Category Archives: Ad Technology

Nov 08 2012
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Ad Ecosystem, Ad Serving, Ad Technology, Economics, Media Agencies, Online Media, Publishers

How ad platforms work (and why you should care)

(By Eric Picard, Originally Published in iMediaConnection, 11/8/12)

Ad platforms are now open, meaning that startups and other technology companies can plug into them and take advantage of their feature sets. The ad technology space is now API driven, just like the rest of the web technology space. The significance of this change hasn’t hit a lot of people yet, but it will. The way this change will affect almost all the companies in ad technology will have an impact on everything: buying, selling, optimization, analytics, and investing.

Companies in our space used to have to build out the entire ad technology “stack” in order to build a business. That meant ad delivery (what most people think of as “ad serving”), event counting (impressions, clicks, conversions, and rich media actions), business intelligence, reporting, analytics, billing, etc. After building out all those capabilities, in a way that can scale significantly, each company would build its “differentiator” features. Many companies in the ad technology space have been created based on certain features of an ad platform. But because the ad platforms in our space were “closed,” each company had to build its own ad platform every time. This wasted a lot of time and money and — unbeknownst to investors — created a huge amount of risk.

Almost every startup in the ad platform space has existed at the whim of Google — specifically because of DoubleClick, the most ubiquitous ad platform in the market. When Google acquired DoubleClick, its platform was mostly closed (didn’t have extensive open APIs), and its engineering team subsequently went through a long cycle of re-architecture that essentially halted new feature development for several years. The market demanded new features — such as ad verification, brand safety, viewable impressions, real-time bidding, real-time selling, and others — that didn’t exist in DoubleClick’s platform or any others with traction in the space.

This led to the creation of many new companies in each space where new features were demanded. In some cases, Google bought leaders in those spaces. In others, Google has now started to roll out features that replicate the entirety of some companies’ product offerings. The Google stack is powerful and broad, and the many companies that have built point solutions based on specific features that were once lacking in Google’s platform suddenly are finding themselves competing with a giant who has a very advanced next-generation platform underlying it. Google has either completed or is in the process of integrating all of its acquisitions on top of this platform, and it has done a great job of opening up APIs that allow other companies to plug into the Google stack.

I’ve repeatedly said over the years that at the end of the natural process this industry is going through, we’ll end up with two to three major platforms (possibly four) driving the entire ecosystem, with a healthy ecosystem of other companies sitting on top of them. Right now, our ecosystem isn’t quite healthy — it’s complex and has vast numbers of redundancies. Many of those companies aren’t doing great and are likely to consolidate into the platform ecosystem in the next few years.

So how does the “stack” of the ad platform function? Which companies are likely to exist standalone on top of the stack? Which will get consumed by the stack? And which companies are going to find themselves in trouble?

Let’s take a look.

How ad platforms work (and why should you care)

Pretty much every system is going to have a stack that contains buckets of services and modules that contain something like what you see above. In an ideal platform, each individual service should be available to the external partner and should be consumable by itself. The idea here is that the platform should be decomposable such that the third party can use the whole stack or just the pieces it needs.

Whether we’re discussing the ubiquitous Google stack or those of competitors like AppNexus, the fact that these platforms are open means that, instead of building a replica of a stack like the one above, an ad-tech startup can now just build a new box that isn’t covered by the stack (or stacks) that it plugs into. Thus, those companies can significantly differentiate.

This does beg the question of whether a company can carve out a new business that won’t just be added as a feature set by the core ad platform (instantly creating a large well-funded competitor). To understand this, entrepreneurs and investors should review the offering carefully: How hard would it be to build the features in question? Is the question of growing the business one of technical invention requiring patents and significant intellectual property, or is it one of sales and marketing? Is the offering really a standalone business, or is it just a feature of an ad platform that one would expect to be there? And finally, will the core platforms be the acquirer of this startup or can a real differentiated business be created?

The next few years will be interesting. You can expect these two movements to occur simultaneously: Existing companies will consolidate into the platforms, and new companies will be created that take advantage of the new world — but in ways that require less capital and can fully focus on differentiation and the creation of real businesses of significance.

Oct 25 2012
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Ad Ecosystem, Ad Technology, Economics, Media Agencies, Online Media, Predictions, Publishers, Startups

How Do Companies Make Any Money in Digital?

(By Eric Picard, Originally Published in AdExchanger 10/25/12)

In 2007 I wrote a paper that analyzed the lack of investment from 2001 to 2006 in the basic infrastructure of ad technology.  The dot-com bubble burst had a chilling effect on investment in the ad tech space, and as an industry we focused for about six years on short term gains and short term arbitrage opportunities.

This period saw the rise of ad networks and was all about extracting any value possible out of existing infrastructure, systems, and inventory.  So all the “remnant” inventory in the space, the stuff the publisher’s in-house sales force couldn’t sell, got liquidated at cheap prices.  And those companies with the willingness to take risk and the smarts to invest in technology to increase the value of remnant got off the ground and succeeded in higher efficiency buying and selling, and lived off the margins they created.

But we lost an entire cycle of innovation that could have driven publisher revenue higher on premium inventory – which is required for digital to matter for media companies. There’s been lots of discussion about the drop from dollars to dimes (and more recently to pennies) for traditional media publishers. And while the Wall Street Journal and New York Times might be able to keep a pay-wall intact for digital subscriptions, very few other publications have managed it.

In 2006 the ad tech ecosystem needed a massive influx of investment in order for digital to flourish from a publisher perspective.  These were my observations and predictions at the time:

  • Fragmentation was driving power from the seller to the buyer. Like so:
  • A lack of automation meant cost of sales for publishers, and cost of media buying management for agencies, were vastly higher in digital (greater than 10x what those things cost for traditional on both the buy and sell side).
  • Prices were stagnated in the digital space because of an over-focus on direct response advertisers, and the inability of the space to attract offline brand dollars.
  • Market inefficiency had created a huge arbitrage opportunity for third parties to scrape away a large percentage of revenue from publishers. Where there is revenue, investment will follow.
  • There was a need for targeting and optimization that existing players were not investing in, because the infrastructure that would empower it to take off didn’t exist yet.
  • Significant investment would soon come from venture capital sources that would kick start new innovation in the space, starting with infrastructure and moving to optimization and data, to drive brand dollars online.

Six years later, this is where we are. I did predict pretty successfully what would happen, but what I didn’t predict was how long it would take – nor that the last item having to do with brand dollars would require six  years. This is mainly because I expected that new technology companies would step up to bat across the entirety of what I was describing.  Given that the most upside is on brand dollars, I expected entrepreneurs and investors to focus efforts there.  But that hasn’t been the case.

So what’s the most important thing that has happened in the last six years?

