase, and the infrastructure capacity of many of these vendors is far less tested than you might think, especially if the publisher is now being asked to pay for the infrastructure (another typical argument used by NetRatings or comScore or others “the market needs to pay high prices to help fund good quality measurement” which is also total BS).

The US remains the largest country by Facebook audience by some distance, and with 63% growth since April it has moved up to being the 12th most penetrated country in the list, behind the Dominican Republic, Iceland, Norway, Canada, Denmark, Singapore, Hong Kong, UK, Chile, Australia, and Sweden still ahead of it in penetration. If the Facebook figures are in fact unduplicated users (which they almost certainly are not, but it’s likely the duplicate rate is probably no more than 10 percent we’d hazard to guess) this means almost a third of all Americans are on Facebook.

Here is the complete list:
Facebook Penetration November Update

CPMa CEO Rob Leathern authored a piece on InternetEvolution.com this week that looks at the relative value of user attention online compared to television:

That means that each user hour spent on search engines is worth about $3.24 in ad revenue, and therefore non-search online ad revenue clocks in at just $0.21 per hour. A lot of search spend is incremental, whereas non-search spend is more likely to reflect share shift from other media, and this seems to be borne out by these numbers as well, since this virtually puts non-search online advertising (display, lead generation, classifieds, video) at parity with offline television ad spend.

Very interesting figures – online display advertising is not that much different from the amount of revenue it generates per user hour compared to television, when in fact it should be a lot higher….

In addition, you can see that over this time period the average number of monthly users has grown to about 197 million in the US, although the rate of growth of users and minutes has been roughly the same, meaning users are not really using the web much more intensely than before. The daily UV figures are also fairly static.

Facebook and Youtube are large and have seen mega-growth over the last three years, and yet they are probably underperforming in terms of their revenue per user hour figures. Any change in their ability to monetize their traffic will certainly have a huge impact in the overall online advertising figures. Figures below are in millions of minutes per month.

I posted a comment to an article about display advertising and thought the point about publishers being able to make more money through arbitrage was one worth alluding to. At Root Markets I worked with several large publishers including the New York Times (who invested in the company as well) to explore this idea further. Surely a publisher of some scale *could* have the data, tools, relationships, position to justifiably take on some more of the downstream economics from advertising vs. selling their remnant inventory for a smaller amount. I still believe this is true, but I know it will take some specialized help for them to be able to do that.

I hope that publisher-side optimizers (normally people mention names like Rubicon, Admeld, Pubmatic etc.) get to the point where they can do more that just shuffle the same inventory between different ad networks (not to say there isn’t value here, but as one of my college CS professors used to say, if it’s not an order of magnitude difference who really cares?), and actually drive meaningful change in the way publishers parcel out, create, optimize inventory. We’re not going to do it, we’re firmly anchored on the advertiser optimization side. But more than hope, I know it will be happen – just who does it, how and how quickly are the questions.