Building On-Ramps to Media Futures Markets

It's been a long time since technologists started building electronic systems for trading forward media . To be fair, it has been at least 20 years since the first companies gave it a shot. In fact, we have a little symbolic graveyard in our office to commemorate our fallen comrades. Some pivoted, some got acquired, some went out of business, and some were divisions inside big tech firms that faded into the background. All made valiant efforts. All failed to build a real exchange for forward media. Let's pour one out in their honor.

Fallen Comrads.jpg

Our fallen comrades who had taken on forward media buying and failed, could not effectively prove to both sides that their platforms and technologies drove greater efficiency and led to better deals.  

So how is it that so much media is bought on a guaranteed basis, but none of it actually trades. As far as we know, no one in the market provides a biddable environment for forward media. To have real markets supply must compete with other supply and demand must compete with other demand in the same market. But, competition is not just the application of a single bid to a single inventory opportunities, it also means the application of multiple bids to multiple inventory opportunities simultaneously. Without this, there is no real exchange, without a real exchange, none of these technologies were able to reach critical mass.

We can ask ourselves if there was a theme among all of these heroic attempts. Is there a common reason that we can point to? Is there one thing we can identify that tripped up silicon valley greats like Google, Yahoo, and Microsoft? We think there was. 

When we look at any of these "marketplaces", some of which still exist in one form or another, we see that they all actually provided ecommerce platforms for media, not exchanges. While that was true, most were marketing their products as if they were exchanges. If a searchable list of products that can be purchased, from multiple buyers,  through a website is a marketplace, than why is doing the same thing over the phone with a sales rep not a marketplace? (Because automated sales wasn't sexy or VC fundable)

Media buying is much more like portfolio management than buying electronics from Amazon. Setting aside the fact that none had an environment in which anything can be traded, none provided the types of solutions that enabled demand from other channels to flow into these forward media marketplaces. In real-time impression markets, pricing and analytics tools facilitated the movement of budget to increasingly targetable audiences. This in turn enabled the measurement of greater efficiency from real-time impressions markets than traditional insertion orders.  In short, buyers and sellers could measure how good of a deal they were getting and simply followed the money. And so, many left the on-ramps to their highways unbuilt. It was too hard to get into the markets, so none got traction. 


I Got 99 NP-Hard Marketing Problems...

We have spent a fair amount of time thinking about why some problems faced by data driven marketers are so much harder than others, advertising's P vs. NP problems. We were looking to find a reason why these hard problems have not been solved.

In short, we realized that there are two ways of thinking about solving data problems, the first is by modeling (think algorithms) and the second was a new idea. The new idea is that there are problems in marketing whose solutions are emergent from the data itself. In other words it can be measured but not modeled. Effectively it means that some problems can only be solved by working out every possibility and measuring which work and which don't. It means that the way we design our data models really matters.

Emergent solutions arise when new properties and behaviors "emerge," with no one directing and no one able to foresee the new characteristics from knowledge of the constituents alone.

In chemistry, for example, the taste of saltiness is a property of salt, but that does not mean that it is also a property of sodium and chlorine, the two elements which make up salt. Thus, saltiness is an emergent property of salt.

17th century economist Adam Smith described an "invisible hand", an emergent property of markets, that guides markets to produce just the amount and variety of goods that the public needs. The stock market has its own "invisible hand." The purely self-interested actions of thousands of buyers and sellers result in the purely blind workings of the stock market—the sudden shifts in activity and valuations, the bubbles and crashes—as well as the market's notorious properties of stupendous intricacy and frustrating unpredictability.

There are some problems in media whose solutions will only emerge from data. The key challenge is usually measuring and identifying the source of the issue. Once a problem can be identified and measured, it’s solution emerges from the data. Patterns can be identified and changes can be made.

Solutions for marketing problems such as attribution are data-emergent in nature. As evidence, look to the current models used for attribution. Frankly, the market has just begun measuring attribution and the models in the market kind of suck. We can’t even model how and why people click on ads, just that they did, let alone understanding why they made a purchase.

To do that we need to change the way we understand attribution data. Books are a good analog to attribution. What if we stored the data for a library in such a way that every book's data contained its translation to every language on earth. Fundamentally, War and Peace is the same story in every language, but understanding all translations at the same time will surely yield understanding that we couldn't get from just the English version. This exemplifies how storing the same basic data in different ways unlocks knowledge that was simply inaccessible before. The old way of storing that information made it invisible. Every language has its own unique way of capturing and communicating ideas. If a story can be told in every language, the underlying fidelity of the ideas in the story are far more well defined. The improved definition is the emergent property in this case.

Many of the problems we face in marketing are as difficult as they are to solve because the way we describe the underlying information needs to be improved. We are simply unable to see a solution because we are unable to identify the source of the problem.

The Dangers Of Scaling Today’s Addressable TV Buying Methods

Originally Published on AdExchanger

For more than a decade, some of the biggest names in television have been hard at work on achieving household-level addressability across their footprints.

Leaders in the space, such as Cablevision, Comcast and Dish, have deployed a great deal of hardware and software to ensure the right creative can be delivered to the right household. But what about the way in which the media is transacted?

Many in the television space have girded themselves for the onslaught of technology they fear will undermine their positions the way display publishers believe early open-market RTB eroded their pricing power.

The problem is that even though there is no real-time bidding in addressable television, the forces that weakened publishers’ pricing power in RTB are rearing their heads in addressable television. But it is not the programmatic or real-time technology that hurts a seller’s pricing power – it is the flow of information.

So, what is it about open-market RTB information flow that is similar to the information flow in today’s manual methods of buying household addressable television? Something is causing this asymmetry of the information flow that will undermine seller’s pricing power, even without any programmatic markets in place. When I shared this insight with some in the industry, the initial response was disbelief. After more explanation, they came to see the trends.

Sellers Left In The Dark

The root problem of the information flow asymmetry is a lack of shared understanding of what is being bought and sold. In the traditional model of linear TV buying, both the buyers and sellers understand the audience and placement being purchased. Both sides know how Nielsen defines the audience and both sides have a general understanding of what is being bought and sold. Therefore, the buyer and seller agreement represents a real market price.

Today’s addressable TV buyers are very different. The buyer leverages data from Rentrak and other third parties to identify a list of target households, which defines the media buy. This is where the information asymmetry begins. A seller that receives a list of households has no idea why the buyer targeted those households or what drove the value of the transaction.

If sellers have no idea why their products are valuable, how can they possibly determine a fair price? But that is how addressable TV media buys are like open-market RTB in display. The buyer knows everything about the product and what defines the value of the deal and the seller knows nothing.

In RTB markets, the publisher has no idea why any impression cleared at the price it did. A publisher has no access to the data the buyer is using to bid. This information asymmetry created a huge advantage to buyers through the use of open RTB markets. It is not the technology that undermined publishers’ pricing power – the technology just leveraged a specific type of deal model, which most onlookers conflated with the technology itself.

Repeating History?

So what does this mean for today’s sellers of addressable TV media? It means that sellers who relinquish control over defining products and packages will be doomed to repeat the long-feared loss of pricing power experienced by display publishers. For addressable TV markets to flourish, sellers will need to use first- and third-party data to certify packages and make them discoverable.

A buyer unwilling to define the target of their buy with the seller knows full well that the value of what they are buying is much higher than what they want to pay. It is a signal to the seller that buyer is only willing to buy the inventory if the publisher sells it below its fair value.

While this may be beneficial in the short term, transaction models that strongly benefit one side of the transaction become overly complex and fail to scale to meet market needs. This has been proven by the movement of display media liquidity from open market RTB to private marketplaces, header bidding and programmatic direct. Display publishers have sought alternative channels to regain lost control.