The entire infrastructure of the ad industry has been re-architected, and redeployed.  The critical change is that the infrastructure is now open across the entire “stack” of technologies, and pretty much every major platform is open and extensible. This means that new companies can innovate on specific problems without having to build out their own copy of the stack.  They can build the pieces they care about, the pieces that add specific value and utility for specific purposes – e.g. New Monetization Models for Publishers and Brand Advertisers, New Ad Formats, New Ad Inventory Types, New Impression Standards, New Innovation across Mobile, Video and Social, and so on.

So who will make money in this space, how will they make it, and how much will they make?

I’ve spent a huge portion of my career analyzing the flow of dollars through the ecosystem. Recently I updated an older slide that shows (it’s fairly complex) how dollars verses impressions flow.

The important thing to take away from this slide is that inventory owners are where the dollars pool, whether the inventory owner is a publisher or an inventory aggregator of some kind.  Agencies have traditionally been a pass-through for revenue, pulling off anywhere from 2 to 12% on the media side (the trend has been lower, not higher), and on average 8 to 10% on the creative side depending on scale of the project.  Media agencies are not missing the point here, and have begun to experiment with media aggregation models, which is really what the trading desks are – an adaptation of the ad network model to the new technology stack and from a media agency point of view.

The piece of this conversation that’s relevant to ad tech companies is that so far in the history of this industry, ad technology companies don’t take a large percentage of spend.  In traditional media, the grand-daddy is Donovan Data Systems (now part of Media Ocean), and historically they have taken less than 1% of media spend for offline media systems. In the online space, we’ve seen a greater percentage of spend accrue to ad tech – ad serving systems for instance take anywhere from 2 to 5% of media spend.

So how do ad tech companies make money today and going forward? It’s a key question for pure transactional systems or other pure technology like ad servers, yield management systems, analytics companies, billing platforms, workflow systems, targeting systems, data management platforms, content distribution networks, and content management systems.

There’s only so much money that publishers and advertisers will allow to be skimmed off by companies supplying technology to the ecosystem. In traditional media, publishers have kept their vendors weak – driving them way down in price and percentage of spend they can pull off. This is clearly the case in the television space, where ad management systems are a tiny fraction of spend – much less than 1%.

In the online space, this has been less the case, where a technology vendor can drive significantly more value than in the offline space. But still it’s unlikely that any more than 10% of total media spend will be accepted by the marketplace, for pure technology licensing.

This means that for pure-play ad tech companies with a straightforward technology license model – whether it’s a fixed fee, volume-based pricing, or a  percentage of spend – the only way to get big is to touch a large piece of the overall spend. That means scaled business models that reach a large percentage of ad impressions.  It also means that ultimately there will only be a few winners in the space.

But that’s not bad news. It’s just reality.  And it’s not the only game in town. Many technology companies have both a pure-technology model, and some kind of marketplace model where they participate in the ecosystem as an inventory owner. And it’s here that lots of revenue can be brought into a technology company’s wheelhouse. But its important to be very clear about the difference between top-line media spend verses ‘real’ revenue. Most hybrid companies – think Google for AdSense, or other ad networks – report media spend for their marketplaces as revenue, rather than the revenue they keep. This is an acceptable accounting practice, but isn’t a very good way to value or understand the value of the companies in question. So ‘real revenue’ is always the important number for investors to keep in mind when evaluating companies in this space.

Many ad technology companies will unlock unique value that they will be the first to understand. These technology companies can capitalize on this knowledge by hybridizing into an inventory owner role as well as pure technology – and these are the companies that will break loose bigger opportunities. Google is a great example of a company that runs across the ecosystem – as are Yahoo, Microsoft and AOL.  But some of the next generation companies also play these hybrid roles, and the newest generation will create even greater opportunities.

Oct 11 2012
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Ad Ecosystem, Publishers, Rich Media

Why publishers’ ad experiences need to be more flexible

(By Eric Picard, Originally Published in iMediaConnection.com October 11, 2012)

In 2004, I was recruited to Microsoft, where among other things I was put in charge of coming up with a new plan for the overall advertising experience for MSN and, soon after, Windows Live. I spent about eight months digging into the advertising experience as it then existed and tried to rationalize how advertising should work on a major site like MSN and across a variety of user experiences.

In an early meeting with a group of folks from the sales team, Gayle Troberman made a fateful suggestion: “You really need some kind of framework for assessing what kind of ad fits in what kind of experience.” This was a key suggestion because it forced me to assemble a cross-disciplinary team and create a shared language that drove numerous long-term decisions.

The first-order considerations were driven by “user modality,” which is defined as the behavior and related mindset that a user is engaged in during specific activities. We needed to determine which advertising experiences were acceptable in each type of modality that existed across the myriad experiences on our properties. By carefully considering modality, we were able to create a set of guidelines for what advertising should be enabled in each type of environment.

To illustrate the point, let me give a few key examples of what we put together:

  • Users who are reading email are open to advertising experiences that are relevant and non-invasive, but that are not explicitly targeted to that user based on the content of the mail — which just is creepy.
  • Users who are writing email are not open to advertising experiences.
  • Users who have sent email are open to a broader ad experience with a larger format ad.
  • Users who are reviewing a home page or section front are open to a large format ad.
  • Users who are reading an article are open to non-invasive ads that can be large format as long as they don’t encroach on the reading experience.

The guidelines I created with that team quickly became the overall framework used by Microsoft to drive advertising experiences across all content experiences across MSN, Windows Live, and even in a variety of emerging media experiences. My “day job” at the time was managing product planning for emerging media, which at that time included video, over-the-top television, mobile, video games, software applications, and new device formats (e-readers, tablets and other device prototypes, Zune, etc.).

Some key principles that I came up with include the following:

  • Ensure that ad clutter is kept to a minimum. It’s better to have one very large-format ad on a page than five small-format ads.
  • Ensure that ads have enough white space around them.
  • Give the user the ability to give feedback about ads (both positive and negative) — such as rating ads.
  • Be transparent about behavioral targeting of ads, including how an ad was targeted to them and what profile information we stored about users. Enable users to correct and enhance their targeting profiles. (This was the most controversial of my recommendations and was discussed at length.)
  • Enable every ad unit to become “rich media enabled” with specific templatized enhancements, such as a store locator, a pop-up video unit, RFI, and others.

Like many efforts I’ve been engaged in over the years, this one met with a mixture of success and failure. It took almost five years before we enacted most of the privacy and targeting features I recommended. And none of the rich media templates ever saw the real world. But the user modality guidelines were a huge hit — maybe in a sense these were too successful. Sometimes the creation of a set of clearly defined “rules” empowers folks who are embedded more deeply in an organization to say “no” to next efforts very quickly. This is often the case with any standards effort, whether at the industry level or within a specific organization.

