Category Archives: Online Media

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 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 22 2012
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Ad Ecosystem, Economics, Online Media, Predictions, Publishers

Why Media Companies Are Being Eaten By Tech Companies

By Eric Picard (Originally published on AdExchanger.com, August 20, 2012)

My friend and colleague Todd Herman (LinkedIn) once wrote a strategy paper about video content when we worked together at Microsoft. Called “Don’t be food,” it was a brilliant paper that laid out a strategy for effectively competing in a world where content is distributed everywhere by anyone.  I love the concept of “Don’t be food.”  It applies to so many existing business models, but clearly where Todd initiated it – Media – it applies incredibly well.

The media business is being forceably evolved through massive disruptions in content distribution. In the past, control over distribution was the primary driver of the media model. Printed material, radio and television content required a complex distribution model. Printing presses and distribution are expensive. Radio and television spectrum is limited, and cable infrastructure is expensive. Most media theory and practices have been deeply influenced by these long term distribution issues, to the point that the media industry is quite rigid in its thinking and cannot easily move forward.

One of my favorite business case studies is the Railroads.  Railroad companies missed massive opportunities as new technologies such as the automobile and airplanes began to be adopted. They saw themselves as being in the “railroad business,” and not the “transportation business.”  Because of this they lost significant opportunities and very few of the powerhouse companies from the rail era continue to exist.

In media, new technologies have been massively disrupting the space for more than a decade. And there is an ongoing debate about technology companies stepping in and disrupting the media companies. Google is a prominent example, and its recent acquisition of Frommer’s is yet another case where it has eaten a content company and continued to expand from pure technology into media.  But Google isn’t moving into media based on the existing rules that the media companies play by – it is approaching media through the lens of technology.

But this issue doesn’t only pertain to the oft-vilified Google: Amazon continues to disrupt the book industry by changing the distribution model through the use of technology, and is clearly gunning for magazine, radio and video content as well.  Microsoft is changing the engagement model and subsequently the distribution of content to the living room via its ever-expanding Xbox footprint, and is broadly expanding toward media with Windows 8, its new Surface tablet devices and smartphones – again using technology.  Apple has turned distribution models on their ears by creating a curated walled garden of myriad distribution vehicles (apps on devices), but charges a toll to the distributors – again using technology to disrupt the media space.  Facebook, Twitter and social media are now beginning to disrupt discovery and distribution in their own ways – barely understood, but again based on technology.

Existing media models are functionally broken – and will continue to be disrupted.  Distribution is always a key facet of the overall media landscape, and will continue to be.  But as distribution channels fragment, and become more open, the role that distribution plays will radically change. Distribution is no longer the key to media – it is inherently important to the overall model of media – but it isn’t the key.

Technology is the key to the future of media. Technology can and has profoundly changed the way content is distributed, and will continue to do so. The future of media is wrapped up in technology, and this is an indicator of why technology companies are eating media companies’ lunches, if not actually consuming them in their entirety.

Media companies don’t understand technology because they are not run by technologists. And there is a vast gulf between the executive leadership of media companies and the needs to understand technology. Every media company should be running significant education efforts to pass along the concepts needed to compete in the technology space, but I’m not convinced even that would be enough to fix the problems they face.

At Microsoft I once had an executive explain to me why most of the executives running businesses at the company were from a software background.  He said something along the lines of, “A super smart engineer who can wrap his or her head around platforms and technology issues can probably learn business concepts and issues faster than a super smart business person can learn technology.”  And he was right – it’s that simple.

Business schools should have requirements today for anyone graduating with an undergraduate or graduate degree to learn how to write software, and most importantly to develop a modern understanding of platforms. These platform models are the future of distribution, and are barely understood even among many technologists. The modern platform models used broadly on the Internet and to create software on devices that drive content distribution are relatively new, and are frequently not understood by people with technical backgrounds who haven’t spent time working with them.

