disruptive technology

How To Fix Media Asset Standards So They Don't Suck

Standardization can seem like a technical topic but it is simply the domain model (the rules that 'govern' ). In the past standardization seemed difficult because the individuality of media assets created an illusion that a standardized domain model for media assets was impossible.

Some think that applying a standard to media would mean forcing a set of descriptions that everything should fit within. Like the way the IAB created a set of context standards that seek to capture all contexts. But what if the standard is not about restricting what descriptions are acceptable but rather about standardizing the way descriptions themselves are created. In other words, any type of descriptor can be added to a media asset, so long as it is done in a way that the system, can understand. Like Mendeleev’s periodic table, the system has a place for newly discovered elements, even though we never knew they existed.

In Chemistry, 19th century researchers faced the same problem. ‘We have all these elements, but how do we standardize our understanding of their respective relationships?’ To solve this problem in chemistry, a new domain model had to be created to bring rational order. While it may have seemed impossible before the problem was solved, afterwards it seemed completely obvious.  Dmitri Mendeleev solved the problem in 1869. His genius was in building a model that simultaneously defined how the elements are similar to each other and how they are different from each other, in more than one way.

Like Mendeleev, media solutions need to conform to a standard that defines how we order the information in the domain, not limit what information can be contained in the domain. On a side note, some of the marketers making periodic tables of marketing are doing it wrong. They don't actually understand why the periodic table is so brilliant.

Most folks in media that we have talked to question the ability to standardize media assets because they can only imagine domain models based on similarity or difference.  The beauty of Mendeleev’s arrangement is that the relationship between and element and its neighbors to the left and right are always the same. The relationship to the elements above it and below it are also always the same. In other words, the elements are arranged such that they show how they are different from each other by showing how they are like each other. Media standards need the same type of domain model.

Periodic Table trends
Periodic Table trends

To build this domain model we have to understand the relationship between two different media assets (two ‘atoms’) and figure out where they belong in the domain relative to each other (their ‘location’ on the ‘periodic table’).  Most media technology was not build to handle transactions, so it did not need to standardize the domain model for media assets, it standardized the communication of transaction requests, e.g. RTB protocol.  For the exchanges and other technologies that were designed for managing transactions, that part of the system was simply ostriched. Why? Because the second price auction does not need to know what is being auctioned to be successful, it simply manages bids and price floors. This was a design feature, not a bug. Since second price auctions are being used to sell an impression in real time, it doesn’t much matter what the impression is, it only mattered who will pay the highest price.

When we want to trade avails (read media futures) we and the auction itself need to understand what is being bought and sold. Since there is so much uniqueness in the domain, we decided to reverse the perspective. Instead of trying to define what makes one piece of inventory unique, we define how it is different from everything else. We can work by inclusion or exclusion, the results are the same. So in technical terms, each piece of information describing a media asset is a vector. Each media asset is a collection of vectors.

In practical terms the ‘standard’ is a way of ordering the information submitted to the system. This means the system incentivizes conformity without demanding it. For example, there can be two competing methods of defining context, but both buyers and sellers have strong incentives to choose what is best for the market. So, if two competing standardization systems will yield the best outcomes, the domain must support both. If one standard will yield the best outcomes, the domain must support that as well. The standards create an incentive to find the optimal solution, the domain does not define the optimal solution.

Like Mendeleev, media solutions need to conform to a standard that defines how we order the information in the domain, not limit what information can be contained in the domain.

PII issues will never go away with real time bidding

Houston, PII has a problem
Houston, PII has a problem

PII issues have long been a point of discussion among us all.  In all that talking and discussing, we never uncovered the root cause of why PII issues are such a dominant force in the current real time bidding market architecture. I propose that taking another point of view at the problem reveals that it is a direct outcome of the market architecture and not a side-effect of some other economic inefficiency. The current market architecture in real time bidding is a ‘call-and-response’ system. One side, the seller calls, and the other side, the buyer responds. This means that the entire market is dominated by the way sellers define their demand. In simple terms, if no one is selling what I am specifically looking to buy in the market, how do I market my demand?

