News & Insight

January 5th, 2017

Podcast: Nate Woodman Speaks with AdExchanger about Proprietary Machine-Learning Models

According to Nate Woodman, GM of demand solutions at IPONWEB, the deployment of brand data in the media-buying arena is at an early stage. His pet thesis: Now that CRM activation in programmatic is common, the next challenge will be the development of proprietary machine-learning models that are owned and controlled by brands.

“Most CRM data is activated through a DSP,” Woodman says in this latest episode of AdExchanger Talks. “That supports a segmentation strategy, but to drive real performance out of a system requires a machine-learning model, which can hit performance targets in a vastly superior way to segment-based buying.”

A tiny club of big marketers, such as Netflix, have initiatives in place today around proprietary algorithmic IP. And other performance-focused verticals like banks may be positioned to do so. But it’s a steep climb.

“The challenge to the industry, and it’s a daunting one, is to find a way to spread proprietary algorithms across programmatic platforms,” Woodman said. “Most brands aren’t even close to realizing this vision, but some are making overtures in the direction of proprietary machine-learning models.”

He added, “I don’t know that it’s going to go there, but it’s a vision.”

Also in this episode: Woodman talks about IPONWEB’s unique place in ad tech history, its current strategy and the evolution of the agency trading desk model.

Click here to view the original article on AdExchanger