A number of years ago, the advertising world borrowed the term “trading” from the financial industry and never gave it back. Let’s look at the similarities: both media trades and stock market trades are propelled by technologically driven data. Both appear insufferably complex to the untrained eye. Both evoke similar images of buyers surrounded by multiple screens doing their very best to make optimal decisions in real time. Ironically, the rise of programmatic, or automated, media buying has only increased the complexity of a media buyer’s daily job. With half a decade of experience under our belts it’s safe to say that the approach of media trading has imploded on itself.
Historically, technology vendors executed digital media buying on a fully managed basis. Later, when agencies and brands demanded control and transparency, these same vendors slapped a facelift on their internal software and dubbed it a “self-serve platform”. Unfortunately, these media buying platforms give a false sense of control. Nearly one in ten digital marketers work with more than 30 different programmatic advertising tools on a regular basis, and these tools require users to manually choose their target audience, the price of this audience, and which levers to pull in order to “optimize delivery”. On top of all this, there’s the constant challenge of actually attributing these decisions to increased sales. Ask any media buyer and you will hear universal dissatisfaction with the state of the advertising technology industry. (Just listen to Machine Zone’s CEO.)
So, what should future media buying platforms look like?
In the future platforms will have a different approach to user experience
Everyday citizens use advanced technology hundreds of times a day. We are highly attuned to user experience gaps in social media or banking apps, yet we readily accept deficiencies in B2B software that supposedly helps us do our jobs. In an homage to the early 2000s, complexity is even lauded as “state-of-art”.
We’ve come to expect clunky, rocket-science-like UI. As a result, there are frictions at every step of the user experience and it’s the general consensus that these platforms are lagging behind B2C technologies, as if consumer products are easier to develop. For example, why are there no mobile-friendly media trading platforms? Salesforce and Hubspot pulled it off and it’s hard to believe that they did it only because of deeper pockets than most advertising or media technology companies. The real reason there are so few customer-centric B2B platforms is that there is a general apathy towards B2B design.
The future of media platforms lays in engineering the user experience to meet customer needs first. It’s only a matter of time until someone bursts onto the market whose vision centers around ease of use rather than elaborate features. And that platform will be unstoppable.
The DIY approach in media platforms will disappear
Current advertising and media trading platforms are designed to allow buyers ultimate flexibility. While this sounds like an effective strategy, users run into issues when these platforms inevitably fail to understand the brand’s business model and therefore fail to provide true value. In the attempts to accommodate everyone, they accommodate no one, and audience discovery methods remain primitive at best.
Here’s how audiences are currently targeted within media platforms: a user navigates an a la carte list of predetermined audiences that he/she thinks would fit the brand they are promoting. This brute targeting approach creates a lot of false positive information about top line performance metrics and breeds inefficiencies.
Future platforms will take the guesswork out of audience targeting and bid pricing by being substantially more intelligent in the way they learn about a brand’s audiences. One-size-fits-all algorithms will make way for custom models that are built by machines able to take into account the unique characteristics of any given brand. Technology will remove the heavy lifting of execution so buyers can focus on big picture strategy. Software with the intelligence to truly understands a brand’s customer base through historical data removes the need for today’s “flexible” approach.
Intelligence will also move beyond customer acquisition into integral features such as fraud protection and brand safety. At the moment, fraud prevention on most platforms is activated on-demand. As a result, software that can be used by any party in the value chain can be misused in ways that contributed to $7B in ad fraud in 2016. Future software will have things like fraud prevention and brand safety baked into the platform.
In today’s adtech industry, complexity creates smoke-and-mirrors and flexibility breeds fraud. For these reasons, it is imperative that programmatic platforms become intelligent machine entities that self-teach the individual audience characteristics of each brand, provide remarkable user experience, and are rigid enough to prevent abuse from bad actors.
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