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Archive for June, 2010


When Competitors Aren’t As Smart As You Think They Are

Monday, June 28th, 2010

Recently, Google went public and announced what their revenue share was for people participating in Google Adsense for Content: 68%.

I have to tell you, I have rarely been so disappointed.  When my friends and I talked about the magic of Google’s black box (“They get publishers to sign up and they don’t even tell them how much money they will make!”), we always thought of hundreds of ways that you could micro-optimize.  Ways we assumed Google was doing, because why not tell everyone if it doesn’t matter.

We assumed that Google was tracking the quality of publisher inventory using some sort of aggregated back-end performance (CPA-ish) algorithm.  We assumed they identified clicks that performed poorly.  We assumed that they took all this information about what sites had great performing clicks and what sites had poor performing clicks and then fine-tuned rev share, giving higher payouts to better quality inventory while punishing lower quality inventory.  This would then theoretically have the effect of subsidizing good inventory, resulting in abnormally high payouts, keeping the best inventory in the network, while pushing bad inventory out of the network.

What does bad inventory look like in a CPC campaign?  There are no shortage of gaming sites where you play a mouse-based game that requires you click all over the screen quickly, then they wrap ads all the way around the game.  The result is a lot of bad clicks.  On the one hand, you generate a lot of revenue charging CPCs on this inventory.  (You can typically generate CTRs of 3%+) On the other, none of these clicks result in any time actually on site or resulting in backend conversions.  We always assumed that Google punished these people algorithmically.  We even knew how we would do it.  The algorithms are easy to figure out.  All you need is to not be locked into a rev share with a publisher, but instead have the flexibility to vary a publishers rev share at any time.  Alas, only one company had the clout to do that: Google.

To hear Google’s mea culpa, that they had a straight rev share that they have applied for the last several years without any of this payout optimization reminds you that, while it pays to be paranoid, they are rarely actually after you!

A free billion dollar problem

Thursday, June 24th, 2010

When I first joined, one of the calculations that led me to join was that it seemed like the market was poised for explosive growth, far above and beyond expectations.  Here was my off-the-cuff theory:

  • Online was 5% of US media spend
  • Online was 17% of US media consumption
  • Until those two numbers are the same, people are getting better value advertising online than anywhere else (arbitrage), so those two numbers will gradually come into alignment.

That made me think that the market would grow 20%+ YoY for several years, because I didn’t think that 17% would get any smaller.

Lo and behold, I was right about that, at least.  Today the numbers are headed in the right direction:

  • 12% of US media spend is online
  • 30% of US media consumption is online
  • So, far from coming together, these two numbers, while increasing rapidly, are actually diverging.

My new theory as to why this is: Advertising online sucks.  It simply doesn’t work as well as advertising on TV.  So TV is getting a disproportionate amount of advertising dollars relative to its media consumption because it works better than online advertising.  And that is not too surprising.  728x90s suck.  They don’t tell a story.  They are like tiny magazine ads.

TV ads have a story arc.  They have punch lines.  They are visually stimulating.

Targeting and measurability and all the stuff that most people in online advertising do is great.  They create a situation where advertising theoretically could work better by being more personalized.  Flight prices to Vegas from your city are not what we are talking about, though.  Without a fundamental change in the kinds of creatives that big brands can put out there, online ads simply won’t work as well, at least in a subjective sense for advertisers.

Solving this problem is hard.

First, we must overcome prohibitive expense.  People already spend way more outside of buying media when prepping an online campaign then they ever did for TV.  You build some web site with some viral thing on it, and all that stuff.  That is great.  If a consumer wants to engage with your brand, you want that brand experience to be awesome.  But the first step in engagement is seeing an awesome ad.  If you asked the top X agencies today if they would prefer a consumers first interaction with a brand be via a 160×600 or a 30 second spot, I think you would struggle to get anyone to say the web banner.  Making these great ads is expensive though and someone has to do it.

Second, there must be a visionary industry breakthrough.  Even if we knew how to do it all affordably, I don’t know that we would crack the nut anyway.  What do awesome ads look like?  Punch the monkey captured the imagination.  I just named a 728×90 ad that people actually recognize (although I don’t know what they were selling).  Dancing Lower My Bills ads?  These caught the eye but in a way that left me angry and bitter.  I don’t think Teracent or Tumri is solving this problem.  Making the ad green or blue or blue-green may increase the odds that I click, but it doesn’t vault the ad into the pantheon of great advertising moments.  At least not mine.

Everything that I see in the market is evolutionary and incremental, but this is not the time for incremental.  We are in the first inning.  You are not standing on the shoulders of giants, you are standing on a speck of dust.  There is so much room for change that we need people to swing for the fences.