Bad business decisions continue to be made by media companies because of the significant lack of technology leadership in both executive and middle management. As technology evolved, the model for many years was that business people figured out “Why and What” to build and “Where” to distribute it, and engineers figured out “How and When” something could be delivered.  Great technology companies break down the walls between Why, What, How, When and Where. Engineers have just as much say in all of those things as the business people. Great technology companies don’t treat engineers and technologists like “back room nerds.”  They recognize that engineering brilliance can be applied to the business problems facing them, and that technology innovation will drive their businesses to disrupt themselves toward future success.

Media companies must evolve away from their historical strengths based on distribution control, and must embrace technology as a key principal.  And they need great engineers to do so. The problem is, great engineers won’t work for mediocre engineers. Great engineers won’t take bad direction from people they don’t respect, especially business people. And many media companies have treated their existing engineering organizations as an extension of traditional IT models. The groups that are responsible for the corporate network, intranet, conference room systems, email servers and laptop support do an important job. But it’s vastly different from building software and inventing new technologies.  Media companies often have not understood this.

For a traditional media company to compete effectively with Google, Amazon, Apple, Microsoft, Facebook, and the thousands of hot startups now competing with them, they must build world-class engineering organizations. This isn’t a light fuzzy requirement, it’s a core fundamental of their ability to survive for the next century.  These companies must evolve forward.  They must find ways to empower internal disruption.

Media companies must build startup organizations within their own internal structures that are isolated from the existing IT leadership and given bold broad empowered charters with the leeway to disrupt other teams’ businesses.  They must build a new technology driven culture within these large media companies that is separate from the existing groups, and then embrace those internal startups as the future of the company.  This isn’t easy.  It’s nearly impossible.  And this very likely will not work the first time it’s tried. But if media companies don’t commit to this kind of change, they are going to be eaten.

Aug 14 2012
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Economics, Media Agencies, Online Media, Publishers

How publishers sell ad inventory

By Eric Picard (Originally published on iMediaConnection, August 09, 2012)

Ad inventory is typically broken down into four buckets: sponsorships, premium guaranteed, audience targeted, and remnant. Each of these buckets can be sold through a variety of sales channels.

Revenue distribution across this “layer-cake” inventory model flows downward — with the vast majority of inventory coming from premium and a significantly lower amount of revenue coming from the remainder:

The process of an advertising sale begins with the media buyer, who sends a request for proposal (RFP) document to numerous publishers. These RFPs typically are written in prose and define the overall goals of the advertiser in question, and of the specific campaign being executed. A typical RFP has between 50 and 100 elements that are laid before the publisher as acceptable or desirable outcomes, and these elements (attributes or attributes of the buy) are generally descriptors of the audience, of the media the advertiser is looking to run on, of the acceptable (and unacceptable) content to be associated with, etc.

Advertising inventory is the base unit sold by a publisher to an advertiser. It is measured in “impressions,” which are defined as an opportunity to show an advertisement to a person. Impressions at their most basic are blank vessels made up of opportunity. Inventory is generally defined in advance by the seller based on a variety of factors, and it is these predefined impressions that are contractually agreed up on between buyer and seller.

Nearly all impressions sold are made up initially of one or two media attributes based on content association (e.g., MSN>Entertainment or MSN>Entertainment>Celebrities; Yahoo>Autos, or Yahoo>Autos>News). Or they’re sold just based on category — in some cases blind, meaning without the knowledge of which publisher the impression ran on. Further refinement of the inventory is based on other attributes such as above the fold, rich media units, or a variety of quality scores. Additional media attributes included in the definition of a piece of sold inventory include various types of targeting and other types of intelligence and filtering such as inventory quality scores and contextual targeting.

Beyond media attributes, there are numerous audience-based targeting attributes available for the buyer to request, or for the seller to offer. These include such attributes as geographic, demographic, psychographic, behavioral, etc.

It is the combination of these various attributes that define the inventory that is sold. Inventory is sold in a number of ways, including on a guaranteed basis (a buyer contracts with a seller for a fixed volume of inventory between specific dates) and on a non-guaranteed basis (if inventory is available that matches, it will be sold, but the seller doesn’t make any guarantees on volume).