Continuing down this path for addressable TV media transactions will result in yet another technology and vendor map that is as confusing and complex as display. That’s something I’m pretty sure none of the TV media buyers and sellers want.

A Lack Of Market Forecasting Is Holding Back TV Media Trading

Originally published on AdExchanger

This year will be a great one for digital media trading. Digital media trading has jumped the shark and landed safely. Transparency will increase, fraud will decrease and market structures will only get better. Moving forward, the real challenge is to bring what we have learned to drive the growth and expansion of media trading into all other media and create unified platforms.

At this point, TV media is purchased and not traded. But that could change with the creation of better market-forecasting tools, which would improve our understanding of media markets, enhance decisioning and enable faster, effective and efficient technology-driven TV media trading. The inability to model and understand media markets is a leading obstacle holding back the birth of TV media trading.

Sellers of TV cannot reliably predict how trading may impact revenue flows, while traditional channels are reliable with forecastable revenue. If trading is not provably more reliable and revenue-accretive, there is no reason to switch from purchasing to trading. When sellers forecast higher yields via trading, there will be incentive to actively trade.

Unfortunately, display media is the petri dish where the earliest experimentation happens. Once technologies are created in display, companies try to cram those technologies into other media with little success. The trading technology developed in display was designed for machine-based trading, not people.

Discoverable Pricing, Secret Strategies

The challenge to developing appropriate TV market-forecasting technology is two-fold. The transaction space is highly fragmented, and the asymmetry between buyers and sellers makes the collection of granular data only possible on the buy side. Current technology makes market pricing and trading strategies inseparable, so everyone in the markets wants all of their data secret. Markets operate best when pricing is discoverable and strategies are secret.

As demand aggregators, agency buyers have a significant advantage. Buyers see upfronts, scatter, cable, satellite and local supply, while the suppliers only see the demand for their own inventory.

Broadcasters and networks have few tools to help them understand how to use packaging and pricing techniques to address viewership and market-demand fluctuations. Sellers can see the scatter budgets coming their way and what their sellout is, so they see both supply and demand, but only for the tiny part of the market that their inventory represents.

There is little that data sellers can use to understand granular demand across the market. Given this environment, people use their anecdotal experience and intuition to make up for the lack of data, which reduces the use of machines to add value.

No Solution In Sight

What is even more disturbing is that while the asymmetry exists, the lack of an organized market generating this historical transaction data means that no one is even working on this problem. Buyer and seller transaction information is so closely guarded that general trends are the best we can hope for.

No existing technology accounts for campaign goals, budget, available inventory, market prices or historical performance metrics. There is also no technology that offers recommendations for an optimal media plan.

On the other side, media companies lack the sales tools that enable what-if scenario modeling to understand how the demand they expect should be most effectively allocated across the media. In reality, media plans and media packages span multiple media and publications. That is what the deal conversations are all about, not a single impression or a line item for a placement. Buyers and sellers need a better way to forecast what those conversations will be like and decide the best course of action.

In Use Now

TV media buyers and sellers need better tools for making decisions. For real-time display, the tools are more straightforward, as people could never pull the trigger fast enough, so machines bear the brunt of the control.

For forward-media buying, in which TV is the 900-pound gorilla, people bear the brunt of control, and technology plays more of a support role. While there are some systems that help manage yield after the deal is made, today, the selection and decisioning of what to offer a potential client and the price at which to offer it is nearly completely manual.

With everything we have accomplished, we still face obstacles that will challenge this momentum moving forward. First and foremost among those is the revolution of market forecasting. Unified platforms require unified – not homogenized – tools and analytics to support omnimedia trading.

While media mix modeling has been around for decades, buyers’ and sellers’ ability to transact an ever-increasing granularity of content and audience programmatically is driving an increased need for a revolution of market-forecasting technology.

Momentum is moving in the right direction to help buyers determine what they can buy, how they can buy it quickly and easily and whether it turned out as expected. The technology for modeling what TV media to buy and sell has not kept up.

Everyone Needs To Understand These Media Trading Models (But Few Do)

Originally published on AdExchanger

I have a confession to make: Before writing this, I couldn’t really say that I, or anyone I know in ad tech, fully understood how different ways to trade media compared with each other.

There are all these different ways that technology brings buyers and sellers together to trade media. This stuff is so confusing and hard to wrap your mind around that I never really felt like I had a solid grip on it.

Buyers and sellers choose the trading models they want to use based on their objectives, technology and access to data. Each media trading model fills a niche in our ecosystem. Understanding the different media buying models is not about picking winners or declaring one better than another. That is up to you, given your business needs.

I set out to map these media trading models so that everyone can pick what works best for them and have a far better understanding of what is going on. To understand the different types of media trading models, I spent a few days talking to folks throughout the industry, which made it clear that it was time to decipher this enigma.

I decided to focus the comparison on three areas of a transaction where key business decisions are made by buyers and sellers. These are the handling of inventory before the trade, managing of the negotiation and how the deal’s final price is determined. The outcome of the effort to understand media trading models resulted in a visual landscape for media trading models that I call a “Media Tradescape.”

I designed it to compare 10 key areas where we can differentiate each of the nine trading models used in display media; I give more detail on each trading model below the tradescape. I’ve also included a breakdown of each trading model with corresponding characteristics as part of my “Table of Trading Models.”

What did I learn from my investigation? There is significant upward price pressure from demand within media trading environments. Since the advent of real-time bidding, an increasing number of media trading models have risen to allow buyers to access inventory at increasingly higher prices. Trading models developed in the last couple of years focused on unlocking trades for more effective and higher-quality inventory, at higher prices. The environment for transacting high-quality and high price-point inventory via technology is very much in flux.

You can download a PDF version here.

Inventory availability: Control by sellers to allow buyers to see forward supply. Some models empower sellers to give buyers a searchable supply, others empower sellers to answer requests for specific supply and, in some, sellers can't expose forward supply at all.

Inventory priority: The ability to guarantee inventory amount and price to a seller. Some models focus on reserved inventory, others on unreserved and some on both.

Inventory allocation: The way in which supply is allocated to demand. Once an impression is received by the publisher's ad server it attempts to allocate the supply to demand, based on the outcome of its yield optimization. If no desirable outcome is found by yield optimization, an outside auction is used to determine the outcome.

Inventory units: The definition of what is supplied and demanded. Units of audience are a mix representing all of the consumers of the supplied media, and “impressions” are units of supply that all share a common set of attributes.

Inventory targeting: The ability to apply granular definitions to the supply using a specific set of agreed-upon attributes. Some trading models enable targeting definitions from the supply side or enable use of definitions from the demand side, while others enable both definitions for filtering.

Pricing model: The units of price used by buyers and sellers. Most trading models are based on CPM pricing, while two support multiple pricing models, including CPM, CPC and CPA.

Seller offers: The ways in which supply is represented in each trading model. Some use hidden floors in an auction to set the lowest price a seller will accept. Others use a set of rules to represent offers to buyers and some use manual processes to set the sell offers used for trading.

Buyer bids: The ways in which demand is represented in each trading model. Trading models can be divided into environments where buyers can bid or buy using a take-it-or-leave-it price. Rules-based bidding allows buyers to set the price at which they are willing to purchase the supply. No-bidding environments provide an ecommercelike experience where buyers can only buy at the offered price.

Negotiation: The ability to consider both the seller’s offer price and buyer’s bids in determining the clearing price. Some models do not account for any negotiation since the price is determined manually by humans before technology is involved. Other trading models support a negotiation and the final price is determined by a technology.

