It was technology that caused the digital ad supply chain to become cluttered and ineffective – so can technology put it right again?
In the battle to straighten-out the digital ad ecosystem, artificial intelligence is being leveraged to do the volume of work that humans cannot.
In this video interview with Beet.TV, Charlie Archibald, VP, Data Science, MediaMath, explains why AI is essential.
Scale beyond human
Some studies have shown, that for every dollar an advertiser spends, approximately 40 cents of that dollar, or 40% of it, is making its way to the publishers, because you have so many middlemen in there, taking their cut,” Archibald says.
“The challenge here is that, given the complexity of this ecosystem, the number of publishers that you have, the number of supply paths that you have in play, it just becomes a really tall order to ask the buyers and the traders to kind of manually day in, day out, kind of manage that.
“So it really requires an AI or machine learning-based approach to address that properly at scale, in an automated fashion.
“You’re just no longer at a scale where that sort of thing can be done manually solely at the hands of traders or buyers. To do that effectively, you really need to leverage, AI or machine learning based solutions.”
Supply path efficiency
Archibald says AI can be used across a wide range of issues, including supply path optimization, the practice of reducing the number of ad-tech partners in order to gain a shorter connection between buyer and seller.
“You’ll see efficiency gains for the DSP by reducing the number SSPs that they are working with for any given a set of inventory and reducing the load on the bidders,” he says.
“And you’ll see efficiencies for the advertisers too, so that they can figure out which supply path makes the most sense to drive the ROI for their business.”
Archibald says using AI can help alleviate strain on header bidding. That practice has been used to entertain bids from multiple bid sources simultaneously, rather than in sequential fashion, so as to achieve higher yield.
But Archibald says that has led to inventory being re-sold through a multitude of SSps, leading to a big spike in the volume of bid requests.
AI in the Brain
Archibald says MediaMath’s platform is using AI everywhere it can, but chiefly in three ways:
- Automated performance: Automatically optimizing campaigns toward true business outcomes with little human intervention.
- Transparent insights: Making clear how its AI algorithms come to decisions.
- Open AI platform: Optionality for customers to run MediaMath’s AI on their own systems.
Transparent insights go to the heart of MediaMath – or, rather, its Brain. That is the name for its algorithm which determines which inventory to bid on and at what price/
“AI and machine learning can often feel a little bit like a black-box,” Archibald adds.
“MediaMath has become very focused on delivering granular transparency into the decisions that our algorithms make. We offer reporting insights into the decision that our Brain makes.
“That reporting gives our end users insights into what factors are most influential in driving the decisions about how much to bid for a given bid opportunity.”
You are watching “Media In Transition: How AI is Powering Change,” a Beet.TV leadership video series presented by IBM Watson Advertising. For more videos, please visit this page.
