A Machine-Learning DSP Built from the Ground Up

Introducing the AppNexus Programmable Platform

AppNexus has long been vocal about the pressing need for change in the digital advertising space: the need to clean up the digital supply chain, the need to surmount the limitations of campaign targeting on the open internet and the imperative to guarantee viewability (and enable buying on views) outside of the walled gardens of Facebook and Google.

And because AppNexus is, at its core, a team of smart, passionate people building tools to transform digital advertising on the open internet, rather than just writing or speaking about these problems, we set out to fix them.

At AppNexus’ New York Summit in early November, we announced the fruits of our labor, our new DSP, the AppNexus Programmable Platform or APP.

Rethinking the DSP

Let’s take a step back.

Four years ago, AppNexus looked at our legacy DSP, Console for Buyers, and said, “We keep trying to build more and more machine learning on top of this existing platform. And every time we add more functionality, the UI becomes more complicated.”

Indeed, advertisers and traders who use our product told us that we have one of the most complicated UIs in the industry because we have added so many features. Instead of simplifying programmatic, we had made it more complex. It was precisely the wrong outcome.

So, we thought, instead of adding machine learning algorithms to this platform that wasn’t built for it, what if we flip the paradigm? What if we started with this machine learning capability, and then built a new DSP around it?

This was a big idea. Personally, I thought it would take a year or two. It ultimately took four years to turn our platform inside-out and launch APP. But it was well worth the time and investment.

Programmability, transparency and brand safety

There are three special elements that distinguish our new DSP:

The first is programmability. APP is powered by machine learning that enables advertisers to express any variable they want with total control. It uses predictive analytics to free traders from tactical tasks that the machine can perform better—tasks like pacing, discovery and ranking— and enables programmatic buyers to spend their time getting closer to strategy.

Second, it is built on the idea of transparency. Our ultimate goal is to share information on every fraction of a penny that we touch so buyers know exactly where their money is going. We aim to guarantee transparency end-to-end throughout the supply chain and make it auditable. We are working with a number of independent ad tech companies and payment providers that leverage block chain technology to do so. As a result, advertisers will be able to follow their money, top to bottom, when using APP.

The third point of differentiation is APP’s radical approach to brand safety. All of the machine learning, anti-fraud and anti-hate-speech work we’ve been driving for years is built into this trading platform. Advertisers need assurance that their campaigns won’t run next to hate speech, graphic violence or pornographic content, and they need further assurance that their programmatic technology partners are protecting them against ad fraud in its many permutations. APP is constructed to deliver on these promises.

This isn’t just a question of technology. It’s also a question of ethics. If you want to place your ads on Breitbart—a publisher that we barred, given its propagation of hate speech—then APP is not for you. Other DSPs will gladly help you out.

We believe that APP delivers powerful machine learning and optimization, transparency and safety. Combined, these attributes deliver world-class outcomes for marketers and brands.

It’s high time to put the power back in the hands of traders so they can innovate and bring unique value to this ecosystem and their clients, something the walled gardens cannot do.