Deal priced by: The layer of technology that determines the clearing price. Regardless of how the negotiation occurred, the final price at which each impression clears is either determined by the publisher's ad server, or that decision is outsourced to a technology outside the publisher's ad server.

This is my interpretation of the landscape of media trading models. I want to have a shared understanding of these trading models so let’s have a conversation. Please add your perspective to our shared understanding of the space. I and many others would be very happy if we could clear this up.

Below is the "Table of Trading Models," which breaks down this information by trading model. You can download a PDF version here.

Four reasons why ‘Infinite’ media is a lie

The idea of infinite digital inventory has been batted around as a concept among colleagues for a long time. Every time I hear this, I get pissed. The reason for this reaction is that I know some folks are turning a blind eye to what is actually happening in advertising markets. There are four ways in which the lie of infinite media is created.

In reality, there is too little real supply.  If real supply and demand are in balance, there is very little room for shenanigans.

First, let’s prove media is not infinite. Then, let’s examine why people think it is. Lastly, let’s contrast the idea of infinite inventory with the idea of finite attention. I’ll use the analogy of data transfer. To illustrate, let’s think of inventory as the volume of data and attention as bandwidth. The idea of infinite inventory is like saying you have unlimited data on your internet service. Everyone can effectively download an infinite amount of data, the question is how fast.  If you try to watch 4K video over DSL, you will get 10 seconds of buffering for every 1 second of video. In this same way, the idea of infinite media ruins the attention experience. If a single user has limited attention bandwidth than the sum of all users also has a limited attention bandwidth and therefore media is finite. The essence of media is the content consumed and attention opportunities it creates not the number of ad placements served.

Now, let’s examine the lie of infinite inventory. Let’s start by assuming it is correct, there is infinite inventory. If true, it is important to consider some possible causes.

1.      There are so many users and so many ads served that there is not enough demand to meet the supply. Supply is growing faster than demand making supply effectively economically infinite.

2.      Infinite supply is produced to syphon off known demand: bots and non-viewable inventory.

3.      The accuracy of and transparency of 3rd party audience derived from lookalike models.  Overly broad segment definitions can create the illusion of far more inventory than actually exists.

4.      The way in which the amount of inventory is measured yields a false count.

Now, let’s address these one by one.

In terms of users, yes, the number of users and the amount of time spent online has grown significantly over the last decade. But let’s be real, finding the right audience, in the right environment, at the right time is pretty darn hard, let alone finding an infinite amount of it. Further, supply can be exponentially increase by flooding ads on a page, turning an article into a ten page slide show, and many other tricks that provide for lots more ad inventory crammed into the same attention bandwidth.

In relation to bots and non-viewable inventory, tomes have been written. In reality, this is inventory that provides zero real audience attention. If media really was infinite, than fraud and ad blocking would not be real issues. Blocking ads, in other words removal of supply, is not a problem when supply is infinite. Further, adding supply via bots, should also have no influence on the market as we could simply replace the lost and fraudulent inventory with real inventory. Further, if $7.2 billion of fraud will take place in 2016 as the ANA study finds, it should leave a pretty big ‘mark’ in the marketplace. It is really hard to hide $7.2 billion. If all programmatic spend in 2015 was $14.2 billion, according to Magna Global, there are a lot of folks making a significant portion of their revenue via fraud.  I’m not a tin-foil-hat conspiracy kind of guy, but if some players in the industry are profiting from this fraud there must be many other players who are happy to look the other way. Said otherwise, if you are willing to buy fraudulent traffic, there is an infinite amount.

Overly broad audience segmentation models are also perpetuators of this lie. For example, a couple of hours of research shows that about 6% of US households replace their car every year. Add to that the fact that the buying consideration period is about a month, then only 0.5% of the population is actually in market for a car at any given point in time. Said otherwise, any data provider that tells you that a general interest or news site can sell you auto intenders that represent more than 0.5% of their audience over any period of time, is likely broadening the model to ‘create’ audience inventory. Using lookalikes may yield lots of opportunities, but do you know how many of those auto intender lookalikes are really auto intenders and not just people with similar behavior? What behaviors drive the model? Just because I visited ford.com and gm.com does that mean I’m going to buy a car?

Last is the way in which we measure inventory. Some buyers and sellers have overcome this measurement problem by transacting on share of voice. Using this model, deals are a commitment for a portion of the overall attention instead of the number of impressions. Measurement by impressions is very easy to manipulate, measuring by attention or share of voice is nearly impossible. If you were choosing between two inventory sources at the same price and you knew that one had 20 ads on the page and one had 4, you would choose to run your ad in the media that was less cluttered. Share of voice or share of attention based deals remove a publisher’s incentive to cram ads and guarantee the buyer is buying the attention that they bargained for.

It’s time to open our eyes. It’s time that legitimate advertisers and publishers take control of the market. Because in the end the lie of infinite inventory only hurts the good guys and makes money for the bad guys.

Analogy Makes It Obvious: The RFP Is Bad News

Technological tillers teach us that sticking too much to old perspectives and ideas is a surefire way to fail. We need to stop thinking of the automated RFP as the product itself, but rather a framework allowing buyers and sellers to access media transactions. If the framework can be avoided while simultaneously creating a better experience for media transactions, then that framework should be avoided.

If technological tillers are ignored new products and technologies fail. For those who acknowledge and solve the problem, it generally  results in a revolution and massive success.

I recently watched a great keynote that I thought applies directly to transacting media and specifically media trading. In  short, the main point is that sticking too much to old perspectives and ideas is a surefire way to fail. The term  for this behavior is 'technological tiller.'Scott Jensen, product strategist at Google, gave this great talk on this subject and came up with this great new term, the  'technological tiller.'  Scott defines a technological tillers as happening when we sticking an old design onto a new technology wrongly thinking it will work.  He derived the term from a tool called a boat tiller, which was, for a long time, the main navigation tool known to man. Hence, when the first cars were invented, rather than having steering wheels as a means of navigation, they had boat tillers.

Cars that used boat tillers to steer were horribly hard to control and prone to crash. Cars could only get widely adopted after the steering wheel was invented and added to the design.

With an understanding of technological tillers, the two main types of media buying, real time and forward,  look very different. For everything that was built using the RTB protocol, there was pretty much no old perspective to stick to when building the technologies and processes, so many problems were avoided and there were no tillers to speak of. For forward media trading, this lens of the past has driven most technology to be developed using the old perspectives. RFPs are a technology tiller. The context and the technology have changed dramatically in recent years.

Worse still, most of the language of media buying and selling technologies was created in the realm of inventory management. Before media could be bought and sold effectively, the very first pioneers of media technologies created technologies such as cookies and ad servers. This first generation of technologies was not developed to support media buying and selling, it was designed to facilitate an understanding of what, and how much, inventory would be available at some time in the future, to track the activity of users for the media owner to provide a good experience, or other non-transactional reasons.

For media trading, this is a valuable lesson:  context or technology changes most often require a different approach. In our car example, the new technology that added a motor engine to a horse carriage needed the new design of the steering wheel to make the resulting technology, the car, reach its full potential.

For forward media trading to reach its full potential we need something different than the RFP. Linda Boff, chief marketing officer at GE, recently wrote a great article Marketers: It's Time to Say RIP to the Media RFP

"...when I think about the many ring-around-the-rosy conversations that characterize the standard RFP process, I literally want to cry. In a post-RFP world, agencies and publishers don't waste time on proposals that will never go anywhere, and brands don't devote resources to sifting through cookie-cutter submissions. Instead, time and talent can be invested where it matters: in identifying breakthrough experiences that are good for users and drive attention -- the only metric that really matters."

