Category Archives: Economics

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.

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.

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.

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, with mediocre engineering talent endemic in their organizations – frequently top to bottom.

Let me say again; great engineers will not work for mediocre engineers.  This means that the existing CTO and entire engineering infrastructure within a media company will not solve this problem. Before moving forward, executive leadership has to recognize that it is likely that their existing technology organization will fight, block and actively try to sabotage any efforts created outside of their own infrastructure. But it is very clear that without a significant change here, these companies are doomed.

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.

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.)

Why the display ecosystem might implode

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

I sat on a panel at OMMA display on Monday, and the discussion was designed to determine if ad exchanges were going to be relegated to the land of direct response advertising, or if they would foster brand-friendly environments.

I’ve written a lot over the past few years about the future of display, and the issues we face and need to overcome. But this panel brought up many key issues that I thought I’d take a quick look at in this article.

Creative formats for display are really awful
If we don’t solve this, we might just need to give it up. Display ads are just too small to really give an effective brand experience. Even the “brand-friendly” banner units like the venerable 300×250 are too small. Are we really saying that pre-roll is the best we can do?

I suggest we think through the issue of brand-friendly space, and fix websites to accommodate it. We should strip all the banners off every page of a major publisher, and replace with a brand-friendly unit that gives the advertiser a great venue to show brand content and is still user friendly. It’s not so hard — there are all sorts of vehicles to use here.

“Sliding ad units” that move the content down for a moment on page load, then retract to reveal a “leave behind” unit that can be explored by the consumer (and re-expand the ad) if they’re interested are my personal favorite. I like this better than over-the-page ads that cover the content in general. But even expanding ads (my last startup, Bluestreak, pioneered expanding ads back in 1997, so I’ve thought about this a lot) work well for this kind of thing as long as they don’t expand on mouse-overs. They should expand for one to three seconds on page load, and only re-expand on clicks. If they very quickly expand on page-load, retract to show that they’re “there” and interactive, and the entire expansion and retraction takes less than three to five seconds, consumers won’t backlash too badly.

Targeted reach is critical to brand advertisers
Brand advertisers will pay to reach audiences that they define. They don’t need to have a conversion tracked, nor do they need to track CPA during the life of the campaign. They don’t need to track clicks — except you’ve fought so hard to convince them of this, that they finally have shrugged their shoulders and said, “Fine, show me the clicks.” Too many people in our industry are drinking their own Kool-Aid.

Why do I still have people argue with me that GRPs and TRPs are not what we should use? They’re good enough metrics for massive amounts of ad spend — tens of billions of dollars, in fact. And we have the arrogance in this industry to simply refuse to adopt and promote something that people with money have been requesting for more than 15 years. Really? The customer isn’t right? You know better? They have money to spend.

I get worked up on this topic — it’s ridiculously stupid that we won’t sell a product that customers with big budgets would like to buy from us. And the argument I continue to hear come out of the mouth of smart people? “We can do better.” This is a fool’s errand. When people say, “I’m thirsty, and I’d like to buy a nice bottle of seltzer water from you”, the response isn’t, “No, that’s not what you want. We sell the water and bubbles separately. It’s much, much more effective that way — I have data to prove it.” And they keep saying, “But I just want a nice bottle of seltzer water.” And we keep telling them to pound sand.

More than this — we keep building incredibly complex tools to manage buying and selling in our space. That makes it very hard and inefficient for brand media buyers to adopt online display since they can get massive reach at a reasonable price from traditional media — but not so much from online.

So I have an idea: Let’s sell the customers something they want — gross and targeted reach and frequency (GRPs and TRPs) that mesh well into the combined cross-media plans that they do, and let’s give them tools that don’t require them to get an advanced math degree to use.

And still I’m going to have comments on this article that “we can do better than GRP and TRP.” Fantastic — you go do that. But why not give them GRP and TRP too? Does it hurt to give them what they’re asking for? Calculating GRP and TRP isn’t that hard.

Build tools that are ideal for brands to use and that make it really easy to buy online display advertising in ways that make sense in the context of all the other money they spend. Give consumers better ad formats that actually are great venues to showcase brand ads with emotional impact. It’s not hard technically. It just requires some group consensus. And I fear that we’re not going to pull it off — despite its relative simplicity.

On the OMMA panel I was on, three of five panelists said that they felt that there was a real chance that the economics of display advertising could implode over the next few years. I was on the dissenting side of this panel. Let’s not make me a liar, shall we?

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.

Why the ad industry is ripe for consolidation

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

The other day I was talking to a good friend of mine who is on the executive team at a startup in the ad technology space. We were talking about strategy — and in the midst of the conversation, I suggested that since the company hadn’t taken any money yet, it should strongly consider selling at its early “life stage” for $10-20 million now. He gasped and told me, “Are you kidding me? I’d put our valuation at between $100-200 million.”