I experienced this one day when I was trying to roll out a new set of ad formats for software applications. I sat down with the product manager in charge of the effort, and when I started walking him through the prototypes, he quickly stopped me with a clear set of concerns: “Uhm… look — these ad formats clearly don’t fit the ad experience framework we use here. So I’m just going to have to say ‘no.'”

Of course, once he learned that I had written those guidelines, the conversation was reopened. But this is an important lesson. Core principles always need to be flexible enough to allow testing the edges and borders of experiences. Once a new content experience is rolled out, an ad experience needs to be tried out with it. Sometimes that new experience doesn’t fit in the guidelines you’ve created.

Oct 05 2012
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Ad Ecosystem, Ad Technology, Economics, Media Agencies, Online Media, Predictions, Publishers, Startups

5 Important Memes for the Digital Advertising Industry

Oct 05 2012
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Ad Ecosystem, Ad Serving, Ad Technology, Economics, Online Media, Predictions, Startups

Entering the Fourth Wave of Ad Technology

By Eric Picard (Originally published on AdExchanger.com, 9/18/2012)

Ad tech is a fascinating and constantly evolving space.  We’ve seen several ‘waves’ of evolution in ad tech over the years, and I believe we’re just about to enter another.  The cycles of investment and innovation are clearly linked, and we can trace this all back to the late 90’s when the first companies entered the advertising technology space.

Wave 1

The early days were about the basics – we needed ways to function as a scalable industry, ways to reach users more effectively, systems to sell ads at scale, systems to buy ads at scale, analytics systems, targeting systems, and rich media advertising technology.

There was lots of investment and hard work in building out these 1.0 version systems in the space. Then the dot-com bubble imploded in 2001, and a lot of companies went out of business.  Investment in the core infrastructure ground to a halt for years. The price of inventory dropped so far and so fast that it took several years before investment in infrastructure could be justified.

We saw this wave last from 1996 through 2001 or 2002 – and during that dot-com meltdown, we saw massive consolidation of companies who were all competing for a piece of a pie that dramatically shrank.  But this consolidation was inevitable, since venture firms generally invest on a five to ten year cycle of return – meaning that they want companies to exit within an ideally 8 year window (or less).

Wave 2

The second wave was really about two things: Paid Search and what I think of as the “rise of the ad networks.”  Paid search is a phenomenon most of us understand pretty well, but the ad network phase of the market – really from 2001 to 2007 was really about arbitrage and remnant ad monetization.  Someone realized that since we had electronic access to all this inventory, we could create a ‘waterfall’ of inventory from the primary sales source to secondary sources, and eventually a ‘daisy-chain’ of sources that created massive new problems of its own.  But the genie was out of the bottle, and this massive supply of inventory that isn’t sold in any other industry was loosed.

It’s actually a little sad to me, because as an industry we flooded the market with super cheap remnant inventory that has caused many problems. But that massive over-supply of inventory did allow the third wave of ad tech innovation to get catalyzed.

Wave 3

Most people believe that the third wave was around ad exchanges, real-time buying and selling, data companies, and what I like to call programmatic buying and selling systems. But those were really just side effects. The third wave was really about building out the next generation infrastructure of advertising. Platforms like AppNexus and Right Media are not just exchanges; they’re fundamentally the next generation infrastructure for the industry.  Even the legacy infrastructure of the space got dramatic architectural overhauls in this period – culminated by the most critical system in our space (DoubleClick for Publishers) getting a massive Google-sponsored overhaul that among other thing opened up the system via extensive APIs so that other technology companies could plug in.

Across the board, this new infrastructure has allowed the myriad ad tech companies to have something to plug into.  This current world of data and real-time transactions is now pretty mature, and it’s extending across media types.  Significant financial investments have been made in the third wave – and most of the money spent in the space has been used to duplicate functionality – rather than innovate significantly on top of what’s been built.  Some call these “Me too” investments in companies that are following earlier startups and refining the model recursively.  That makes a lot of sense, because generally it’s the first group of companies and the third group of companies in a ‘wave’ that get traction. But it leads to a lot of redundancy in the market that is bound to be corrected.

This wave lasted from about 2005 to 2011, when new investments began to be centered on the precepts that happened in Wave 3 – which really was a transition toward ad exchanges (then RTB) and big data.

That’s the same pattern we’ve seen over and over, so I’m confident of where the industry stands today and that we’re starting to enter a new phase. This third major ad tech wave was faster than the first, but a lot of that’s because the pace of technology adoption has sped up significantly with web services and APIs becoming a standard way of operating.

Wave 4

This new wave of innovation we’re entering is really about taking advantage of the changes that have now propagated across the industry. For the first time you can build an ad tech company without having to create every component in the ‘stack’ yourself. Startups can make use of all the other systems out there, access them via APIs, truly execute in the cloud, and build a real company without massive  infrastructure costs.  That’s an amazing thing to participate in, and it wasn’t feasible even 3 years ago.

So we’ll continue to see more of what’s happened in the third wave – with infrastructure investments for those companies that got traction, but that’s really just a continuation of those third wave tech investments, which go through a defined lifecycle of seed, early, then growth stage investments.  Increasingly we’ll see new tech companies sit across the now established wave 3 infrastructure and really take advantage of it.

Another part of what happened in Wave 3 was beyond infrastructure – it involved the scaled investment in big data.  There have been massive investments in big data, which will continue as those investments move into the growth phase. But what’s then needed is companies that focus on what to do with all that data – how to leverage the results that the data miners have exposed.

Wave 4 will really change the economics of advertising significantly – it won’t just be about increasing yield on remnant from $0.20 to $0.50. We’ll see new ad formats that take advantage of multi-modal use (cross device, cross scenario, dynamic creatives that inject richer experiences as well as information), and we’ll see new definitions of ad inventory, including new ad products, packages and bundles.

So I see the next five years as a period where a new herd of ad tech companies will step in and supercharge the space. All this infrastructure investment has been necessary, because the original ad tech platforms were built the wrong way to take advantage of modern programming methodologies.  Now with modern platforms available pretty ubiquitously, we can start focusing on how to change the economics by taking advantage of that investment.

I also think we’re going to see massive consolidation of the third wave companies. Most of the redundancies in the market will be cleaned up.  Today we have many competitors fighting over pieces of the space that can’t support the number of companies in competition – and this is clearly obvious to anyone studying the Lumascape charts.

Unfortunately some of the earlier players who now have customer traction are finding that their technology investments are functionally flawed – they were too early and built out architectures that don’t take advantage of the newer ways of developing software. So we’ll see some of these early players with revenue acquiring smaller newer players to take advantage of their newer more efficient and effective architectures.