The only thing that Linda does not address in this great article is what the solution is. In other words, if automating the RFP process is a technological tiller, then what is the steering wheel solution for media buying? And that my friends is why media futures technology is so very necessary.

Be Prepared for the Great Advertising Technology Tsunami

What is the next big thing out there that is really going to change the media game? I’m talking about tectonic changes. The way the introduction of display advertising really changed the game or what we are witnessing today with mobile. Where is the next big wave of disruption? It is going to be the expansion of markets and trading technologies. That might seem a bit obvious, but I think what is driving the change is very different than what drove it in the past. It is this reason that will make the next wave of media trading so disruptive. The most recent disruption in this space was the ability to buy impressions in real time. The difference is that real time was a bolt on to the existing system. Real time bidding made something possible that didn’t exist in the past, the allocation of an impression based on real time market dynamics. The next expansion will be different. The next expansion of advertising and media technology will not be a bolt-on, it will drive changes at the heart of media buying and selling.

So, how can disruption be measured in our business? For media, disruption is measured in the ability to shift spending on a media plan. Better ways to achieve campaign or media buying goals is the measure by which media products are judged and priced.  The better the product, the more demand it will capture. Looking back, it is clear that the advent of display media really moved a significant amount of budget around in media plans and that mobile is doing the same today.

We saw the first move in the expansion of trading technologies when programmatic direct became possible in display. That small foothold has been expanding into things like print and outdoor media. The new changes are starting to build. The new systems are not the media planning platforms of old. Those were just messaging and ticketing systems that automated the paper process. These new changes bring new processes. Much more efficient processes.

There are literally billions of dollars of opportunity to create value by eliminating fraud and unviewed impressions. To do that, processes have to be better. We all know that the old way of media buying is just not measurable enough anymore. Measuring better means more efficient capital allocation and better outcomes. It means that sellers need to be able to slice, dice, and price their available inventory much better, and buyers need to be able to find it and bid.

This is the next disruption in media. Media transactions will be smaller and more frequent. Buyers will be buying shorter flights and more targeted audience segments. This means buyers and sellers need the tools to help them do what they already do, but at scale. Give people more time to make more decisions by speeding up or automating more of the basic administrative stuff. It’s like the difference between a hacksaw and a Sawzall. They do the same thing, except the Sawzall allows the carpenter to focus on cutting without worrying about powering the saw. The next disruption in media is power tools for buyers and sellers that meaningfully impact how budgets are allocated across and within media plans.

How Should We Measure Media Value?

Originally published on AdExchanger

Measuring the comparative value of media inventory has been a longstanding challenge. For both sides, the relative value of media inventory is the most important measure to determine price.

At the heart of the problem is the fact that each buyer measures value differently. While that is true, the questions each buyer asks to find value are the same. Being able to answer these questions about available media inventory means that the optimal mix of targeted inventory, given current market conditions, can always be found.

If a media-buying team can answer all of these questions about all if its inventory sources, it can confidently say that it is always buying the best-performing inventory at the lowest price, given the condition of the market.

Since guaranteed deals set the price before the deal is done, the exact value of each possible deal can be compared to determine which will provide the greatest amount of value in budget.

How did the media I bought from this source perform on each metric?

In media, value is measured by the amount of performance achieved. Since performance happens along multiple measures, viewability, click-through rate and conversions, we can think of each of these as a measure in the value space.

Simply put, the best answer that a targeted inventory source can provide is that every impression is viewable, every impression results in a click and every impression converts.

The worst answer is when viewability, clicks and conversions all total zero. When everything converts, every last bit of value was captured. When nothing converts, no value was created.

How efficiently was this source’s inventory moving prospects through the funnel?

The next challenge in measuring value has to do with how steep the sides of the funnel are. In other words, how efficiently does the audience of this inventory source move from the top of the funnel to the bottom? Low viewability and a high conversion rate are just as inefficient as a high viewability and a low conversion rate. The efficiency of the funnel measures both. The wider the funnel is at the bottom, the better.

How much performance and efficiency am I getting from this inventory source at this price?

In the end, it is about effectiveness. Inventory that delivers high value may be important, but if the price is too high, it might actually be less effective than something cheaper. So when comparing different media inventory, it is the combination of value and price that drive the decision.

How much audience scale does this inventory source have?

Having fairly priced and efficient inventory is great, but there is still another piece missing: the amount that is available for sale. Being able to achieve campaign goals with the least number of sellers is important in keeping down the cost of the media buy and ensuing administrative costs.

If the media-buying team can answer all of these questions about all of its inventory sources, it can confidently say that it is always buying the best-performing inventory at the cheapest price, given the condition of the market.

Without viewability price does not measure value

While much discussion of viewability has taken place, there is still room to discuss viewability in the context of media markets. The true price at which something will sell in the market contains a very important bit of information. Pricing and market data within media are like the DNA building blocks for our understanding of the market. You need to have all the pieces to understand what is going on. True price is the most important piece of information. For buyers, not having the ability to understand the unit price of inventory, which will be viewed by real audience members matching their targeting, means there is a missing piece in the DNA that makes up that buyers’ understanding of the market. Without the knowledge of price, a significant amount of decisions cannot be made with certainty. An impression that is not known to be viewed has a price that has little information buyers and sellers can glean from. Viewability measurement is so important because without it, price cannot be used to compare the value of different media inventory. In turn, that means that a real negotiation is more difficult.

Buyers and sellers want to know that they are doing business ‘on the level’. Viewability is not about higher or lower prices, viewability is about finding the right price. For those hiding in the shadows, lack of viewability hides true quality, artificially raising effective price, and can be used as a negotiation bludgeon to artificially lower price. In the end though, all the good folk of the media market just want fairness.

In media markets, buyers know ‘a price’, the problem is that the price they know is not exactly for what they are buying. Some media buyers will read the previous statement and disagree. I argue that the only price the buyer cares about is the CPM of all the real impressions. If a buyer knows how many impressions were shown to their specified audience of real people, in a viewable manner, and the real unit price of what they’re buying, before the purchase, they can proactively select the inventory that will perform best.

Media is not a commodity, the viewability of each publisher is unique and the mix of real and bot impressions is unique. Moreover, two buyers who buy the same inventory at the same price will not achieve the same ROI. So, every publisher is different and so is every buyer.

Let’s work through an analogy. Imagine you’re a contractor building houses. You have an opportunity to build houses that you know will sell for $1000 per square foot. What should you build to maximize your profit? Well, if you consider all the materials and labor, you can mathematically figure out the most profitable size house to build. But what if you had no idea what the price of the real materials would be when you need to build the house? What if the amount of defective materials varied by store and manufacturer and you had no way to measure it? Viewability is exactly like that. Without viewability you don’t know the actual price of the product that you need to buy.

Today, the data landscape is rich with solutions that help separate the wheat from the chaff when it comes to impressions. This data powers buyers’ ability to look past the amount they paid and into the price of target audience and media.

Using that data to power media buying decisions, the ability to measure substitutability begins to emerge. Figuring out “what to buy instead” is a very important function of the buy side. Houses are not commodities, but we all know that when you have to choose a place to live you figure out how to balance the good, bad, and price. The second choice at a lower price can quickly become your first choice. Without viewability, you cannot accurately measure price, and without price you can’t make good decisions to balance the good, bad, and price.