I stopped talking for a minute, and then said, “I’m not sure how you could possibly have the revenue to justify that.” This is, after all, an early stage startup that only has been in business for a year or two, and I’m fairly familiar with the company and its customers; I know it’s not doing more than $2-3 million of annual revenue right now.

And he said, “In (insert niche here) nobody is bought on a multiple of revenue — it’s always based on strategic value.”

To which I replied, “That might be true of funding — of course VCs and increasingly PE firms are betting on the long-term value of disruptive technologies. But for an acquisition, at least for a rational one, nobody is bought without some discussion of ‘comps’ for similar companies and revenue, and some ‘reasonable’ multiple is definitely a factor.”

My friend rattled off several examples of companies that have been acquired (for what I see as irrational amounts of money) lately and some of his beliefs on their revenue pictures — and we picked over the specifics of the acquisitions. And that’s when I started to get worried.

This conversation has been rattling around in my head for days now, and I have to say I’m concerned about the market. I see this space as primed for consolidation. The Luma Partners display ecosystem slide is a perfect example of much that is wrong in our space:

As dollars move between advertisers and publishers, the folks sitting in the middle are trying to find a way to strip off some money as it passes through the ecosystem. The only way they’re going to be able to strip some pennies off of the dollars as they flow through is if they provide some value back to the ecosystem. The problem is both the number of companies in this space and the exuberance of those companies for how they believe they’ll participate. Many are not realistic on what they should be paid.

There’s opportunity in this space; don’t get me wrong. I wouldn’t be invested so heavily in online advertising if I didn’t believe that there is a strong opportunity for me and my company. But let’s all be very clear about what that opportunity really looks like. The greater the provided value, the more money that the company in the middle can take away. So is the value a moderate improvement in efficiency — or a substantial change in value? How significant is the change? At the end of the day, the market will bear only so much being stripped away, so only those companies that have disruptive technologies are going to be able to extract significant amounts of money.

It might be useful to look at what percentage of spend various vendors are able to extract today. Let’s start with agencies, which are often the target of technology companies trying to find a place to disrupt the market through disintermediation. But that’s crap. First of all, the agency lives in thepower position in the ecosystem. And despite the kvetching of the technically minded who don’t “get” what agencies do (nor even the difference between a creative and media agency), agencies provide a lot of value to the advertiser (their customers). Agencies are not easily disintermediated — nobody has been able to disintermediate them so far.

Most startups vastly inflate the amount agencies get paid — typically the number that is thrown out is somewhere between 15 and 20 percent of spend, which would be freakin’ awesome if it were true. But those kinds of percentages went out of style in the ad space along with well-tailored suits, smoking a lot of cigarettes, and drinking whiskey and water like it’s going out of style. Most big agencies no longer negotiate their contracts with the marketing team as an advertiser; they negotiate with procurement offices and negotiate for fixed margins — very low margins, in many cases. They’d be psyched to claim 15 percent of spend. They’d be excited about 10 percent of spend — even 5 percent, in some cases, would be cause for ecstatic celebration.

OK, so agencies are not where the money pools. What about tech startups? The reality is that technology vendors take small percentages of the dollars out of the flow and make it up on margin and volume.

Ad serving is a great example of this. A third-party (buy side) ad server is typically getting between $0.07 and $0.15 CPM for its service. That is really not a huge amount of money. It typically comes in at less than 5 percent of spend — and at volume, and depending on price, it frequently is down below 1 percent.

In traditional media, typical vendors are well below 1 percent of spend as the money travels through their systems. But ad serving is commoditized, you might say (and I’d argue that before too long, most technologies are commoditized). Look at DSPs, which have been the much-laureled darlings of advertising technology for the last three years. There’s very little differentiation here. They’ve all commoditized out to varying degrees, competing only on price or service, or minor feature differences, rather than by disrupting each other. (And for the record, there’s nothing wrong with this — which is sort of my entire point.)

“But the DSPs are the future,” you might say. “They’re the ones who are bringing automation and efficiency to this space; they’re the future of advertising! Damn it!”

Well — yes and no. DSPs are playing in an emerging media — the real-time inventory market. In emerging media, the top-line media spend CPMs are generally higher. (Let’s not have any illusions here — it’s a product of supply and demand in which the amount of available inventory is low and the demand is high.) DSPs are in an emerging space where supply is vast, and demand is small (but growing), and they still are taking a proportionally large chunk of spend (8-20% depending on the contract and volume) because the market is emerging and the average deal size is still quite small.

