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Today I read an article on SAI about how Online video that was re-posted from Dave Rayburn’s Streamingmedia.com.  The article inferred that online video will not replace TV in the near future because Akamai finally released some numbers on the actual number of live video streams during the World Cup and the numbers were underwhelming.

My thoughts are that there are some systematic problems with online video but this should not be confused with consumer demand for it.

Online video is pre-mature because of a couple things.  First of all you can’t get a decent stream.  Now this could be the CDN’s fault, the ISP’s fault for throttling bandwidth, or the content provider’s fault for purposefully not investing in decent quality video through the internet channels.  But the truth is it goes through the same line so it’s more of a business decision rather than a technical limitation.

The counter argument of, well people prefer to watch things on TV….. I’m not buying it.  Cable TV’s menu user experience is terrible.  Boxee, Apple TV, Hulu, Netflix, every one of them has a better UI, more selection and better customer experiences.  Also, now any computer can be plugged into a TV with an HDMI cable and give excellent picture and an iPhone or Droid can be used as the remote, so saying people prefer TV is just wrong.

Just like everything else in media it’s tied to advertising and the attribution model.  TV has a great racket going on for commercial spots.  The fact that you buy on a spot basis or TRP or GRP measurement basis is just silly.  The technology is there to buy and track it better, content providers, ISP’s and CDN’s are just choosing not to do it.  Right now they have created a similar setup to homepages online.  

The truth is Cable TV could be bought like exchange display advertising and the diversity and segmentation that’s going on in display will bring in a flood of new advertisers and faster moving transactions and I also believe competition will be driven up for the premium spot buys for national premier series like American Idol spots much like Yahoo’s homepage in Q4.

Right now companies like TidalTV and Simulmedia are working on solutions for this but don’t yet have access to do the transactions and sales (to my knowledge).  I look forward to this opening up, but I’m not waiting for them.

Attribution can be done on Cable TV right now and we will begin modeling it out in coming months and I look forward to integrating this attribution model with online.

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This is a continuation of my post on Friday discussing how the Supply side was affected by attribution modeling and, though I’m confident it will be a good thing for the ad market because I think online ads sell for too cheap these days, I can see how publishers are worried and advertisers could be too opportunistic.  That said let’s examine the Demand Side.

Supply = Publishers (Friday’s Post)

Demand = Advertisers (This Post)

Demand

Attribution modeling is truly an Advertisers dream.  Many publishers attempt to offer it like Doubleclick and Atlas’ Engagement mapping or the Advertising.com custom data mining offerings but there are inherent flaws because data is limited, the whole puzzle isn’t visible to the publisher, or advertisers are just skeptical that there could be a conflict of interest in that they are just trying to sell you more advertising.

Every marketer’s job is to buy advertising and make creative and then align the cost of doing so in an attempt to make it drastically cheaper to acquire new customers than what you are charging the customer.  The problem with this is that without a solid attribution model, you never truly know what piece of media and creative is actually driving that customer.  Furthermore it rarely is just one ad impression so the question becomes what combination of media over what time period (and what time interval) is the most cost efficient. 

Couple that with the fact that you either need to pay for each individual ad (like a homepage) or you pay for a result and you have no control over or have no way to track how and when the ads were shown (like a pay per click search text link) and you have quite a messy scenario.

So in the grand scheme of things there is only upside for the advertiser with attribution modeling but there is a major philosophical flaw.  Most marketers if they look at their marketing plan have customers that they think are for free.  Natural search traffic, organic traffic to your site, customers walking in or calling in and just buying a product.

So I will be bold enough to lay down the Cardinal Rules of Attribution Modeling:

1. There is no such thing as free traffic

2. There is no such thing as a free customer

3. If you have free traffic and free customers, your attribution model is BROKEN.

I will end with a ridiculous scenario and  prediction.  I personally think that the demand side of attribution modeling could be the fix to ad market growth and economic growth.  The reality is that we are doing less work and incurring less costs to acquire new customers, so therefore companies like Amazon, Google, and Yahoo can deliver sales to customers at a much lower overhead than newspaper, TV, and radio have done in the past.  This concentrates dollars in marketplace pricing scenarios and those dollars are then compressed because these businesses use their low TAC to offer low ad prices.