The Programmatic Catalog

As the process of media transacting becomes increasingly streamlined, the number of buyers a publisher interacts with continues to increase. While many are hidden behind the real-time technology stack, publishers have many more counterparties buying their inventory than ever before. The increasing presence of technology and complexity of the media transaction process  has created a new need – product information management. The recent acquisition of Yieldex by AppNexus for its forecasting capabilities and programmatic direct platform is a clear indicator that the big players are beginning to recognize this need. Ad Ops and Sales teams need an electronic map of the inventory landscape. What is on the map? How much of that inventory do they have? At what price should it be sold? In which channel? Publishers need an “app” that can do all of that by automatically collecting and analyzing data. Remember Programmatic Inventory Has A 'Yellow Pages Problem'? Folks have been talking about this since 2012

With that in mind here is a simple question: do publishers manually update their audience data? Are there analysts that update cookie profiles? We all know that the answer to that is no. So why should publishers have to manually create all their placements, ad units, products, and guaranteed targeting in the ad server. Publishers should have tools to scale up that process using technology.

Today, solutions construct a single view of the future. In reality, there is not one future, there are a bunch of possible futures each of which has a different probability of becoming reality. The future is uncertain but understanding the landscape of things that will very likely happen, will probably happen, and might happen can be clearly defined.

Obviously there are too many ways to sell and too many prices for today’s manual processes to address. The problem is that you can’t just update the current process. Almost all of a publisher’s new buyers have a very specific set of buying criteria for media. None of these criteria exist on the rate card and none of them has a price someone can just look up. It’s just too complex to sell that way. In the real time environment, data companies have filled the need for near instant classification of impressions for sale and pricing is solved for via auction. What has not changed is how publishers classify forward inventory.

Fortunately, these problems have been faced by other industries and has been solved for them by some of the best technology companies in the world, Oracle and IBM to name a few. It’s called a Product Information Management System (PIMS):

Centrally managing information about products, with a focus on the data required to market and sell the products through one or more distribution channels. A central set of product data can be used to feed consistent, accurate and up-to-date information to multiple channels such as sales teams, marketplaces, and direct deals. - Modified, from Wikipedia

Some will contend that they have such a system. While that may seem true, almost all the information in their system is created, maintained, and updated manually. Again, do publishers manually update their audience data?

A product information management system for publishers should be designed to be integrated with all sales channels, provide an accurate and constantly updated catalog of all the things that you can sell, how much inventory is available for each, and its price. Synchronized systems allow publishers to increase prices as inventory is selling out or decrease it if it is going unsold. It keeps sales teams, marketplace offers, technology partners, and ad ops teams all on the same page. Publishers can present any package they could possibly sell, with an appropriate price, to any sales channel, at any time through a single synchronized platform.

We Need To Rethink Marketplace Fees If We Want Better Liquidity

Originally posted in AdExchanger We can thank the long struggle between advertisers and agencies for the fee structure used throughout today’s online advertising industry. Agencies have always wanted to pass marketplace fees on to advertisers, but advertisers only want to pay media costs.

As a result, a significant portion of the industry hides transaction costs in the media price. Transacting environments nearly always charge the publisher by deducting a fee from the buyers bid. It is unclear if any transaction business in the industry has been able to layer its fee on top of the bid.

This struggle between agencies and advertisers has hamstrung the whole industry by forcing the use of a fee structure that fails to yield the best result for anyone. I believe that moving to a make-or-take model can fix this and improve market liquidity for everyone.

In the end, everyone seeks to get the most value out of any transaction, even when that transaction is buying services from a marketplace. The most obvious strategy is to maximize our own outcomes. Given that we know we will all act this way, does every fee structure for the services of a marketplace have the same result? No. The best model is one in which everyone’s interest are aligned, including buyers, sellers and the marketplace itself.

‘Going First’

There are two types of participants in a market, and I’m not talking about buyers and sellers. We need to look at the participants of a transaction in a different way.

In every transaction, there is someone who “goes first.” More specifically, they are the first party – it could be either the buyer or seller – to state the price at which they are willing to do the deal. That information creates liquidity. The marketplaces in which lots of buyers and sellers are willing to broadcast their price need far fewer transactions to be liquid. In contrast, the markets where the price at which buyers and sellers are willing to make a deal are secret need many more buyers, sellers and transactions to be liquid.

That being the case, it doesn’t matter if you are a buyer or a seller, “going first” is clearly a benefit to everyone in the market. So, the side creating the benefit should be rewarded and the side consuming that benefit should pay. In a marketplace, a fee structure that accomplishes that objective is called a make-or-take fee structure. In other words, if a buyer puts in a buy order before there exists a sell order to match with it, the buyer gets the reward. It is also true the other way: If the seller puts in a sell order that must wait for a buy order to match, the seller gets the reward.

This way you can always choose to go second and keep your desired price secret until you see someone on the other side that wants to make a deal at your price.


This strategy makes for a business model where buyers and sellers are rewarded for participating in the creation of a crowdsourced “book” of supply and demand that all participants have access to. In stock markets, the side that is “going first” is referred to as making liquidity, while the side that is “going second” is said to be taking liquidity. Hence the name: make-or-take model.

In real terms, this means the current financial exchanges, such as the New York Stock Exchange or NASDAQ, charge market participants who “go second” about $0.30 for every 100 units, of which they pay the participant who chose to “go first” about $0.27. The difference, $0.03, is the exchange’s revenue. The implication of this model is that those who choose to “go first” in the market actually get paid to trade.

For a long time, folks in the industry have dreamed about a central repository that enables buyers and sellers to understand at what price inventory will clear and how much is available. But if buyers and sellers receive no benefit from listing their intentions in this repository – meaning there is no payment for “going first” – no one will do it.

That is why the dream of a giant catalog of available inventory has not materialized. There is no mechanism in the market to create that incentive.

For Guaranteed, 2-Sided is better than 2nd Price

Hal Varian, Chief Economist at Google once said “All of the major search engines use auctions to price ads. The reason is simple: there are millions of keywords that need to be priced and it would be impossible to set all those prices by hand.” Hal’s thesis was the underlying rationale for using the same auction model for search and display advertising. That is why today’s exchange technologies all operate using a second price auction. The problem is that you can’t use second price auctions for guaranteed. Which is why no one is doing it. There is a better way to trade guaranteed media. We can’t leave the best guaranteed inventory to sell through technologies which ecommerce figured out 20 years ago.  We need a market driven, technology powered, negotiated marketplace to buy and sell guaranteed media.

At first, it is easy to think that the focus of Hal’s statement is about labor. But if you look more deeply, you find that the key action in Hal’s quote was ‘set all those prices.’ If you can’t calculate and set prices as a seller you need the buyers to set them for you. Or in Google’s case, if ‘can’t’ is because it is too complex or expensive, you let the auction do the heavy lifting for free.

What if the problem of ‘set too many prices’ is already solved? What if there was already a way to automate it too? If that were true, the seller would want to have control over setting the ask price of their sell orders. The nature of guaranteed is that we have much more time to buy and sell it. If the seller has no bids, they can wait. If a buyer sees no inventory they can leave a bid. This type of trading works much better in two-sided auctions.

The fundamental difference is that two-sided auction transaction prices are set by both sides. Neither side has to do the deal right now. Guaranteed media is a negotiated media transaction, there is no negotiation in second price auctions. The auction decides. In a negotiated environment, each side has the power to change the price at which they are willing to do the deal. Negotiation is all about change.

Two-sided is different:

-Auctions match bids and asks, they don’t determine clearing price.

-Resting orders. Buy and sell orders stay open.

-A continuous auction where a buyer describes demand so it can be understood by any seller, to identify if they have matching inventory they may want to offer in reply, and vice versa.