Companies doing due diligence on acquisitions need to be really aware of this – that buying the leader in a specific space that’s been around since 2008 may mean that to really grow that business they’ll need to buy a smaller competitor too – and transition customers to the newer platform.

For the investment community it’s also very important to understand that while Wave 3 companies that survive the oncoming consolidation will be very big companies with very high revenues, it is by nature that these infrastructure heavy investments will have lower margins and high volume (low) pricing to hit their high revenues. They still will operate on technology/software revenue margins – over 80% gross margins are the standard that tech companies run after. But the Wave 3 companies have seen their gross revenue numbers be a bit lower than we’d like as an industry.  This is because they are the equivalent of (very technically complex) plumbing for the industry.  There are plenty of places where they invest in intelligence, but the vast majority of their costs and their value deal with massive scale that they can handle, while being open to all the players in the ecosystem to plug in and add value.

Being a Wave 4 company implicitly means that you are able to leverage the existing sunk cost of these companies’ investment.  Thomas Friedman talks about this in “The World is Flat” – one of his core concepts is that every time an industry has seen (what he called) over-investment in enabling infrastructure, a massive economic benefit followed that had broad repercussions.  He cites the example of railroad investment that enabled cheap travel and shipping that led to a massive explosion of growth in the United States.  He cites the investment in data infrastructure globally that led to outsourcing of services to India and other third world countries on a massive scale.  And frequently those leveraging the sunk cost of these infrastructure plays make much more money from their own investments than those who created the opportunity.

So what should investors be watching for as we enter this fourth wave of ad tech innovation?

  1. Companies that are built on light cloud-based architectures that can easily and quickly plug into many other systems, and that don’t need to invest in large infrastructure to grow
  2. Companies that take advantage of the significant investments in big data, but in ways that synthesize or add value to the big data analysis with their own algorithms and optimizations
  3. Companies that can focus the majority of technical resources on innovative and disruptive new technologies – especially those that either synthesize data, optimize the actions of other systems, or fundamentally change the way that money is made in the advertising ecosystem
  4. Companies that are able to achieve scale quickly because they can leverage the existing large open architectures of other systems from Wave 3, but that are fundamentally doing something different than the Wave 3 companies
  5. Companies that take advantage of multiple ecosystems or marketplaces (effectively) are both risky but will have extremely high rewards when they take off

This is an exciting time to be in this space – and I predict that we’ll see significant growth in revenue and capabilities as Wave 4 gets off the ground that vastly eclipse what we’ve seen in any of the other waves.

Aug 14 2012
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Ad Ecosystem, Ad Technology, Media Agencies, Publishers, Startups

How real-time bidding works

By Eric Picard (First published on July 19, 2012 on iMediaConnection.com)

The real-time bidding ecosystem is still fairly new, and for many in our industry, there are a lot of misconceptions about how all the different parts of the ecosystem fit together. I’ve had a lot of requests from folks in the industry to explain how RTB works, and how the different players in our space fit together.

The biggest concept to get your head around with real-time bidding is the concept of programmatic buying and selling. The idea here is to streamline the buying and selling process by removing humans from the transaction. Now this is a very important thing to understand: By “the transaction,” I don’t mean that buyers and sellers no longer interact, or that there’s no role for sales in the equation. I simply mean that the act of booking the buy — let’s call it “order taking” — is completely automated. Ultimately this is a good thing for sales teams, as it lets them focus on building the relationship and selling the buyer on the value of their publisher brands. It lets the seller step away from the order-taking process.

Programmatic buying and selling is absolutely the future of this industry; it’s just a question of how long that transition will take. The lower cost of sales for publishers and more efficient buying for media agencies absolutely will make up for any hit to average CPM. And many (myself included) believe that we’ll actually see higher CPMs as a result of all this streamlining. Today most of the inventory that’s available is remnant, and it’s not the high-quality premium inventory currently handled by sales teams. Ultimately, all inventory will transact programmatically. But, like I said, sales will still play a very important role.

At the center of the RTB ecosystem are the ad exchanges. These platforms allow all the various players in the ecosystem to share supply and demand and create liquidity in the market. Examples of ad exchanges include Right Media, the DoubleClick exchange, AppNexus, and many others. On top of these pure-play ad exchanges are many ad networks and supply-side platforms that have essentially built ad exchanges on top of their existing products. The lines get very blurry between the “pure play” ad networks and the other aggregators of inventory that make that inventory available programmatically.

Similar to how stock or commodities exchanges allow inventory to be transacted upon at high volumes with maximum liquidity, the advertising exchanges play that central role. But it’s very important to understand that, just like in the financial services world, the big revenue opportunity is not with the exchange; it’s with brokers representing buyers or sellers. It’s these brokerages that represent the bulk of the value and that pull away the highest percentage of the transaction costs.

The equivalents of brokers in the RTB space are the ad networks, the supply-side platforms (SSPs), and the demand-side platforms (DSPs.) All of these ecosystem players have important roles and provide value. However, it should be noted that the lines are beginning to blur throughout the ecosystem. I predict that in the next few years, many DSPs will roll out SSP services, and many SSPs will become full-fledged ad exchanges. (But more on this in another article.)

So let’s follow the ecosystem participants from start to finish:

The impression starts with the consumer and runs through a web browser. (I didn’t put device in here, but note that even on mobile and tablets, there’s a browser involved.) The impression moves over to the publisher, through some SSP (or ad network) to the ad exchange, and then through to the DSP that is managed by an agency trading desk team on behalf of an advertiser.

There’s nothing very sophisticated about what I’ve drawn here — but note that this is the simplest way I could draw the RTB ecosystem. Here’s another view:

Note that even this is a simplified view, and that many of the various partners can service numerous blocks in the ecosystem. At the end of the day, the RTB ecosystem is made up of dozens of players (possibly hundreds), and they’re all scrambling to figure out their business models. This new ecosystem is definitely the future, but how all the pieces will ultimately fit together is still being determined.

The important thing to note in the RTB space is that from the moment consumers visit a web page, the entire transaction of selling and delivering the advertisements to them takes only a few hundred milliseconds. And this is where the revolution plays out; the competition over those impressions plays out in real time. The best ad for monetizing that user is theoretically shown, and the highest yield for the publisher is achieved. Thus, it should make the ad ecosystem function much better.

But there are many changes that have to take place, and I believe we’ll see it happen. First is that publishers need to push more and more of their premium inventory into the RTB environments. Publishers can make use of almost any ad exchange or SSP to create a private exchange where they can define advertiser-specific or agency-specific terms that are negotiated in advance, and the transaction simply makes use of the RTB infrastructure. Terms with specific advertisers can be reached in pre-decided negotiations, and the transaction takes place through the RTB infrastructure.

