Meat in the Machine

Don Dodge has a characteristically thoughtful post here asking a bunch of good questions about why there seems to be such a big gap between the promise and the reality of online ad targeting:

Lots of startups and VCs are pinning their hopes on this simple premise. It seems obvious, but there is very little evidence to support it. So what is wrong?

  • Is the ad serving technology not able to take advantage of all this new “attention data” to better target the ads?
  • Are advertisers not willing to pay higher CPM rates for the better targeting?
  • Has ad targeting been tried with all this “attention data” and the results are not much better?
  • Is there just too much ad inventory which is depressing prices?
  • Are we just too early in the game to get good results?

Collectively, kind of.

To be more precise, starting at the top, the ad serving technology has not yet made it sufficiently easy for advertisers and their agencies to better target the ads.

Joe Blow Media Buyer

Sometimes tech folk forget that at the other end of the digital tentacles reaching across the ad-powered web, sooner or later, is a person pulling the levers. Joe Blow media buyer – think pimply-faced state college graduate 2-years out of school making $18K/year and living in Queens – simply can’t keep up with the pace of innovation on the web. They learn a few of the biggest ad targeting systems, which incidentally are the only ones with sufficient scale for them to complete their buys and move on, and crank 90% of their ad budgets through them. Once in a while one of the better ad network sales guys buys them some really good sushi and makes a decent case for some experiment, and voila, that technology gets thrown a $10K “test buy” bone.

If it works as promised – “works” being hard to both define and measure given the current cacophony of competing measurement standards and conflicting data – Joe may up the ante, and pay more for it on a CPM basis than he’d been willing to up to that point. Still, the equation he solves in his head:

  1. What is the probability that doing this will make me a hero with my boss and/or client?
  2. What is the probability that said boss and/or client is going to smack me for wasting time on this $35K diversion instead of doing everything I can to “optimize” the $500,000.00 buy we already have in process on Yahoo?
  3. Is the potential upside of 1. materially greater than the potential downside of 2.?

Goop in the Tranny

My point is simple: The reason all these Ferrari-esque ad targeting engines aren’t driving the wheels as fast as it seems they should is that there are a bunch of messy, imperfect, easily bored and overworked human beings gumming up the transmission.

The pace of progress in the ad targeting business will NOT be constrained by the capabilities of the technology to deliver improvements. The bottleneck is elsewhere… namely in Joe Blow’s ability to identify, grasp, and fully leverage the capabilities of that technology. That’s the lag, Don, at least IMHO.

Good News on the Horizon

So where are we in that process? Don refers to a pretty comprehensive post on the subject by CNET’s Stefanie Olsen, where she opines:

The first wave of Internet investing dealt with commercializing the Web, helping companies like and eBay get on their way. The second wave has been about helping people socialize and connect through sites like Flickr, YouTube, and Facebook. The third, venture capitalists say, will be about making sense of all the data people create around the Web, and then searching for patterns in the data to improve the delivery of personalized content, search results, or advertising.

Amen. I think we’re getting there, glad some smart folks on the VC side seem to agree.


2 Responses to Meat in the Machine

  1. Lee Hower says:

    Agree w/ all of the above. I’d add that another factor is that even w/ spiffy “hypertargeting” (FIM’s description these days) or whatever other newfangled targeting technology, a fairly large swathe of media buyers and marketers remain uncomfortable making buys against UGC.

    So perhaps social media properties and/or companies w/ unique targeting technology will be the data repositories (and thus economic beneficiaries, at least in part) of the future, either as buyers get comfortable w/ UGC or if this targeting happens off social media sites thru some form of inventory arb. But at present many social media properties still have to overcome the fundamental challenges to demand for their inventory.

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