- Depth of forward supply and demand liquidity can be measured. - Supply competes for demand and demand competes for supply in the same auction.

- Buyers can search for supply and Sellers can search for demand. Buyers can query sell orders and sellers can query buy orders; each can query the price and amount required to fulfill their order.

- Market data is deterministic.

For this, orders have to be kept in a ‘book’ and every market participant needs to be able to see this book. If you know what the supply and demand in the market is, you don’t need to guess what it will be. Negotiation of all those prices is possible because the problem of ‘set too many prices’ is already solved.

As an industry we need to have a new conversation about technology for guaranteed. Current guaranteed models that use the ad server as if it was designed to be the back-end for an ecommerce platform for guaranteed media buying don’t meet the needs of buyers or sellers. There is a much better way than ‘add to cart’ and ‘proceed to checkout.’

We can’t rely on auction models designed for substitutable real-time keyword searches to trade inventory that is not substitutable. We need innovation.

Illiquid Media Markets Leave Industry Flying Blind

First publisher on AdExchanger January 26th, 2015 Markets and exchanges are now an everyday part of life in the media industry. Like all businesses, they seek to maximize value for customers and create the best possible incentive for buyers and sellers to participate. Since exchanges and markets are two-sided business models that bring buyers and sellers together in transactions, they must incentivize both sides to come to the table to the greatest degree.

In other words, markets and exchanges succeed when the opportunity to transact is maximized for both sides. This happens when markets are as liquid as possible. Unfortunately, today’s media markets and exchanges are just the opposite, which leaves buyers and sellers playing a guessing game.

The most visible symptoms in this illiquid market are massive volatility in several areas, including the second price, across all platforms, in open and private exchanges and the supply in open-market inventory. In financial markets, a 5% or greater spread between bids and what is asked is a sign of illiquidity. In media exchanges, the bid/paid spread averages 50%.

For sellers, this means that price floors are not effective in creating bid tension, which hurts aggregate revenue and has driven the recent shift to private markets. For buyers, supply is sporadic and unreliable as higher priority environments, such as guaranteed and private markets, intermittently siphon off supply, which increases price volatility even more.

The price volatility and lack of reliable supply make it nearly impossible to understand what the market thinks any impression is worth. We’re all flying blind. While there are market models that solve for these problems, none of the major players use them.

One Market, One Buyer

Currently, each bidder in an impression auction is likely bidding on a different set of attributes with a different ROI forecast. There are negative economic side effects when impressions are put into auctions designed for perfectly substitutable  goods. In reality, each bidder is in their own micro-market with the publisher. A market with one buyer is not liquid, even if combined with many other buyers in a single auction.

When Google introduced a one-sided auction for search, it was, and still is, the right auction structure for that type of media. If all you know about an impression is the search string, such as “Hawaii flights,” all searches are equal. But when that market model was introduced to display media and used beyond bottom-of-the-barrel inventory, funky stuff started happening.

In the current auction models, buyers have no idea at what price sellers would be willing to sell. Sellers have no idea what an impression is worth. The auction model is designed to figure that out. But does the market model make sense if buyers and sellers already knew what an impression is worth before sale? Not always.


While many refer to the opportunity to transact or the availability of impressions in a market as liquidity, like all things related to media trading, there is a subtlety when talking about the opportunity to buy actual impressions. The classic definition of liquidity is something that can be sold rapidly, with minimal loss of value and a continuous supply of willing buyers and sellers.

In a real-time delivery market, such as classic RTB and private markets, there is clearly a lot of speed, but what about the loss of value part? Selling an impression for some amount of money is better than nothing, but if the sale drives down the price of future transactions, value has been lost even if the sale generated revenue.

For example, airline seats, like impressions, yield nothing if left empty. But if a plane is half full, you couldn’t buy that seat for $10 at the airport counter and there would be no second- or first-price auction to determine the price of that seat. That would teach airline customers that seats could be bought very cheaply, at the last minute, which would drive incremental revenue and sell seats quickly but at a loss in the value of future sales. Eventually, customers would expect to pay less and would wait until the last minute to buy cheap seats.

A market is liquid if assets can be rapidly sold with little impact on value. The precipitous decline of media prices since the introduction of RTB and private markets, regardless of the number of bids, indicates the market has little liquidity.

A Willing Seller?

A 2013 study by Yuan, Wang and Zhao contains a visualization of auction liquidity by mapping bid price and price paid from 12,965,119 auctions, 50 placements and 16 websites of different categories.

In each auction the spread between the bid and price paid is the same as the gap between the first and second price. The spread is used to measure liquidity. This data indicates that the impression auction bid/paid spread average about 50%. In most financial markets, the bid/ask spread is less than 1%, while anything greater than 5% is considered illiquid.

That may sound like heresy to many media professionals familiar with ad tech. In reality, the essential characteristic of a liquid market is that there are always ready and willing buyers and sellers.

In real-time markets, sellers do not know if there are willing buyers until they offer the impression for sale. Sellers can guess what buyers may be willing to pay based on historical data, but there are no buy orders in the market for them to act against. For buyers, the lack of a “buy it now” price, with only price floors, means they don’t actually know if there is a willing seller.

All of this carries big economic implications, including the fragmentation of display media into billions of individual and illiquid micro-markets. The historic decline in publishers’ pricing power since the introduction of real-time markets has been driven by the creation of illiquid markets that have the illusion of liquidity, not the oft-repeated industry myth of infinite inventory.

Programmatic Direct Is Automatic Not Programmatic

It's time to clear up some of the marketing doublespeak that has surrounded the growth of programmatic direct. There is a distinct group of folks who are working hard to muddle what programmatic direct does and apply what people have learned from real-time-delivery markets, by over emphasizing the intelligence of the automation.  The strategy to do this is based on leveraging all the hard work  real-time and private market technologist have done to develop fast and smart technology. Marketers of programmatic direct are equating the cruise control feature of your car to Google's self-driving cars. One is automated and one is programmatic. One just does while the other is 'thinking.' That's a big difference.

In short, real-time and private market technologies work really hard to allocate each impression so that it will yield the highest revenue to the publisher and to sift through billions of impressions daily to find the right audience for advertisers. These systems do a lot of 'thinking.' They work to understand what is actually happening in the real world and automate choosing the best decision to make. In short, exchanges, markets, SSPs, and DSPs, leverage lots of data and technology to make lots of decisions really fast. That is the promise of programmatic.

To draw comparisons to other technologies, programmatic direct is the grubhub of ad tech. Customers can see your menu and put in orders that are trafficked right to the kitchen. The difference is that real time technologies help to optimize transactions for buyers and sellers in terms of both pricing, performance, and the application of audience data. None of this happens in programmatic direct. The real-time stack is like a technology that helps a restaurant figure out if they should use the ingredients in their fridge to make Vegetable Chow Fun, Pasta Primavera,  or Bún Chay to get the highest revenue from the ingredients in stock. For buyers the real-time stack helps them to figure out what is the best veggy noodle dish to buy in the market at the moment.

So, yes the programmatic in programmatic direct means automation, but it is not the same programmatic that is in real-time markets. It is not as good and it is not as smart. The trick was to co-opt the meaning of the word to make things seem better than they actually are. There is a reason why  we have two separate words for programmatic and automatic. If it is the same, why didn't the ad tech marketers choose to call the technology automatic guarenteed? The reason is that programmatic has a 'sexy' that automatic does not have.

Our friends over at AdSlot seem to agree. They built this nifty graphical illustration titled Automatic Guaranteed.  Nice to know that we agree.