This means sellers need to express their supply so that buyers will bid. Economics teaches us that in this situation, the seller is best served by providing as much information as possible on this impression, so that the maximum number of potential buyers is achieved. In other words, there is an economic incentive to say as much as possible about the impression.

The problem with this market architecture is that sellers can’t search for buyers before the inventory shows up. If a seller could search for demand and elect to meet some of that demand with their supply, the only information transferred during the transaction is that this audience member and ad placement unit meet the criteria of the buy order. So, if a seller never meets demand that violates PII standards, all transactions will be free of PII issues. In a market structure where demand can be transparent, the incentive is to share as little information as possible. This is the opposite market structure incentive from that of the real time market architecture.

The real time market architecture segregates supply and demand to the ‘call’ side or ‘response’ side, the market self-defines itself as an asymmetric market. For some inventory acquisition strategies like retargeting, this is a great, and most probably the most optimal, market structure. But, for big brands this market asymmetry is bad. We all know that they buy huge swaths of audiences across all media to build their brand. For these buyers, the real size of the transactions ($) they want to make is not accounted for in the second price auction. That auction does not know or care that you have a $25K budget for this line item.

This is a problem. By leaving this demand out of the price calculations we are effectively only looking at the tips of icebergs; and we still have tons of PII issues. If you are a marketer or a publisher navigating your boat through these treacherous waters, no wonder you’re fed up.

The #1 Way To Improve Yield Optimization, Thanks Dr. Laffer

Most yield systems 'think' about a graph of their revenue versus impressions andsee a line going up from left to right. The idea is that every single impression has the opportunity to generate income.

This view can only be true if each additional sellable impression is a real person that gives just as much attention to each new ad impression. With the exception of a microscopic minority, this is impossible. We all know that overloading the user with ads means they actually wind up ignoring all of the ads.

In reality, ethical publishers know full well that jamming your pages full of ads, and playing games and inflating page loads doesn’t last. Increasing supply undermines future pricing power and increases the opportunity for others to arbitrage the publisher.

In part, yield optimization is to blame. The real culprit is the second price auction. It’s baked into that auction method and it can’t be removed.

Let’s take another view. If we apply what we know, we know that the publisher’s revenue curve actually shows that if we keep pumping impression production up artificially, the total revenue we can generate through the market goes down.

Graph 2
Graph 2

So, the real question is what is the minimal amount of impressions that will maximize the publisher’s revenue. The curve illustrates that if there are zero ad impressions, there is no revenue—obviously—to the publisher. But if a publisher had no content and just ads, that won't generate revenue either, as there is no longer any incentive for a person to consume that publisher’s media.

If you’re a bit of a policy nerd like me, that sounds like a theory that came in to legend on a napkin “…officials Dick Cheney and Donald Rumsfeld in 1974 in which he reportedly sketched the curve on a napkin to illustrate his argument[1]” This is the legend of the Laffer Curve, an idea that made a big impact on tax policy throughout the 1980s.

To answer the revenue maximization question above we have to figure out the shape of the curve and how close we are to the top. Sounds simple enough right? Now, let’s think about any technologies in advertising that do that? Is there a yield optimization system that does that?

If you are managing media inventory today, can you tell me what dot on the curve above best represents your organization? If you can’t, your organization is managing the world through the lens of the line graph and not the curve.

[1] https://en.wikipedia.org/wiki/Laffer_curve

The Untapped Potential Of All This Data

Originally Published in AdExchanger We’ve all marveled at the new technology solutions entering the programmatic marketing and advertising ecosystems, along with the vast quantities of data produced. Everywhere a business problem could be quantified, in terms of something that can be counted or measured, a solution has sprung up, specializing in things like behavioral modeling, viewability and attribution.

