Rethinking Media Types in the Age of Advanced Digital, Part 1
Part 1: Is it time for a new “Media Type” paradigm?
In this first part of the series Rethinking Media Types in the Age of Advanced Digital, we examine the role of programmatic in muddying our industry standards and processes and explore the possibilities of "Media Activation Vectors" as a model to streamline media buying workflows and drive innovation in ad technology.
Posted by Michael Stoeckel on August 12, 2024
Recently, after spending some years in the trenches of media tech—following many previous years spent on the client-side, surviving very related constraints at my first ad agency job—I realized that how our clients think about “media types” matters. A lot. But then I asked myself, is it the way clients think about media types, or is it the way legacy technology and processes have pushed them to think about media?
“We can finally tear down the barriers to innovation that stale, out-of-date technologies and processes have helped keep erected. When it is time to try a new type of media, ad format, or platform, our new standard model will help us innovate, not stand in the way.”
As we often explore in our regular In the Mix industry insights series, the pace of evolution in media buying is only accelerating, and a new paradigm for managing what we’ve always referred to as “media types” is required for ad technology to properly evolve with it.
But why does it matter? What is really at stake?
Suppose we can accurately model all media with an industry-wide consistent schema. Then, we will be able to change the paradigm from one of “boxed-in”, limited workflows to a new, “channel-less” approach to buying, planning, billing, and paying.
In short: We can finally tear down the barriers to innovation that stale, out-of-date technologies and processes have helped keep erected. When it is time to try a new type of media, ad format, or platform, our new standard model will help us innovate, not stand in the way.
So, with that in mind, here’s how I’m thinking about media types lately. I would love your reactions.
How my quest began: Is Programmatic a “Media Type”?
I started thinking deeply about the media type paradigm during a recent forecasting exercise when a colleague and I were trying to determine the typical spread between Digital Direct and Programmatic ad spend.
Utilizing recent and very trusted industry research, others in our organization pegged Programmatic at greater than 90%. My initial reaction was most certainly, “What?! Has the market changed so drastically in just a few years?” Because to tell the truth, there was a time not (too) long ago that I remember high-fiving my small team of supply-side platform (SSP) optimization ninjas when we finally managed to sell 20% in programmatic at a very well-respected publisher with over 100 years in the ad sales game.
I’ve since dived deeper into industry ad spend research. I started with a simple question: What do we mean when we refer to media as “programmatic”? Revisiting the IAB’s widely accepted Glossary of Terminology, the term refers to “media or ad buying that uses technology to automate and optimize, in real-time, the ad buying process.”
A lack of standards & consistency
“At the end of the day, naming convention hacks are never an effective strategy for running—or optimizing—a business.”
However, in my review of eMarketer's Programmatic Ad Spending Forecast H1 2024, among several other sources, something else became apparent. Though it may not be news to many of you, I realized that the inconsistent way we as an industry refer to “programmatic”—and how we often miscategorize it as a media type or even a platform—is at the root of a great deal of confusion across our ecosystem.
Again, but why does it matter what we call it? Without clearer distinctions, we end up with a set of “frankensteined” media types that are nearly impossible to properly manage, apply best practices to, and report on.
For example, programmatic is now a primary means of buying National CTV. Still, it isn’t uncommon for buyers and planners working within legacy media management systems to resort to creating several “sub-media types” to manage their programmatically bought National CTV buys. One team might categorize these as National TV - CTV - Programmatic, while another labels them as Programmatic - National TV - CTV. The former would be used for their National TV buyers, while the latter would be applied to buys from a Digital team. What an overlapping mess, especially when it is time to measure, report, optimize, and reconcile those buys. At the end of the day, naming convention hacks are never an effective strategy for running—or optimizing—a business.
What is a “Media Type” anyway?
Still, for the sake of our argument, taking yet another step back to define what we mean we say “media type” also feels necessary to push forward.
Fig. 1
Let’s start with our own company, Hudson MX. Figure 1 shows the primary “media types” defined in our software, the MX Platform.
Still, this list is not exhaustive. Unlike most competitors, we allow users the flexibility to customize these to meet their needs and allow for dozens, if not hundreds, of sub-media types. But, for now, let’s consider the list a very typical starting point.
When we try to hold these “types” up to a consistent standard, it might feel impossible to do so. Instead, we’re left with both apples and oranges here.
Though some will disagree, I’d like to start with a purist’s definition of the Media Type, which refers to how the media is consumed, not how the ad is bought or delivered. Thus, a video ad creative running in a banner on a standard webpage would be a video-rich media execution but not a video Media Type.