Based on economic principles alone, if every advertiser knew what ads truly drove their sales right now, they would double down their ad dollars.  That would double the ad market and pump twice as much money back into our economy and all problems would be solved.  THE END!

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So I recently engaged in a debate about how solving the attribution modeling problem could effect the ad market.  The conversation was broken into supply and demand where:

Supply = Publishers   (this post)

Demand = Advertisers  (the next post)

Supply

On the supply side solving the attribution modeling issue could affect publishers in a drastic way.  Since ad inventory is becoming so fluid as a result of companies creating marketplace environments out of their ad inventory, the value that an advertiser sees in an ad, could really affect a publisher’s business.

We already know that marketplace buying drastically compresses ad dollars.  We see that with advertisers who have pulled money out of newspapers and TV and put it into google.  Google takes these dollars and since they can deliver the eyeballs and customers at an incredibly inexpensive overhead cost, they allow advertisers to essentially set the price of each keyword ad.  Since there are so many keywords and relatively few bidders on each keyword and such low cost to deliver each incremental customer, this works extremely well so there is plenty of diversity for google to rely on their prices to continually rise as competition increases.

For display advertising it’s not the same.  A homepage 300x250 ad typically only has one advertiser per day and with 365 days in a year and between $50k - $2mm per day (depending on the site) that’s a lot of eggs in one basket for a publisher. 

So they are highly incented to keep advertisers from knowing the real value of their advertising and they can create scarcity in a high competition placement to drive up price.

The threat here is that if the small group of advertisers (it can’t be more than 365) all know exactly how much this placement is worth to them, they can hold the publisher hostage on price.

I think that gives an idea of two polar opposite sides of the spectrum for the supply side.  One area with a lot of diversity and little competition where having true attribution and REAL pricing will not threaten a publisher’s business model and another where little diversity and high competition if attribution is introduced could curb that high competition and cause problems for a publisher.

There is also the fact that REAL pricing and a sound attribution model could make advertisers identify what really drives incremental sales in which case all publishers win!

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Going back to a startup environment from a large corporate environment definitely has it’s upsides and downsides.  The good part is the upside for those who aren’t afraid to work hard is typically worthwhile.

The upside is that at a large corporation you have a huge support team.  For the morale support (drink the kool aid, corp culture), for the financial support of a reliable large paycheck every two weeks, and the physical support of thousands of co-workers (though they sometimes seem inefficient) end up doing a lot of the heavy lifting based on your strategic decisions.

This can be good and bad.  Good because you get paid for being smart. You are valued for the work you have done in the past, and the resume you have built. Your life becomes a series of meetings and you steam roll forward on a large complex agenda.  Your valued for what you know and your experience and you don’t have to mess with spreadsheets and computer code and the physical headaches that come with…….well hard work.

That said, some of us aren’t cut out for the large personal office job with the assistant on the 23rd floor of a San Francisco high rise over-looking North Beach.  Some people are meant to do the busy work and gravitate to being stressed out.  They create tight deadlines biting off more than they can chew and they are okay with not being paid much in the short term in hopes of a slight chance at a large payoff in the distant future.

Here’s the upside.  As it turns out doing the hard work is where the ideas come from.  Talking about something strategically like “Well yea, of course you can model out attribution and track it to the impression level and bid on it in realtime with an automatic machine learning algorithm and display it in realtime in a slick web interface.”  But then you sit down and you try to do it and you realize it’s a massive undertaking and there are thousands of details that need to be thought through, calculated out, and coded and all the top level dynamic language frameworks and NOsql databases in the world can make a plan like that come together easily.

Also, at a large company when you manage through a major deal or a major product launch the emotional payoff just isn’t that great.  All you really did was state the vision and work through the politics and clear internal barriers so that other people could do the work. On launch day, it’s just not that exciting and often times the final product really doesn’t have a place for you anymore anyway.

The flip side of that is when you hack though the most minuscule detail of a small corner of your larger idea on your own at a startup it just feels better. Something as simple as the first impression displays in the reporting, you’re ready to throw a office wide party and stand on your desk and announce VICTORY!