I believe the untapped potential of all this data is to predict the future. If we took the 100,000-foot view across both marketing technology and advertising technology, we find a very interesting pattern. The land of mar tech and ad tech data is divided in to three main areas, but only one is populated with almost zero technology.

Some technologies can be found in the area I call “The Past.” There are lots of technologies that are in “The Present.” There are hardly any in “The Future” – there are very few forecasting technologies.

I predict the third generation of advanced mar tech and ad tech solutions will focus on telling publishers and marketers what will probably happen in the future. Predicting the future is an exercise of understanding how past data about what happened, when it happened and why it happened can be used as the colors to paint a picture of the future.

The Past: What Happened?

Today’s technology for data capture and storage is like a 100-megapixel camera – it provides a super accurate picture of what happened in the past. We have 100% certainty that what we measured happened. It’s not like there are other possible outcomes in the past.

Data storage solutions provide this vast understanding of anything that we chose to measure. If a data point was created and saved, it can exist forever. The evolution of this area of technology is focused on the expansion of what data is measured and captured. The ever-growing sea of data is a beautiful sight to behold for the analytical among us.

The Present: What’s Happening?

The last massive wave of technology innovation in mar tech and ad tech happened in this category, which focuses on the collecting and disseminating data about the present. The technology that collects data about what the present looks like is less sharp than data about the past. To understand the present, we need to pull a lot of data together really fast so we can act on it.

For data about the past, the effectiveness of analytics that bring data together is not limited by the amount of time that it takes. For that reason, the present is a little less sharp. We don’t have time to look at all the data together.

What’s more, as the sea of data being collected grows, the amount we can actually act on becomes an ever-decreasing portion of what we actually have. It’s more like a 20-megapixel camera.

Technologies that work to understand what is happening and take action include yield management, creative optimization and supply-side platforms. This area of technology is evolving with a focus on the expansion of delivering and processing an ever-growing data set to answer a question in less than a second.

The Future: What’s Going To Happen?

In this category of mar tech and ad tech, the fewest solutions exist. There are no companies on the LUMAscape dedicated to forecasting; I only know of one startup. Forecasting features in current technologies are treated the way municipal politicians treat sewage infrastructure: Nobody wants to talk about it, it’s hard and dirty work, but no one can live without it.

The future will never be as clear as the present or the past, but in this space of mar tech and ad tech technologies, innovation and investment have significantly lagged the market. Predicting the future is hard. It’s never like the past – it’s fuzzy and out of focus. Our current tools for predicting the future are, at best, like a 0.5-megapixel camera. It’s really hard to tell what will happen.

This is where a ton of untapped potential exists. Leveraging all this data being collected everywhere to build better modeling tools will help bring the future into focus. No one can predict when this market shift will gain significant traction, but I think we will see the future as an increasingly important topic of conversation for industry innovation and thought leadership in the next few years.

Picking The Programmatic 3.0 Marketplace That Will Make You A Winner

On today’s cutting edge of media trading "programmatic 3.0" are a number of solutions that allow buyers and sellers to make a deal now for inventory that will be delivered in the future. This new technology segment has emerged, in the already crowded field of programmatic solutions. The challenge for publishers and media buyers has been to distinguish the difference among the approaches vendors are bringing to the table to support programmatic deals for inventory delivered in the future. Because these different approaches all seek to address buyers’ and sellers’ pain points, they all present very similar value propositions. In reality, these approaches are very different.

The three approaches that have emerged in the market so far are the marketplace for traditional avails, real-time statistical arbitrage, and biddable impression futures. If we simply looked at the value propositions of each they seem nearly indistinguishable. If we dig deeper to understand what and how they work, the differences become clearer.