Let this be a call to entrepreneurs.  If you figure out how to make great ads online, you get a billion dollars.

Have you considering sponsoring CogBlog?

Tuesday, June 22nd, 2010

I think it is safe to say that everyone who reads Cogblog is a believer in Commerce and/or a believer in Advertising.  Now you can represent for your beliefs by buying ad space on the mighty Cogblog.  Every weekly or monthly sponsor receives a Cogmug, the official coffee cup of Cogmap.

Let me know if you have any trouble.

RTB Disrupts Yield Optimizers with Global Cookie Machine

Tuesday, June 22nd, 2010

A couple of things about RTB that everyone already knew, but I wanted to make sure got documented by someone:

  1. RTB has dramatically skewed the balance of technological sophistication required by buyers and sellers of ad inventory.  It used to be that ad buyers only had to operate on impressions they bought.  Now they need to look at impressions and decide what they are worth prior to buying.  And that decision needs to be made in less than 150 milliseconds.  Ad buying technology is changing quickly.
  2. The ad sellers world has not changed nearly as much.  Most ad sellers had a yield optimizer before that algorithmically guessed about how the daisy chain should be arranged.  Now they simply RTB the impression.  The technology used by the yield optimizer has actually gotten much simpler – there is no longer any optimization.  You simply take the impression and RTB it.  There is no calculation, no learning, no consideration of past performance.  Easy.
  3. Ad Buyers need algorithms and technology to bid in this new world.  One of the interesting ways that I always characterized AdLearn,’s algorithm (and this is painting in somewhat inaccurate, extremely broad strokes, so don’t think you are finding anything in here or that I am giving you some interesting information.  This is not accurate.) was that it was an algorithm that worked well in situations with poor context.  Unlike Google, which scraped the page and attempted to show contextually relevant ads, AdLearn started with no assumptions and generated learnings.  What this means is that some inventory, from an algorithmic persepective, was more likely to yield good performance than other inventory for different networks. My personal prediction was that’s predictions would tend to work better on MySpace than Google’s algorithm.  Your algorithm has an inventory sweet spot also.  Know what it is.
  4. RTB could, more accurately, be called “Real-time cookie inspection”.  I don’t think people are actually changing their bids in real-time.  Formulating a good bid takes time.  Frankly, in our current environment, most of this formulation is called “Media Planning”.  A media planner deduces that we should pay $8 for people with this data attribute at a given frequency.  Blamo, bid calculation complete.  After this, we RTB to look for two things: The frequency cap value  and other data attributes we are tracking.  Bidding: nil.  Cookie inspection: Potentially billions of times per day.

God forbid I am mischaracterizing the world, if you are a company that is changing your bids more than once a minute per campaign and the change is more than simply random variation to test bid strength, let me know!  I would love to hear your story.

Thoughts on Invite Media

Thursday, June 17th, 2010

Every time I talk to people about this transaction, I have the same talking points.  I figured I should put them out there:

  1. Invite Media is written virtually entirely in Python, the language of Google-ness.  I would expect to see a more seamless transition to Google-ey-ness than we did with JotSpot, Feedburner, or DoubleClick, where things disappeared (for, in some cases, years) while they were being re-written in Python – Google’s preferred mode of acquisition integration.  That probably allows Google to get a little more excited than they might otherwise.
  2. If you are Invite Media and Google calls and tells you they are acquiring a DSP, that DSP has to be you, right?  Google’s acquisition of Invite has taken the biggest acquirer out of the market, dropping the valuation of all the DSPs.  You do not want to be the one that does not get bought.  This probably means that Invite was open to a lower price since it was the best possible acquirer.
  3. I imagine a world where Invite technology is suddenly free.  Most people thought that Invite had the best UI in the market and most people agree that the UI for interacting directly with the exchanges sucks.  Given the 8-figure price tag (cheaper than many other deals they have done), it is easy to imagine that Google’s ROI is off the charts here.  They can probably make all that money back by driving more volume through the DoubleClick exchange front-running impressions and increasing volume via a great free UI.

The DSP landscape will be rocked if Google suddenly announces that they are giving away Invite technology to agencies.  People better be bringing their A-game.

Congrats to Nat and Zach.

View-through is not a success metric

Tuesday, June 15th, 2010

True or False: Current usage of view-through conversions is not a success metric customers benefit from, but rather a pricing mechanism by which agencies are able to imply a correlation with performance while networks are able to use their reach to spend large budgets, pleasing all parties except the advertiser.