In a nuts-and-bolts summary article like this, I’ve glossed over a lot of the nuance and details, and I’m sure we’ll hear from a few parties about what I’ve missed or how I’ve not quite explained this correctly. But I welcome the dialogue. In the RTB space, I think there’s a lot of focus on the details, and not a lot of high-level framing going on — which alienates some of the industry folks who are looking to participate but haven’t dived in yet.

May 26 2012
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Ad Ecosystem, Publishers, Rich Media

Making the most of the New IAB Creative Formats

By Eric Picard (First published May 21st, 2012 on iMediaConnection.com)

The IAB has finally released new creative standards for the first time in a decade. The new rich media branding units (formerly called “rising stars”) are now officially the newest standards out there and should drive a new revolution in advertising online. Creative formats are the No. 1 reason that major brands have not adopted online advertising to the extent that spend matches hours spent. (There are several other major issues, but this one is the biggest.)

So where do these new rising stars fit in the overall continuum of online display advertising? And how fast can we expect them to be adopted? Let’s review.

There are two types of advertising experiences that are created on major publisher sites today.

One is an extremely brand-centric page-takeover type experience that is very custom and fundamentally overtakes the user experience on the homepage (or section front) of a major publisher to give a quality brand significant creative license. This is great for everyone, including the audience visiting the site. The experience is custom, crafted, and well considered. But this doesn’t scale as a business model, and many publishers don’t yield much profit from these implementations. They’re essentially loss leaders that bring in more spend on scalable inventory.

So what is “scalable inventory?” Well, judging from the 20 or so major publisher sites I just visited, it looks like that has consolidated around a combination of two standard IAB formats — the leaderboard (728×90) and the medium rectangle (300×250). There are, of course, a few other formats that are used at some degree of scale, particularly various formats of the skyscraper ads out there. But I’ve been seeing fewer of these on major publications, which seem to be consolidating on the 728×90 and 300×250 combination.

On one level, this makes me very happy — because I made very strong recommendations to adopt these two formats as the industry standard when they were released. In 2002. Yes, the UAP format standards were released to the industry way back in 2002. (Yes, that’s a decade ago.)

The problem with this lag is that while screen resolutions have radically increased in this timeframe, the formerly “large” 300×250 standard ad unit is now a postage-stamp sized unit.

The graphic above is one I created in 2009 to make the point that creative formats were too small. The problem has gotten worse with wide-screen monitors becoming the new standard.

Now that we have the first new formats available in a decade, it’s on the shoulders of media buyers and publishers to force this issue. First, media buyers must demand this inventory from publishers at scale. They should be pushing to get these units on every page of every publisher they buy from. These shouldn’t be a more-scaled version of the page takeover; they shouldn’t be special media buys that are a fixed percentage of a buy. They should be the bulk of every buy.

As for publishers, they need to enable (and quickly) every page on their sites to immediately adopt these units as their standard unit. The UAP is a decade old, far too small, and very prone to banner blindness by users. These new ad formats are well-thought-through and do a great job of catching user attention.

Publishers also need to make sure that these new units are not held aside as special options and used like rich media has been used for more than a decade now — as the way to preserve floor price. Yes, that’s a good thing for us to do; publishers should be preserving floor price wherever they can. But if we don’t aggressively move off of the long-in-the-tooth formats from 2002, we’re going to continue to see overall CPM erode.

Publishers must also make sure that these new units are made available for programmatic buying and selling. If we move to a world where hand-sold inventory is the rising star units, and all page views serviced by ad exchanges are UAP ads, publishers are going to cause a huge economic problem for themselves. I can imagine the argument being made that this helps with channel conflict resolution — but it won’t. It will create a new class of ridiculously cheap inventory that will further erode overall CPMs.

If media buyers demand that all their buys fit these new formats, and if publishers ensure that there is no friction in acquiring ads in these formats at scale, the whole industry will significantly benefit.

Mar 03 2012
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Ad Ecosystem, Ad Technology, Economics, Media Agencies, Publishers, Startups

3 ways that display advertising must change — or else

(Originally published in iMediaConnection, October 2011) by Eric Picard

Despite all the excitement in our industry about programmatic buying and selling of inventory (via ad exchanges, DSPs, SSPs, and a variety of direct-to-publisher vehicles like private exchanges and private marketplaces), the vast majority of dollars today are still spent the “old fashioned” way.

Since display ads began being sold in the mid-1990s, very little has changed in the way that the vast majority of ad dollars are spent. Most ad dollars are spent via a guaranteed media buy — either a sponsorship (the brand is placed on a specific location for all impressions served to it) or a volume guarantee (ad space of a specific volume is reserved against either a specific location on a page, or a specific group of pages, but will rotate out dynamically on a per-page view).

Sponsorships are great for buyers and sellers because they’re easy to manage. The buyer gets a fixed location, takes over every impression delivered to that ad location, and the seller doesn’t need to worry much about over- or under-delivery. (Sometimes they will sign up for a volume guarantee here, but many times they don’t.) And generally while sponsorships tend to yield low CPMs for the publisher, the ad buys are frequently for solid brands and the size of a sponsorship tends to be large on a dollar figure, if not large on CPM basis (e.g., it may be a multi-million dollar buy, but the CPM is probably low).

The oft-misunderstood publisher benefit of sponsorships, despite the low CPM, is that the cost of sales tends to be much lower. A sponsorship buy can be executed quickly and doesn’t require a lot of labor after the fact. I’ll discuss more about the issue of cost of sales when I touch on efficiency. But don’t underestimate the importance here.

Guaranteed volume-based buys are in many ways the cause of vast problems in our industry, despite being generally more lucrative and higher yielding on a CPM basis than sponsorships. First, they tend to be very sales and operations intensive, which means the cost of sales is often extremely high (frequently above 30-40 percent, and sometimes significantly higher for some of the most complex campaigns). There are several reasons why guaranteed volume-based buys are complex and costly.

First is that when inventory is sold in advance, there is some degree of prediction involved to determine how much inventory of any specific type or location will exist in the future. This inventory prediction problem is still one of the biggest issues we face as an industry. The ability to predict how many users will visit a specific section or page of a site is quite difficult on its own. Given the guaranteed nature of these buys, the prediction methods need to be extremely accurate, and getting accurate predictions is hard, even just based on seasonality and one or two locations. Once additional parameters, like various types of targeting, frequency capping, and various competitive exclusions are applied, the calculations are near impossible to calculate accurately.

This difficulty with predicting specific inventory in advance is the root of the second problem — optimizing buys on the publisher side during the life of the campaign. This rears its head in general, but much more so when the buy is targeted. Most buyers have no idea of the complexity of delivering these buys and how much work happens behind the scenes at most publishers to pull it off. Frequently there are daily (sometimes multiple daily) optimizations done behind the scenes to make sure a targeted campaign delivers against its goals. This can involve making changes to prioritization in the ad delivery systems, spreading the buy to larger pools of inventory, and bumping lower-paying campaigns out of the same inventory pool (at least temporarily) in order to ensure delivery.