A marketplace for traditional avails

This approach is currently the most common and has been adopted by some of the big players that pioneered the real-time space. This approach allows a seller to expose products from their ad server to a marketplace with a “buy it now” price. It focuses on automating the trafficking of media buys and making the media that was sold direct, since the dawn of digital media, discoverable in a marketplace.  This is the approach used by the likes of Rubicon (iSocket/ShinyAds), AppNexus (Twixt/Yieldex Marketplace), and AdSlot

Real-time statistical arbitrage

In this approach the media is not bought from the publisher, but rather from an intermediary that takes on the risk of promising to sell the inventory at a fixed price after buying the impression at a variable price through an auction.  The approach focuses on technology that can forecast what will probably be available in the real-time environment and its estimated auction clearing price. This approach is used by the likes of Media Gamma and was attempted by MetaMarkets and Media Crossing prior to their pivots.

Biddable impression futures

This approach focuses on allowing buyers and sellers to agree to transact media where all the impressions meet a specified set criteria that can include a publisher’s product, 1st or 3rd party segments, context, viewability, or any other criteria the counterparties agree to. This environment is an order management layer that abstracts supply and demand into a separate technology layer to optimize the way in which supply and demand are presented, priced, and matched. This approach does not handle actual impressions or bid requests the way the real-time environment does. This is our approach at MASS Exchange.

In the wild

Let’s look at a concrete example across all the approaches. A publisher is asked to sell a 300x250 unit on the landing page of their automotive section, targeted at males, 18-35, in-market.

In the marketplace for traditional avails, a publisher must manually create the product in the ad server so that it appears in the marketplace via its API integration into the ad server. While doable, selling targeted impressions, not an audience over-indexed inventory, is possible but the efficiency of the marketplace is quickly outweighed by the massive manual process required to set it up. Further, none of the current marketplaces for traditional avails are auction based. So, it’s like Amazon for traditional avails.

Using the real-time statistical arbitrage approach the vendor targets an audience in an open market or may be able to acquire it through a private market, but the negotiation and pricing of the deal between the vendor and the end buyer is handled manually like any other traditional direct media buy. Further, scaling this approach to buy inventory from specified publishers means that yet another technology is inserted into the cost structure of the media and requires the vendor to have PMP deals with each seller so that a specified publisher’s inventory can be resold.

In the biddable impression futures environment, all of the combinations of audience, placement, and viewability attributes that a seller wishes to expose to the market are discoverable and priced with an asking price. In this environment, avails are biddable and transacted through and auction that only clears if the buyer is willing to pay the seller’s asking price.  This approach scales wonderfully as inventory definitions, pricing, availability, negotiation, and trafficking can all be automated. This approach provides tools that can scale across all the part of the transaction process, from start to finish.

How To Spot The Harbinger That Will Revolutionize Media Trading

Its summer, so like every other year, we make our annual family trip to Copenhagen. Strolling down the beautiful old streets I began wondering if the folks who buy and sell media on a daily basis know that real media trading will probably never include a 3-letter technology in the middle. But, the technology is not the primary barrier to this revolution. The current standard terms of media buying contracts are the biggest obstacle to true media trading.

Trading

Buying media via programmatic direct, a la an Ebay style 'buy it now' tile is not trading. Buying impressions via a bid in an Ebay style auction, is also not trading. If you are not buying and selling the same media your are not trading. Real traders make their money by buying and selling, not procuring or producing. Most of today's media buyers are brokers, not traders. The only folks in our industry who actually do any real trading are maligned and ignored by most technology related media types, the media barter agencies.

Real trading in media will look much more like the old fashion and out-of-vogue barter business. Media barter companies make forward investments into goods and services companies such as printers, hotels and hospitality companies to acquire products or services at below the market rate. These are then traded on a $ for $ basis with media owners enabling the barter company to create a margin on media space. Sometimes the barter firms even 'resell' media inventory the agency no  longer has a use for, but has committed to purchase. Effectively, barter agencies buy promises to deliver media with payment in many forms.

promise
promise

Promises Promises

That being the case, it's time to cut out the messy part of paying for media with airline tickets or cars, for simple promises of cash payments. To do that, we don't need any 3-letter ad tech. The technology for buying and selling promises is very different from the technology to buy impressions. But, the technology to deliver on those promises has been around for over a decade, the 1st and 3rd party ad servers.