In emerging spaces, the technology vendors typically take much bigger pieces of the pie. For example, look at ad serving back in 1998 — CPMs were closer to a dollar. Look at rich media vendors, which could easily pull close to $2 out of the ecosystem back in the early days. But the core CPMs of the media in an emerging market are higher. Look at mobile: In 2004, the average mobile CPM was between $60 and $80, and is now below $5 (depending on who you talk to). And when the CPMs are high, and the market is still figuring itself out, vendors can take a big piece of the pie. Even in paid search, which hasn’t seen the bottom drop out of CPMs (for very strong economically provable reasons), the percentage of sustainable media spend by vendors hasn’t been very high. The simple truth is that mature media markets are only willing to allow very small amounts of money to leach away between buyer and seller for “table stakes” technologies.

Does this mean that the online advertising space is not as “hot” as investors have believed for the last decade? I think this space is incredibly hot — and that there’s a huge amount of value to be created and we’re only at the beginning of it. But let’s be clear. Let’s look each other in the eye and not pretend that the dynamics of an emerging market are sustainable over the long term.

There are only two tricks to play out here: You either need to be the Donovan Data Systems of your market (i.e., you are indispensible, are taking a reasonable percentage of spend as the dollars flow through you, and you’re the stand-out leader in your space). Or you need to be the company that redefines the market completely (i.e., you will use technology to fundamentally change the way the market operates). And if technology is at the center of that disruption and technology is the driver of that fundamental change, then suddenly the rules are different.

What bothers me about the space we’re in right now is not only that it’s getting really crowded, but also that most of the parties playing in the middle are not adding the value that a full corporate entity needs to be adding in order to both create and extract the value needed. Most of these startups are really more of a feature rather than a whole business. But if they’re just a feature, what do they plug into?

The problem is that consolidation is not easy. It actually sucks majorly — for everyone involved. I speak from experience; I was on the deal teams for of a bunch of companies we acquired when I was at Microsoft. I was involved in the projects to consolidate those acquisitions, and I’m friends with a bunch of folks who were in similar roles at Google, AOL, Amazon, Yahoo, etc. And it’s just never easy. The buyer has this nasty problem of a new and generally incompatible technology, plus a completely different culture — both of which are super hard to converge successfully.

And what about when you’re getting bought? It only works out well for those who are fairly mercenary — the ones who ran after the idea because they wanted to exit well, and who were determined to exit well, and were plenty happy to exit as early as they could. But what about for those who are in love with their own startups, who see them as children? Great entrepreneurs I’ve met look upon an acquisition as an opportunity to get their struggling products the visibility and distribution might that they deserve. And it’s called an exit for a reason. When your company is acquired, it ceases to exist. It’s no longer your company; it belongs to someone else, who is very likely going to screw it up and kill it.

The trick for having a successful startup in this space and a successful exit (not only for the cash value, but to have your beloved business count for something going forward) is for folks to be realistic about both the value they bring to the table and the way they can be leveraged. And let’s not forget that in order to really be valuable when you are acquired, your technology has to somehow rationally live in the context of the acquiring party’s landscape — both technically and culturally.

Exit earlier rather than later if you can — while you still own a good chunk of the company. As a founder, would you rather have 30 percent of $20 million, or 5 percent of $80 million? I’ll give you some advice — earlier is better. Exit before you have to scale the thing up — before you have to invest in customer support or in operations, before hosting everything in the cloud stops scaling for you cost effectively and you have to invest seriously in capital expenses and need to raise a lot more money.

And please — build your technology in as abstracted and “ingestible” a way as possible. Please — I’m begging you!

But I digress. The reality is that there are a lot of companies that are stuck. They’ve taken a lot of money, but they aren’t the leader of their space or disrupting their space significantly. And most of them have become targets for new companies coming in and running after them — and either exactly copying them (further commoditizing them) or disrupting them.

It’s these second-generation companies that are the ones to watch. They’re typically bootstrapped and generally doing more interesting things than their established competitors. And they’re the ones who are most ripe for consolidation because they can afford to exit for much less money since they haven’t taken as much from investors.

The only question is this: What happens when they get acquired? And what happens to the middle of the market — those that have raised $15-40 million and that have stalled on growth and suddenly face a plethora of competitors? They had better find a way to get profitable real fast.

An online marketer’s guide to the full product life cycle

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

Let me state the obvious — because clearly it’s not so obvious, especially to those of us working in online marketing. Most products and services are designed with a target market in mind. This market could be as broad as those of us with teeth, who hope to keep them healthy into old age, or as specific as 38-year-old women who want white teeth for their 20th high school reunions. The trend for the last few decades has been toward designing products for narrower and narrower markets — and using specific differentiation between target markets to drive sales and profits. And of course, with better targeting available all the time, the ability to hone the product to a specific subset of customers will become ever more possible.