Most publishers are not aware of the vast amount of labor done by ad agencies on their buys across publishers in order to ensure that advertiser goals are met. This can range from just ensuring that volumes that were agreed to are met, to ensuring that click or conversion rates driven by the buy are meeting a performance goal (for the direct-response advertisers). In either case, the amount of work done by agencies to optimize these buys, frequently across dozens of publishers, is huge.

Buying and selling inventory must get more efficient
This brings us to our first big problem that must be solved. Media buying and selling needs to get more efficient. If you compare efficiency (i.e., costs) of buying and selling traditional media versus online media, there’s a very clear difference. I’ve been told by numerous sources that the efficiency is between 10-15 times less efficient for big spenders for buying online versus offline media. And certainly there is a similar lack of efficiency for selling of online media.

One way that both buying and selling can become more efficient is through basic automation. Much of the back and forth of a media buy between buyer and seller is manual. There are not simple standard efficient means of automating the media buying process. There are numerous tools on the market that try to do this in the guaranteed space, but adoption has remained small so far. Between TRAFFIQ (full disclosure: I run product and engineering at TRAFFIQ), Centro, FatTail, isocket, Donovan Data Systems, DoubleClick, and others, there is plenty of choice to automate buying and selling of guaranteed between systems focused on the buy or the sell side of the problem.

And despite the promise of programmatic buying and selling removing much of the inefficiency from the space, most publishers are so worried about putting premium inventory into exchanges that we are still relegating exchanges to massive repositories of remnant inventory. Publishers must start using the private exchange and marketplace functionality that’s available to represent premium inventory.

This doesn’t mean that salespeople go away, and it doesn’t mean that publishers lose control of their inventory. It just means that much of the inefficient order-taking and campaign optimization that is done on both sides of the media buy can be removed from the system and automated. Sales become a more evangelical process, less work goes on behind the scenes, and salespeople stop spending so much time “order-taking.” Today publishers can set dynamic floor prices against exchange cleared inventory, buyers can automate their bids, and at the end of the day, the whole marketplace can get more efficient.

Publishers often say they don’t want this to happen because they fear a drop in the CPM of their guaranteed buys. The reality is that the cost of sales is so extreme on guaranteed media buys — especially targeted or frequency-capped ones — that publishers could easily skim 20-30 percent off their floor price if the cost of sales was significantly reduced.

One major reason that we’re having such trouble in the display industry is the predominance of performance or DR spend in our space. This overemphasis on DR for display has huge consequences to our space — from depressed CPMs to a focus on metrics and methodologies that require a lot of work. This leads us to our second major change that must take place.

Online display must become a brand friendly medium
Let’s face it. As a brand advertiser, you’re much better off putting your message on television or in magazines than on almost any digital vehicle. Our ads are too small to give the brand a proper emotionally reactive vehicle to reach audiences. Even the “brand friendly” 300×250 ad unit is tiny on today’s modern high-resolution screens. Luckily the IAB is responding to this problem with action, and there are many new larger standard ad sizes being promoted across the industry. But publishers have got to adopt them, and buyers have got to demand them as part of their RFPs. We should be moving much faster here — especially when you consider how many new tablet form-factor devices are moving into the hands of consumers.

But beyond the simple size of the ad, the design of most web pages leaves a lot to be desired from the perspective of a brand advertiser. There are too many ad units, not enough “white space,” too much noise on the page, and not enough back-and-forth value to the site’s own visitors or to the brands from the “advertising experience,” meaning the way ads are integrated with content. In a perfect world, the audience and the brand should be at the very least “neutral” in tension, and ideally the ads should be adding value to the viewing experience.

But there hasn’t been a huge outcry from the brands to fix this because they don’t see online as a medium that caters to them or is brand friendly. The flat CPM pricing is fine, but the lack of available GRP or TRP measurement in order to provide some cross-media evaluative metrics is a major roadblock.

Another reason that the biggest brands haven’t come online, beyond both the efficiency and brand friendliness issues, is that the ad units are shared with numerous less brand-centric advertisers, many of which run creatives that no brand advertiser would ever want running alongside their own creatives. This massive over focus we have on direct response or performance advertisers has somewhat tainted online display, and the willingness of publishers to liquidate every single available impression at fire-sale prices has led to overall much lower CPMs than media that have focused on brands as their primary customers. This issue leads to our third and final major change that must happen in online display.

Online display must increase overall CPMs of inventory
If we can transform display into a high-quality space for brand advertising, we should be able to demand higher CPMs. This sounds nice and wonderful to most publishers, but many of the people reading this article will somewhat cynically push back at this point and talk about the “reality” we face in online display today.

So let me dispel a few myths by explaining the economics of our space in terms many of you have probably never heard.

Every emerging media that I have researched or lived through has focused initially on DR advertisers as their primary target in the very beginning. There is an economic theory that drives this: budget elasticity. The idea is that a DR advertiser is theoretically managing spend based on pure ROI. That is, they only buy ads that drive profitable sales of product or services (i.e., the budget is “elastic”). This, in theory, means they will spend as much as they can as long as the media buy creates more revenue than ad spend. And because the media experience is new in an emerging media, and the advertising is novel, response rates to those new ads in new media types tend to start out much higher, and then they will eventually plateau.

The problem with this theory is that it only works out well for publishers catering to DR buyers when the conversion rate on their inventory is high enough to drive high CPMs. The type of inventory that drives high conversion rates is typically extremely well-targeted inventory, typified in our space by paid search advertising, where the users tend to be searching for the very thing that the advertiser is selling. There are some forms of display advertising that also drive high conversion rates. They are frequently driven by retargeting of search queries, very lucrative behavioral segments that show a user’s propensity to buy is higher than average, or similar principles.

Like all other emerging media, when display advertising first started out, the focus was on getting DR advertisers in the door. And like all other emerging media, the response rates on ads were relatively high in the early days. But unlike all emerging media before online display, we wrote software that managed media buys online right at the beginning of this industry. And all of the DR “knobs and dials” were locked down in code, which made it much harder to evolve out of DR into brand advertising. If response rates had grown or remained high, this wouldn’t have mattered. But like most “top of purchase funnel” ad experiences, the response rates are too low to justify high CPMs by the DR advertisers.

When a media type does not drive a very high conversion rate, DR advertisers are only willing to spend a very low CPM. There’s a magic point at which the price of the inventory is low enough that the DR formula for positive ROI starts to make sense even for low performing inventory. This inventory is generally cheaper than 50 cents and frequently cheaper than 5 cents. And there’s a ton of it available in our space. This overemphasis on DR has numerous unintended or unrealized consequences.