After being on the outside for about a month, my eyes have been opened in ways I can’t even explain.  I go home with a headache each day and find my mind racing at night instead of sleeping but the thing is, it just feels better knowing that I’m doing the work.

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I got into a discussion with @durana today about doing some simple calculations on real-time display ad data.  I pointed out to him that if we are looking at a real-time flow of data coming in of say display ad impressions and clicks and page views and we were to calculate a click-thru rate or conversion rate that the data would look really messy and lack integrity.

My fear was that a media buyer is used to looking at daily conversion rates and click thru rates and we are watching a 24 or 48 hour build of data flow in before our eyes, then rates could be inflated or deflated.  He then pointed out that in fact this would be more accurate.

Now, I know we need to consider re-set cookies and new cookies and all of that but….I mean do you really?  If you are truly looking at real-time data flow in the door and you have a real-time bidding engine to take advantage of that and you can look at users flow through specific sites and audiences from Impression, to Click, and/or to page view, and then to sale and cascade from audience to audience…….then you don’t need to do as much sampling and data validating.  You just need to know the cost that you are incurring in real-time and how much that would go up or down based on the click-thru rate and conversion rate that you are looking at and estimate the impact. 

Also, if you are looking at the effect of your change in real-time then you can make up for any inaccuracies so quickly that it doesn’t matter in the first place considering accuracy is only valuable if time passes between when you take action and receive the data on the outcome of your action.  But you are acting in real-time and can get the results in real-time, then why so accurate???

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I came across a post by Brad Terrell talking about the Appnexus Innovation summit and he highlights the topic of targeting sites vs. targeting audiences.

He goes on to talk about two different ad networks, their differences and gives emerical evidence of his thoughts:

Adam also illustrated the value creation potential of the audience-driven approach to targeting by pointing out how the enterprise value of a representative “old school” ad network, Burst Media, paled in comparison to the much higher enterprise value of a newer “audience-driven” ad network, interCLICK

 - Please read the whole post as this could be considered out of context and its worth reading the whole post http://loca.ly/couk6j

So I think about this from a entrepreneur’s perspective and I completely agree.  Advertisers and Marketers cling to what is new and there is continual pressure to do a better job and take advantage of the newest technologies and methods possible.

That said, DON’T OVERLOOK SITE TARGETING.  Audience targeting if done properly with re-targeting or search keyword re-targeting such as with Magnetic.is can be very powerful and literally spin gold when it comes to bottom of the funnel and making sure you get in-market sales.  

Beyond this however lies the ocean of ad impressions that are still being boiled by the likes of the big ad networks and exchanges.  I recently had a conversation with the VP of Operations at one of the larges online ad agencies pitching my business and knowing that I used to sell to him I asked, well what do you think I should be buying.  He responded, that when you are doing direct response advertising where you need to hit a specific ROI to continue to invest, what you do is buy all of the ad networks and optimize the best you can.  He said DSP’s are great for getting that re-targeting audience and a couple other segments but largely a lot of the audiences do not work and there are so many of them that even if there is an optimal audience, you will waste a lot of money trying to find it.

From my experience on the sales side on any given campaign there were 2-3 audiences that really worked on any given campaign (one being re-targeting) and the rest of the heavy lifting was done by site optimization and frequency within site optimization.  In fact the most important driver is something that I rarely hear people selling on or creating business models on, which is site frequency and the fact that the first few impressions (1-3) are in fact the most valuable by a long shot.  Most publishers know this and technology lends to selling this easily but for some reason it is not sold out there on the open market.

Furthermore there is also a lot of evidence that brand name new sites and mail sites such as LA Times, NY Times, Yahoo Mail, AOL Mail and others similar create the most ROI impact if bought at the right frequency and attributed properly…..which leads to attribution modeling which is a whole other post which I probably need to write more on.  That said, if bought through an ad network or exchange often you get the higher site-frequency impressions and these sites don’t appear to work as well.  If bought directly, you have the burden of paperwork and exorbitantly high prices to get access to the right impressions of this media.

So because they have such a broad view of their buys I think a great new frontier for ad networks SSP’s, and DSP’s is to sell based on site-frequency.  They have this data and often know where they are in the publisher daisy chain and can aggregate supply across many sites and can efficiently convert this into a fluid buy.  

And, I would buy it…..

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