The best companies use a combination of personas and scenarios to ensure that they are nailing the product requirements early in the design phase. These scenarios (sometimes also called use cases) are pushed into the hands of eagerly waiting marketers, who in turn get the product put into a strong series of marketing messages (and even the actual creative) that tie to specific target customers (the personas). The personas for which the product and marketing teams have developed their products ideally make up the basis of a media plan.

I’m frequently shocked at how few of the basics are used in the development of media plans for online marketing. And I’m frequently shocked at how products are released with marketing messages and targeting that don’t match. In many cases, the creative for online is either just completely different than the offline creative, or it has been so incredibly simplified for online that none of the powerful messaging from other media actually make it through.

So I thought I’d write a short primer for online marketers so that they understand the whole product life cycle and how they should be plugging into it. In advance, I’ll warn you that there are numerous methodologies here, and almost every company does this just a bit differently. So I’ll just push forward a simplified version of a typical process, and you should be able to apply the concepts as you stumble across them. And of course, if any companies you’re working with don’t use some variant of what I’m describing, you should be a bit concerned.

Product planning
In a perfect world — where there are plenty of resources, time, and money to properly plan a product — the model goes something like this:

Three to six months of market research are commissioned, funded, and executed to ensure understanding of the market demand for the product in question. This process begins with a series of ideas and invention, combined (at least for existing products and services) with feedback from existing customers, and is turned into a strategic plan for what product will be built.

In this process, the target personas for the customers to whom the product is designed to appeal are created. Ideally some market sizing is done to determine what the financial opportunity for all companies running after similar products and services might be — and what the specific opportunity for the product in question might be. Simultaneously, work typically is done to determine what scenarios will be supported in order to bring clarity to all members of the product team, from research to development to marketing to sales.

Example persona: Wealthy, highly educated, sophisticated urban empty nesters — Brad (64) and Sandra (62)

Example product: Online banking services for wealthy clients with multiple homes

Example scenario: Brad and Sandra live in New York City during the spring and fall, in Martha’s Vineyard during the summer, and in Killington, Vt., during the winter. They need a way to ensure that all their bills are paid on-time for all their properties, all year round, even when they are rarely there. This service creates a very clear portfolio of all their properties, and all their expenses, such that bills can be easily assigned to a property, tracked, and managed in a clear automated way.

Product planning is really the process of defining the opportunity at a broad level, and ultimately answers the question of why a product or service should be rolled out. The more discipline, time, and effort put into effective product planning, the easier the job of all the subsequent teams engaged in the process.

Product management
Once the product has been planned and approved, it’s time to build it. In this case, we’re talking about a software development project that will be rolled out via a website and a variety of apps across PC, phone, and tablets. The process entails defining the specific features, creating the project plan, working with the product development teams to ensure the correct product decisions are made, coordinating internal communications, and development of the appropriate key performance indicators (KPIs) to measure the product’s success in the market.

In most companies, the product management team is really the “product owner” and makes all the decisions and prioritizations of features of that product. Essentially, the team defines what will be built, leaving the how to product development. In some companies the what is shared between the product management and product development teams.

The key to strong product management is always being customer driven — which means creating very powerful and accurate personas and scenarios that always drive the “true north” of what is being built. This process should become the basis of what is handed off to the sales and marketing teams in order to drive the go-to-market strategy and sales positioning.

Product marketing
Product marketing is typically one of the most important teams, leading one of the most important efforts — but frequently this discipline is under-funded and under-resourced. In an appropriately resourced product marketing effort, key partners and customers are engaged in deep ongoing conversations. Ideally, the personas and scenarios that were created during the product planning effort received vast input from the product marketing teams. The go-to-market strategy for how that product will be launched, including all the marketing and training materials used by sales and customer services within the company, is managed by this team, which also feeds the key marketing positioning to the marketing communications teams.

If the product marketing team does its job correctly, the corporate marketing and sales efforts will be successful. Product marketing ultimately owns the decisions related to where and when the product will be rolled out (with huge dependencies on all the other teams).

Marketing communications
Given the intended audience reading this article, I won’t spend a lot of time here — as this is either you or your direct customer. However, a few key points are worth spending time on:

If the correct personas were created, the media strategy and even the core media plan should come together like a breeze. If the correct scenarios were chosen and executed against correctly by product management and product development, then the creative of the advertising should be quite easy to conceive and execute. In a perfect world, there is a direct feed from inception to creation to getting that product or service in front of prospective customers — and converting them to active customers.

There are, of course, many other teams involved any business, and all play critical roles at varying moments of the product lifecycle. Hopefully this rather nuts-and-bolts summary of the overall process will help those of you who have grown up attached to this mechanism either internally or externally, but who haven’t had full exposure to the processes and roles.

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