In that context, let's clarify how MASS Exchange is unique:

  • A unified view of price and depth of supply and demand for future impression inventory.
  • A programmatic system that drives transactions by 'thinking' through market conditions, not an ecommerce platform for media.
  • An environment where bids to buy and offers to sell are matched by a rules-based matching engine in real-time, but impressions are delivered at some time in the future.
  • Analytics that provides sellers a better understanding of their inventory in the context of market demand.
  • Siloed markets seamlessly connected via a unified market interfacing technology.

The Mystery of the Impression Auctions

There is more than one way to auction impressions. Understanding that difference is something that can best be explained with a simple story. Let's imagine for a moment. You are walking down the street and someone hands you a box. It is heavy, so you hold it with two hands. Surprised that some random person handed you a box in the middle of the street, you stand there for a moment, confused.  You think to yourself "what the..."  and start to play-back in your mind the hand-off that just occurred.

As you focus your thoughts on what just happened, you hear a voice calling out. You can't quite make out what it is saying. You shift your focus to find that voice is actually yelling at you, yelling $51.07. "Wait, what $51.07?" you think to yourself.  And then it dawns on you, that the person right in front of you on the street just offered you $51.07 for the box. So you look down. "What's in this box?" As you look down, you notice that the flaps of the box are closed using one of those self-folding interlocking methods. Still. there is a gap. One big enough for light to shine through so you can see inside.

Inside the box, you see a bunch of stuff. Some things look cheaper and some more expensive. You think to yourself, "Huh, sure, I'll sell this." At this point you are sure that this box was destined for the trash, but you could sell it.  So, you take the $51.07. Before you have a chance to put your money in your pocket it happens again, another box, this time at $95.06.

You're happy, you just got a bunch of cash for something that was about to get tossed out. You turn to make your way back and you realize that right behind you stood an antique store. One that is closing up shop and moving. In fact, today. The movers are bringing boxes out of the store. Suddenly, one of the moving guys hands you another box. And just then, you realize that those boxes were not about to get tossed out.

That is the story of information asymmetry and that is what is happening in many auctions today. What just happened to you on the street was a perfect example that there is a key piece of information missing from the sellers decision, that the buyer has. The people on the street offering money could see where the boxes were coming from. In fact, they also had their own information about what was inside the box. Now, let's compare that to how that closing-down antique store use to sell and auction its wares. Before shutting down, the antique store would post their prices on the merchandise and allow potential customers to come in an inspect it. When they needed to move some inventory, they would hold auctions. The key similarity between both is that the antique store would tell you exactly what you were about to buy and let you inspect it.

In this situation, the antique store is making a transaction based on a good price. The decision here is simpler, it is just "what is this worth?" In the boxes situation, the decision is much more complicated "what is this thing and what is it worth?" If the definitions and sources of that kind of information lack a common and agreed to standard, buying and selling can only be like the boxes situation and never like the the antique store situation. Value and price are very important decisions that need to be made by both buyers and sellers. If those two elements are determined separately, than both sides have a better understanding of transactions and potential transactions.

In  the broader worlds, there are many ways to buy and sell, and many ways to manage risk. The greatest value is created for buyers and sellers when they can choose the  best way for themselves to buy or sell. In some situations one way is superior, in others, another way is . The diversity of methods is a critical part of a healthy and vibrant market.

The Frontier Of Innovation In Advertising

The evolution of advertising technology innovation is shifting. It used to be pipes. Now it is something else.  In the last few years, technologists have been hard at work building an interconnected network for delivery and bidding across the media industry. Now, the network has reached critical scale. This is when things change. There are many day-to-day technologies that we take for granted because the networks they built have already reached scale - credit cards, telecommunications, and social media to name a few.What good is a phone if there is no one to call? Why would you use a social network if nobody that you knew was on it? What use is a credit card if you can't find somewhere to buy stuff with it? Networks are awesome! Networks create a whole new set of value propositions to their users. The value of the network isn't just that it provides a simple way for members of that network to communicate. Does a traditional phone call between two people have the same value proposition as a conference call, just smaller? No. One conversation among many people is not the same as many conversations between two people. That math has no power here.

The evolution of advertising technology is shifting to the "conference call." The reason that you have seen fundamental innovation in our industry stall is that the basic rules of the media plumbing are set. Innovation among  the major players now focuses on scale, speed, and cost of operation. That's cool, but those are not fundamental problems facing the advertising and publishing industries. Media buyers and sellers just don't have enough communication in the market about what is going on. Communication in the market can bring about amazing outcomes.


In an AdExchanger article, members of the Facebook technology team discussed 'the"people-based" marketing opportunity.' The idea being that Facebook is scaling targeting resolution across the entire internet. In an environment with this level of complexity, everybody needs to be talking to everyone else so that there are enough 'conversations' being had. A single 'conversation' only tells you price. A conference call tells you value. Would you rather be a buyer and know the price of something or what it was worth?

What if publisher Somethingsnappy.com decides that they want more money. The Somethingsnappy.com management team undertakes to monetizing their platform by buying bot traffic and other such shenanigans. Over time, as the buyers of Somethingsnappy.com media realize that there are problems, they start to pull media buys and reduce the demand in the market. In a "conference call" market the change in demand is seen as fewer buy orders and lower bid prices on the order book. This process sends a very important signal to Somethingsnappy.com buyers who are still in the market, something may be wrong with Somethingsnappy.com inventory; the price is dropping. This kind of value can only come from  "conference call" market innovations. The "conference call" identifies poor value faster. But, this is a fair market, so the pendulum swings both ways.  If Somethingsnappy.com's media performs really well, outstanding in fact, then more bids and or higher bids will creep into the market. The "conference" call identifies better value faster too.

In a second price auction, only the winner knows when demand is dropping, and they only know it if it happens at the second price. That is a pretty blunt instrument for measuring broad demand.

If powered to do so, a network can be its own built-in policing mechanism. The price of an item in the market is a reflection of demand. In a "conference call" market you know something is good because it sells for a premium. The price is the voice of the market and the collective expression of the members of the network. Quality in the market is much easier to identify. Intrinsic policing is just one of the many benefits of the "conference call" market.

While that is all true, there is one caveat. Price, or any other signal from the market is the result of data, lots of data. This is where the network actually is. It is not the pipes, because the members of the market act through the pipe, the activity of buyers and sellers is what  flows through those pipes. It is the information communicated across the network, not the network itself. The market is our understanding of historical price information and the representations of future supply and demand. Together this data forms our view of the market. This is where the next wave of ad tech innovation will take place. There are a few companies in this space, but I'm not sure that even they know that they are in this space...

Creating New Media Markets

What is at the edge of a market

If something has never been traded before, how do you start trading it? How do people go from not selling something to becoming buyers and a sellers. That is where the edge of the market is. The place where each side has something they are willing to exchange. When people decide they would rather own a product than own a $20 bill, buyers are created. When people decide they would rather have someone else's $20 than the product they own, sellers are created.

That means the buyer gave $20 and got at least that much value and that the seller believes this is probably the most they can get for this product. How do you encourage people to understand that there is value in the market that is up for grabs?

Show it to them. Teach them how to grab it.

Let's try a real world example. Meet Alice, Alice loves to bake. She makes lots of cakes and all her friends love them. In fact, like any good friend who recognizes a good thing, Alice is told by her friends "you could totally sell these, they're awesome." So, Alice starts trying to sell her cakes. Did you see what just happened there? Alice's friend showed her that there is demand for the product she is making  - "you could totally sell these." Alice's friend showed it to her and taught her to grab it. If Alice would rather have more money than the cost of the brownie she just baked, we have a market.