Many large publishers sell their guaranteed inventory at well above $3 on average, and many publishers average between $5 and $9 for what is sold by hand. But this typically represents well under half of their inventory, and for many publishers it’s more like 30-40 percent of their total inventory. Once you dip below the conversion threshold of a DR buyer on most ad inventory, you’re driving very hard toward the basement on your prices. And if more than half of your inventory is sold off for less than 20 percent of your total revenue, then something is very wrong with the way we’re managing our space.

Publishers would be much better off stripping half the ads off of their site, redesigning the site to accommodate larger brand-friendly ad units, selling a lot more sponsorships with their human sales force, and selling the remainder of those ads mostly through a very automated sales channel, such as a private exchange, or at the very least automating their sales with one of the available tools.

Even selling10-20 percent more ad inventory through premium channels would significantly increase yield for most publishers than all of the remnant sales that take place today. Simply repurposing the sales and operations teams away from the remnant inventory problem and focusing them on selling premium could solve this.

To conclude, if we can make buying and selling inventory across the online display space more efficient, more brand friendly, and significantly increase our CPMs, then we’re going to have a rapidly growing and expanding space — one that would rival venerable offline media like print and television in size and scale. And that would become the perfect vehicle for those media to travel through as they become “tablet-ized” and “streamed.” But with such a huge overemphasis on DR, massive inefficiencies in buying, and low CPMs, we have a ways to go.

Mar 03 2012
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Ad Technology, Media Agencies

3 ways to increase ad engagement, conversions, and ROI

(Originally published in iMediaConnection, June 2011

We’ve been at this online advertising thing for about 15 years now — give or take a few years. And we’ve seen time and again all sorts of tricks, tools, approaches, and technologies that can be used to increase ROI from the advertiser’s perspective and yield from a publisher’s perspective. I’ve written tons of articles saying what we should do as an industry to improve advertising from a policy, approach, and technology perspective. But today, I have a nice little article about how to improve your results as an advertiser.

In 1997, I started one of the first rich media advertising companies. Many of the ads we built — back in the days of 56K modems, before broadband, and when creative file size limits were tiny — would win awards today and still be recognized as groundbreaking. As an industry, we’ve gone backward, not forward.

Disrupt your own creative approach
My overall recommendation is to “productize” your advertising. You can do this by creating standardized ad units with preconfigured types of interactivity and with one defining trait from a creative perspective that immediately connects with the user. This last element is important — and is the trickiest to pull off — but once you nail it for one set of campaigns, you’ll be done with that work.

Example: For an advertiser selling cleaning products, surround the border of each ad with a froth that animates little popping bubbles.

Whatever that unifying theme is, break it down into the simplest graphical treatment that doesn’t overwhelm the rest of the ad, but that is both noticeable and engaging. Work with your rich media vendors to find out what is possible across the publishers you want to work with — and make it real.

Since our display advertising space is small, and the units make up a tiny non-disruptive portion of the screen, you need to force the issue about space. That might mean you need to create very compelling creative that somehow creates interaction between multiple units on the page, breaks outside the boundary of the border of the creative unit, or just uses simple and arresting copy or images to capture the user’s attention.

I realize this is a bit of Advertising 101. But we spend too much time in this industry running ads that don’t differentiate from each other, don’t capture the user’s attention, and are just plain old boring ads in standard IAB-sized units.

Every rich media vendor out there offers a variety of simple solutions to the ad mechanism, whether the mechanism is a 300×250 banner that breaks outside the boundaries of the creative, or whether it enables an over-the-page experience in which the ad expands and is not rectangular.

Create multiple engagement opportunities within the ad
Even within standard ad units that run on a significant number of sites, many opportunities for engagement exist. Whether we are talking about a 300×250 ad unit, a 300×600 half-page unit, a 728×90 leaderboard, or 160×600 wide skyscraper, all of these formats are large enough to create deeper opportunities to create content — not just an ad.

Ads that just offer a click-through to a landing page are very straightforward and miss out on massive opportunities. My recommendation is to always offer at least two — if not three — specific and clear opportunities for engagement with the user. One should be the primary execution; the others should be highlighted but not overwhelm the primary.

Example: For a cleaning product, the primary creative should be an engaging brand message with eye-catching graphics and a simple story. The second opportunity should be more direct-response driven (e.g., print out a coupon or request a free sample by mail). If a third opportunity makes sense, it should pull in a different direction (e.g., sign up for a cleaning tips newsletter or go to a store locator for places to buy the product).

In any case, this should always happen right within the ad itself, not requiring the user to jump to another website. Conversions within an ad unit tend to be much higher than those that require leaving the site that the user is on — and the larger ad units certainly have enough room to put some simple forms in front of the user and capture data. Every rich media advertising vendor out there has ways to do this for you; just work with your vendor to see what’s possible.

Tie online ads to the physical world (ideally locally)
Every ad should be a combination of engagement opportunities — driving brand engagement and brand metrics, but also offering quick-twitch direct-response opportunities.

Users are not going to buy a car or a washing machine from an ad. But they might well be willing to sign up for a test drive or visit a store for a scheduled demonstration of a large-ticket product. Working with opportunities that are localized is very smart, if at all possible. Frequently the possibilities exist, but they are outside the normal consideration set for an online component of an overall advertising campaign. So don’t use normal considerations — break outside the boundaries of the norm and drive change.

Examples: If you are advertising a product that is sold by dealers (cars, agents, etc.), retailers, or resellers, create engagement packages with them to drive customers into their stores. In some cases they might be willing to share some of the expenses for successful engagements, or at the least could be willing to participate in a broader proposal. These could be as simple as setting up a special event at their location that ties to the lifetime of the campaign, such as having food grilled at a car dealership on a specific weekend, or offering to give product demonstrations one evening a week.

Getting your online creative to pop outside the box of the ad unit, to drive deeper engagement with the customer, to offer some kind of outcome driver as part of every unit, and to tie to offline (physical world) engagements in the local community will completely change the game and drive much greater ROI for the advertiser.

Mar 03 2012
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Ad Technology, Media Agencies, Publishers

DSPs: What they really are and why you should care

(Originally published in iMediaConnection, May 2010) by Eric Picard

Recently on the Internet Oldtimers List, someone posted a link to a video mashup where someone had taken a clip from the movie “A Few Good Men” and replaced the famous “You can’t handle the truth!” dialogue between Nicholson and Cruise with a farcical semi-humorous debate about demand-side platforms (DSPs). What was interesting about this clip was that its central argument was that DSPs lower the CPM of premium publishers’ impressions (with Cruise arguing for the premium publisher and Nicholson arguing for the DSP).