In order to predict how much inventory will be available, publisher ad platforms need to look at historical data with seasonality and apply some very sophisticated algorithms to make a guess as to how much inventory will be available during specific date ranges. These “avails,” as they are called, become the basis for how all guaranteed ad sales are done.

But ad inventory has many very complex and difficult-to-predict issues that are endemic to the problem — the problem of predicting how many impressions will exist in a specific month is sort of like imagining how many cars will cross the Golden Gate Bridge in a given week. Predicting this based on historical data isn’t too hard. And predicting the color of the various cars that might cross the bridge is probably feasible with some degree of accuracy. Maybe even predicting the general destinations of the cars crossing the bridge is possible. But trying to predict how many red Toyotas driven by women with an infant in the car who have red hair and who make more than $125,000 annually is probably not a solvable problem.

This is akin to the requests given on a daily basis regarding ad targeting. This type of prediction is extremely technically challenging; nobody has been able to accurately predict how much ad inventory will be available in advance for more than three to four targeting attributes in advance. Therefore, publishers rarely will sell inventory that contains more than three to four attributes because this causes an immense amount of work during the live ad campaign for the publisher’s ad operations team. (They must monitor ad delivery carefully and adjust numerous settings in order to ensure delivery of the campaign.)

Inventory is sold within a contract called an insertion order (I/O), and each sold element is typically called a “line item” on the I/O. Line items correspond to a variety of attributes within the publisher’s inventory management systems. A simple example would be MSN>Entertainment. But a more complex example would be MSN>Entertainment>Women>18-34.

Beyond a typical guaranteed media buy, there are several other mechanisms for selling ads. Some ads are re-sold by a third party such as an ad network (examples include Collective Media, ValueClick, Advertising.com, etc.). Some ads are sold through an automated channel such as a supply-side platform, or SSP (examples include Rubicon, Admeld, PubMatic, etc.). There are also ad exchanges that can sit in the middle of all the transactions, and as the industry has matured, the difference between an exchange and an SSP has become less clear. These exchanges and SSPs then create a marketplace that allows ad networks and various demand-side platforms (DSPs) to compete for the inventory in real time. We’ll refer to this as real-time bidding (RTB) even though in some cases this term doesn’t apply exactly.

The management systems for buying RTB inventory are generally called demand-side platforms (DSPs). In RTB media buys, it is extremely rare to have more than three to four targeting attributes (just like in guaranteed media buys), not because of prediction but because inventory that exists for each campaign or line item that contains more than three to four attributes delivers with extremely low volume. In fact, the amount of inventory available on a per-impression basis as you layer on more targeting attributes generally drops significantly with each new attribute.  This means that a typical line item for an RTB campaign would look very much like the one for a guaranteed buy: Entertainment>Women>18-34.

For a DSP to spend an entire media buy at more than four targeting attributes, the buyer would have to manually create hundreds or thousands of ad campaigns that each would then be manually optimized and managed. It isn’t actually feasible to do this at scale manually.

In summary
In a perfect world, advertisers would be able to find all available ad inventory that matches their goals, with as many attributes as exist on all impressions. The problem is that existing inventory management and ad serving systems are not designed to deal well with more than two to three concurrent targeting attributes, whether for guaranteed media buys or RTB.

So why do advertisers and publishers prefer to sell ads on a guaranteed basis?

Inventory guarantees serve several purposes. The most critical is predictability; media buyers have agreed with the advertiser on a set advertising budget to be spent on a monthly basis throughout the year. They are contractually obligated to spend that budget, and it is one of their primary key performance indicators. Publishers like to have revenue predictability as well, which is solved by selling a guarantee on volumes for a fixed budget.

For all the innovation in the ad-tech space over the last decade, it’s fairly impressive that very few of the core problems of a publisher have been solved. At the end of the day, 60-80 percent of the revenue that publishers bring in comes from their premium inventory, sold on a guaranteed basis — which represents generally less than half of all their available inventory. Nearly all the ad technology innovation in the last decade has focused on what to do with that other half in order to raise the median price of that revenue from nearly zero to a bit more than zero.

It seems to me that there is an opportunity to focus on something else. (And you might imagine that I’m doing just that.)

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