The Implications for media

Now that we have that behind us, let's talk shop. What does that mean in terms of trading advertising? Well, every buyer in the attention markets industry would love to buy audiences at scale from publishing partners. They do, through private markets, but at what scale? Are private market deals searchable across the market? No. Is there pricing and market data? No. So basically, real-time markets don't consider the future in how they price. Supply and demand only exist in the present. A bid you see in one auction has no influence on a bid in a different impression's auction, now or in the future. Did you see what just happened there? I showed that there is demand for a product, future impressions, that does not have a reservoir of buy and sell orders.

Buyers would much rather have a market where they can freely and continuously manage their flow of capital. Sellers would love to allocate guarantees quickly and dynamically. Private marketplace deals take some time to put together, they require a commitment from both sides, are a small universe onto themselves, and provide no way to understand pricing throughout the market. If I don't like how my money or assets are put to work, how long does it take to fix that? how much work does it take? Electronic markets are designed so that it takes minutes or seconds to manage transactions.

If you can find value, a market participant has media that they are willing to sell at some price and a media buyer willing to buy at that price, you have crossed the edge and entered the market. In media, there are a lot of buyers and sellers on the edge making deals and trading media. What does not exist for reserved and guaranteed media is an exchange, a reservoir of buy and sell orders.

What is past the edge of the market

Sure, there is programmatic direct, but that is like needing to have a separate phone line for every person you call. Programmatic direct systems can only support two-way conversations. Transactions do not represent the outcome of many overlapping supply and demand interactions. Programmatic direct provides a platform for a specific form of communication: "Hey, I want to buy/sell your stuff?" What buyers and sellers really need is a much more complex web that stretches across the edges of the market. It is not about the buyer telling the seller or vice versa, that is a two-way conversation. It is about the buyer or seller telling the market that they have supply or demand and letting the market find the other side for them: "Hey, does someone want to buy/sell this stuff?"

They way a market is designed makes all the difference when it comes to finding buyers for sellers and sellers for buyers. In illiquid markets, buyers and sellers find each other one by one. In liquid markets, supply is matched to demand by the market itself, the exchange.

Where Is The Sabre Systems For Media

If you have been around the media and advertising industry for more than a few months, you have probably heard people throw around the name Sabre Systems.  Why do so many people in the industry throw this name around? What does it actually mean?

Like most non-media terms bantered around our industry, most people who refer to Sabre Systems, really have little understanding of what Sabre actually is or does. Understanding the value of such a system in media is really important to a full understanding of the challenges facing media buyers and sellers. So, lets start with the problem Sabre was designed to solve. As Wikipedia defined it "In the 1950s, American Airlines was facing a serious challenge in its ability to quickly handle airline reservations in an era that witnessed high growth in passenger volumes in the airline industry. Before the introduction of SABRE, the airline's system for booking flights was entirely manual."  Sounds awfully familiar. Sounds like the reason every programmatic direct technology has for their existance.

For a quick review of the players, we have Twixt (Appnexus), 49BC (Rubicon), Yieldex Direct, Adslot, iSocket (acquired by Rubicon), and Shiney Ads (also acquired by Rubicon), PubDirect (PubMatic), and Mediaocean's Prisma.

In reality, the value of the automation Sabre provided was to overcome the issues of scaling the airlines booking workforce. There were simply too many flights, too many seats, and too many queries to manage with a people-based system. Now let's think about that in the context of direct media sales. How many media companies have you heard complain about lost revenue opportunities associated with the inability to handle the number of direct deals? Is direct sales experiencing 'high growth' like the airlines of the 1950s? The answers to those two questions are: exactly zero and no, in that order. While the efficiency of having less paperwork, emails, and calls to deal with in booking media is important, it adds very little value. Sabre was created because automating the ticket buying process for airlines in the 1950s was critical to enabling them to drive significant growth.

So how does Sabre actually create value? This is how Sabre describes itself today "...through improved forecasting and decision support. This includes a hybrid pricing environment that looks at real-time data from across the enterprise as well as external sources. This provides the most accurate information on customer choice-based forecasting, network revenue optimization, competitor pricing data and configurable business rules automation." Does that sound like anything that any of the above companies do? No, no, and no. None of the current programmatic direct systems actually solve for any of these problems.

For a bit more depth on that, "Improved forecasting accuracy and overbooking optimization with advanced modeling at the segment and fare class level... The forecasts provided include spill estimation and time-based as well as event-based seasonality adjustments. According to forecasted demand, the system overbooks and sets authorization levels higher than capacity by compensating for customer cancellations and no-shows."

Today's media companies face a very different set of problems than the slowness of excel, phones, and faxes. Yes, it is labor intensive. But, that's like saying that the limiting factor in the growth of human construction was the labor intensive work of the stone mason. Yes, cutting stone by hand is very slow and inefficient, but what changed our society was not the electric chisel, but concrete. Even if we have robots cutting stone, building with stone is simply not a scalable method. Building with concrete is. Media sales faces the same problem. The old process simply is not scalable. The current batch of programmatic direct solutions may enable publishers to do it cheaper and faster (stone cutting robots), but no one is claiming to help them do it better and drive more revenue (concrete).

What Are Attention Markets

Let's start with a challenge. Think about 'programmatic'... now stop. The term  is no longer a good description of what is going on in our industry. We challenge you to stop using that word to describe the industry. It's inaccurate and confusing. It's holding back the entire industry by misrepresenting the value propositions of advertising and marketing technologies. The word programmatic is defined as "of, relating to, resembling, or having a program." It means automation. Now, let me ask a simple question, is anyone using real-time bidding doing it primarily for reasons of automation? We would argue that not a single one does.  Automation  is probably last on a list of reasons that includes targeting, impression level decisions, and market driven prices. In today's advertising markets automation is not the cause, it is the effect. Having a place to buy and sell that reflects the wills and desires of market participants is the end-goal. Why are we collectively naming the industry 'automation'? This industry is about the time and attention people are willing to give to a message, it is about understanding economic decisions people need to make and providing them with suggestions.

In reality, something very real is traded in these markets. Its actually not even really media. In the end, it is all about what the advertising stands for. It stands for the time an attention of people you want to reach, that's it. Its about getting your message in front of people. It's about attention. Real-time bidding (also a poorly conceived name), programmatic direct, video, the nascent TV markets, and everything else from digital out-of-home to audio ads, are all members of the larger Attention Markets ecosystem.

Attention markets are what all the significant buyers want and, in many ways, it is also what the sellers want. If both sides can easily understand the value of an advertising opportunity, now and in the future, it is much easier to figure out what the 'markets' think things are worth. The markets are simply the entire collection of all buy orders and sell orders. This is where people's attention is bought and sold. We've all heard the adage "if  you're not paying, you're the product.' Well, these are the exact 'products' that are being traded in Attention Markets.

An impression is a unit of attention, a view is a unit of attention, a click is a unit of attention, and action is a unit of attention, even reach is a unit of attention. In market terms real-time bidding is a spot market, cash and carry. The larger environment is a broader fabric of technology to transact attention assets. Not all are automated.

There is a great report from McKinsey&Company (download link) that helps to put this in perspective. In short, McKinsey & Company estimate that the entire advertising industry is about $1.5 Trillion (with a T) dollars global. That's one and a half million millions! That's 2% of global GDP! And we don't trade this stuff in a market like all the other major parts of our economy? Yep.

So what does all that mean to you right now? Well, buckle your seat belt, the next decade may be the largest technology gold rush since the rise of social media. Let's add a little more perspective, all global oil production in 2013 was $3 Trillion according to research from BP. The entire global oil market is only twice the size of advertising. Stop and think about that for a moment.