The video is cute — pretty well done, and worth a view if you’re someone on the inside of this particular space online. But what really surprised me about it was that very few people seem to really understand what’s happening with DSPs in general — and there’s obviously misinformation going around. This particular debate about DSPs lowering the yield of publisher impressions was one I hadn’t heard articulated before.

So let’s get started digging into this by discussing what a demand-side platform really is. These advertiser/agency facing systems let buyers do self-service media buying from publishers; publisher aggregators (sometimes now being called sell-side platforms, or SSPs) like PubMatic, AdMeld, Rubicon, and others; and ad exchanges. The most important part of these mechanisms is that they enable real-time bidding against inventory on these sites. This is really important because in real-time bidding, the DSP can let the buyer specify business rules describing the value of impressions based on their audience attributes. That means the buyer can assign monetary value against specific audiences, and the DSP can bid on every impression in real time based on its actual value to the advertiser.

One reason real-time bidding is so valuable is that advertisers can bring multiple data sources to bear on the valuation problem. This would include the targeting attributes that the publisher lists about its own impressions, data attributes from third-party data providers like BlueKai and others, and most importantly, proprietary data that the advertiser owns about its own set of customers. Based on all these different targeting attributes, the buyer can assign various business rules that align the campaign goals against potential impressions, and the bids can be set against all the various providers of inventory.

The DSP then will begin bidding across the sell-side platforms, exchanges, and any publishers that directly support real-time bidding, and will automatically optimize the bids based on success and results. The result can be as simple as reaching 100,000 people that fit some specific criteria — or it could optimize across CPC or CPA. Real-time bidding is vastly superior to other mechanisms when it comes to ensuring that the advertiser gets the best ROI. But there are some issues.

I’ve heard from many of the DSPs that they are running out of real-time biddable inventory, meaning that their CPMs are rising because their supply is constrained. This might sound funny to those who fondly quote that there is unlimited supply of display inventory — but consider that there are short- and long-term factors driving this imbalance. In the short term, the sources for this type of inventory are still somewhat limited; even with the explosive growth we’re seeing in this category, there are not enough impressions available to satisfy demand. DSPs can still participate in non-real-time auctions in order to supplement impressions, but they lose the extra value they bring to the table when they can examine the impression before bidding.

Long term, there will be lots of impressions being made available. (In fact, I predict that most impressions will ultimately be made available in real-time.) But this real-time bidding world is all based on audience targeting — and the same users that Whole Foods wants to reach are also highly valuable to Best Buy and The Home Depot. This means that those impressions driven by highly desirable audiences will be a small percentage of the total number. But note: Although from a percentage perspective we’re talking small numbers, from a volume perspective that could still represent massive amounts of high bid-density inventory. Paid search impressions are a tiny fraction of display impressions today, yet drive half the revenue in online advertising. This could change significantly if we can drive enough bid density on a small fraction of display inventory that represents valuable audiences.

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I have heard some premium publisher folks state concerns that there could be issues with real-time bidding on display inventory due to asymmetric bidding and low bid density. Consider the following example that illustrates how low bid density (leading to asymmetric bids) could be a problem in the future as more impressions become available for real-time bidding. I’ll make it unrealistically simple to illustrate the issue:

An impression shows up for bid. It has the following attributes:

  1. Male
  2. 34 years old
  3. Greater than $150,000 income
  4. Chicago DMA
  5. New parent
  6. Auto shopper
  7. Jewelry shopper
  8. Health club member
  9. Impression is 300×250 pixels
  10. Site category is entertainment

Four advertisers participate in the auction:

Advertiser 1: Pampers — knows nothing extra

Advertiser 2: Ford — knows user owns a BMW and has been shopping for Land Rovers through proprietary data deals

Advertiser 3: Zales — has existing customer data that shows this is an inactive customer, a high spender in past who bought an engagement ring three years ago

Advertiser 4: An independent Chicago diaper service — knows nothing extra

The bidding follows like this:

Pampers bids $1 CPM.

Ford bids $5 CPM — it knows it has a low likelihood of converting this profile, so it doesn’t bid very high.

Zales bids $40 CPM — it knows that this customer bought his engagement ring at Zales three years ago, and given the new parent status, he is likely to be open to buying an expensive Mother’s Day present.

The Chicago diaper service bids $10 CPM based on simple CPA optimization.

Because this is a second price auction, Zales will win, but only pay $10 CPM for the impression. In this simple example, that might not seem too bad. But in reality, it should be possible for the publisher to predict that this impression, based on past bids on similar impressions, would sell for much higher than $5 CPM. So the publisher has not gotten the maximum yield it could have gotten based on the auction it had in play.

In the future, I predict that publishers will make use of yield optimization technology to fix this problem. The publisher should be setting a floor price on a per-impression basis based on its prediction of value to the advertisers in the marketplace. The publisher probably could have comfortably set a floor price that would have given it a higher yield (e.g., set the price at $12 or even $20 CPM based on historical trends for this type of impression and the current bidders in the auction). But this is a very hard technology problem to solve.

In paid search, we’ve seen high bid density drive very high CPMs on highly desirable keywords within the auction. And where the bid density is lower, we’ve frequently seen lower CPMs. Essentially, bid density refers to how many participants within an auction are bidding over the same item. In paid search, overall this hasn’t been a problem — mostly because there are “single digit” millions of commercially viable keywords, and about half a million advertisers competing over them. This leads to pretty good distribution, with some keywords getting lots of competition, and some getting very little — and overall the average yield being very high for the search engine. It’s a supply and demand problem for the most part.

But in online display advertising, there are trillions of display impressions a month with fewer than 10,000 advertisers (at least, in the world we live in today), with most dollars being spent in the U.S. coming from fewer than 3,000 advertisers. Further, the role of agencies could significantly change under this new set of mechanisms. There’s no reason that an agency using a DSP couldn’t withhold bids from its stable of advertisers so that only the top bid available for any advertiser for each impression would be placed. From a bid density perspective, this could be damaging without the kind of yield optimization I mentioned above and the creation of competition between multiple advertisers that normally wouldn’t have competed in the past. But there are still things that could drive lower bid density and lower publisher yield.

For instance: In an extreme world, each agency holding company could have its own DSP, and each of these would offer only one bid per impression as it reviewed the available targeting parameters and determined — based on each advertiser’s business rules — which of their campaigns would have the highest bid. In other words, each DSP could run an internal auction prior to placing a bid in the publisher-facing system. That would reduce the density of the auction on the publisher side significantly, causing the publisher to reduce yield. But it does require significant process change from how things are done today.

In the end, I think publishers would be foolish to worry too much here. It’s likely that their highest value impressions are going to go way up in yield, even if they see a drop on the rest of their impressions. And at the least, those two things should make up for each other. At the best, this could drive average yield higher in online display than we’ve ever seen before.

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