Have you or anyone you know ever consumed the media format “programmatic”? If so, please tell me about that experience because I never have. I could argue that I have viewed Search, Social, Print, and many of the other “Media Types” above in the literal sense, but not programmatic, because it is not a media type.
How did we get to this awkward list, then? It is primarily due to incumbent technologies holding on to the inflexible status quo. More on that later.
A modern alternative: Media activation vectors
Just like database normalization establishes information integrity and eliminates redundancies with any data source, further defining media types by the attributes of a media buy has a real benefit. Doing so gives us the foundation necessary to accommodate new media paradigms, or “waves,” without overhauling your operational tools and processes while avoiding some of the unscalable workarounds mentioned earlier.
It’s time to break down what we consider "Media Types" into several standardized attributes. Looking at the default list of media types we provide our users, it is clear that each media type’s genesis was primarily based on the evolution of each specialized area’s ad-buying teams, followed by ad sales teams built to mirror their buyers. Varying naming conventions were developed through this evolution. While they aren’t always consistent, I suspect that once normalized, very consistent workflows, at least at a high level, can be found between all media type categories.
However, to test this hypothesis, we must first identify, define, and categorize these proposed non-media types, such as Programmatic and Direct Response.
Let’s define “Direct” and “Programmatic” advertising as opposites, with “Direct” being the traditional, (significantly) non-automated means of selling and buying advertising. This will be the first vector or attribute I will apply to any valid media type. We’ll call these vector options “Acquisition Methods.” I will also assign to it only two possible values: Direct or Programmatic.
To identify other vectors, let's next look at the primary flavors of Programmatic. When people read or hear about “Programmatic,” they most immediately focus on the “Wild West” auctions, which can include tens of thousands of ad buyers bidding on inventory supplied by tens of thousands of ad sellers. Such auctions are the root of the majority of Programmatic pitfalls. These “many-to-many (M:N)” executions, though, represent only one way to transact programmatically, so let’s look at a fuller set:
Open Market (M:N)
Private Marketplace (1:N - one buyer invites multiple sellers to bid or vice-versa)
Preferred Deal (1:1 - sorry if this is primarily a Google term, and recommended substitutes are welcome)
Automated Guaranteed (1:1, and, as per my definitions above, NEVER call it “Programmatic Direct”)
Unlike other attributes that we will identify, “Buyer-Seller ratio” is only applicable to Programmatic as, even if a similar ad product is offered to several buyers, Direct sales are ultimately closed between a single selling entity and a single buying entity even if the latter simultaneously represents several advertisers or clients.
How do we distinguish between the two “1:1” Programmatic executions, Automated Guaranteed and Preferred Deals? Unlike the other Programmatic flavors that involve bidding, they both include “Fixed Pricing,” so the Pricing Method is not the key. Automated Guaranteed is typically sold at a higher unit price than Preferred Deals for the same content and audiences. However, that is inherent in the name: the inventory purchased is “Guaranteed” versus “Preemptible” for Preferred Deals. Note, though, that the Preemptible “Inventory Security” option existed long before Programmatic advertising emerged (again, see “DR”).
A proposed new Media Activation Vector model
Using our newly defined vectors, let’s try to remap some of our users’ most commonly used media types, as shown in Figure 2.
Please note that this list represents the “predominant” executions of these Media Types but is not “exhaustive.” However, a less-than-perfect model is better than an outdated one. By breaking this up into several components, I believe that we can also handle edge cases, see Figure 3.
What do you think about the proposed Media Activation Vector model?
At the end of the day, this exercise is about tackling standards. Without standards, it will be grueling to implement and scale as our industry continues to evolve and innovate, and it will be even harder to optimize the technologies and processes behind those innovators.
This is why, here at Hudson MX, we continue to examine how to optimize our software to accommodate continuous growth, from new paradigms and vectors to reporting and other internal processes.
In the meantime, what are your thoughts on the need for a new industry-wide vector model? How can it solve problems where you sit? In Part 2, of this series, I’ll put the vector model to the test and optimize it. Subscribe to catch up and continue exploring this with me.
Next Up
If you’re as excited as I am about this exploration of future media models, check out Part 2 of this series, where we explore ways to test and optimize a new model.
About the Author
Michael Stoeckel
Head of Platform Partnerships, Hudson MX
Michael is a digital advertising executive with diversified business and technology skills at the intersection of media, mathematics, and organizational leadership. With a strong reputation for navigating diverse stakeholder needs and mobilizing resources, Michael has over 3 decades of experience effectively partnering with technology, marketing, and sales teams to drive innovation in disruptive industries. Michael lives on the Jersey Shore with his wife and daughter. He enjoys sports activities like golf, softball, bicycle riding, body surfing, attending athletic and music events, and traveling with friends and family. Connect with Michael here.