When agencies make forward investments in promises to buy media, for which they (and not the advertiser) are on the hook, media trading can become a reality. Today, one of the industries most influential media trade organizations, the IAB, promulgates a standard media contract where agencies are not 'on the hook' - "...Agency will use commercially reasonable efforts to assist Media Company in collecting payment from the Advertiser..."

Real Trading

In order to truly trade, buyers need to be liable for the promises they make and both buyers and sellers need a market mechanism to help determine the price of media 'promises,' based on market conditions.

The first step in accomplishing this goal is to provide for a biddable programmatic direct environment where bids and clearing prices are transparent. A market price can not be truly determined without all market participants understanding what others paid or sold for in the past and what they are willing to pay or sell for in the future.

Real trading can happen when the promise of media delivery is specific enough to drive increased publisher revenues, provide profit opportunity to the trader, and provide better performance to the buyer. If buyers know that they are running their campaigns in a brand safe environment, where real people view their creative, and the expected performance metrics are achieved, they don't really care who the publisher actually is. This is where a trading opportunity exists that creates value for the advertiser, publisher, and the trader, and is a win-win-win.

Real trading only happens when everyone believes that they have a fair shot at winning.

What AdTech Can Learn From Bitcoin

Advertising is undergoing a fundamental rethinking. Over the last decade, a set of radical technologies have ushered in massive waves of transformation in the publishing and advertising businesses. New revenue sources for content creation and opportunities to reach audiences in completely new ways have brought fourth many new technologies. That is where most of the focus has been. Given the technology the media industry has in place today, what would we come up with if we started from a clean slate? We are living through that moment in our industry. We are having a “Facebook” innovation moment because of a “Bitcoin” disruption.

The evolution of technology in advertising is shifting because of a focus on new areas of innovation. The last wave of advertising innovation focused on bringing advertising from the old manual-space into a machine-automated environment. But, the processes that we automated were originally designed to be done by people. Now that a majority of processes originally designed for manual human-driven tasks have been automated, the focus of innovation is about optimizing the system in its current state. It’s like the leap from email to social media. Email is just an electronic letter while social media is a communication innovation that could only exist because we have the internet. The “Facebook” innovation.

The technology space in which advertising operates today is very different than a decade ago. But like advertising, the financial ecosystem has also changed so much in the last decade. Innovation now focuses on things that you simply couldn’t do without computers, as opposed to computers being automaters of human tasks. The new space of innovation is focused on a better understanding of a network of advertising transactions. Now that innovators can examine the network, they are rethinking its fundamental parts. In finance, technologists rethought the entire idea of money. Rethinking fundamental parts of the system is where real innovation is happening today. The “Bitcoin” disruption.

We can draw a parallel to money. Money was originally made of a precious metal, to carry its own value. Then paper money was invented, physical value was uncoupled from the currency. Then checks, physical representations of money. Then credit cards, which are debts that represent future checks. Today, bitcoin. Bitcoin is a purely mathematical representation of money, it uncouples money from the government or country whose currency it represents. There is no such thing as a physical bitcoin, it is not issued by any government or body, and it’s just data. To put that in perspective, Satoshi Nakamoto invented a way to move and store value, Bitcoin, that innovated on the invention of fiat currency in China over a thousand years ago. All that happened because of the technology network underpinning finance.

So what does that mean for advertising technology? It means that we need to start being mindful of rethinking the most fundamental ways in which the business works. Should we be buying impressions? Should we be buying GRP? or should we be buying something else? Now that the industry has so much technology built-in, what can we do now that we simply couldn’t do a decade ago? The answer is the way supply and demand get defined, measured, and are made to meet.

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.