written by Rémi Lemonnier, co-founder at Scibids. for AdExchanger

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Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Machine learning (ML) is a very trendy term, raising huge expectations on one end and creating fantastic fears on the other.

Even if there is a lot of “ML-washing” among the ad tech industry, there is no doubt that it is and will continue reshaping the digital advertising ecosystem. A recent ​Juniper Research study predicted machine-learning algorithms would generate some $42 billion in annual ad spend by 2021, up from an estimated $3.5 billion in 2016.

Following the steps of quantitative finance, real-time bidding is transitioning from a manual data analysis domain to a purely mathematical one. I am not referring to single cost-per-click or cost-per-action optimization at the campaign level, but holistic solutions that will take into account multiple KPIs and media plan constraints for a given advertiser >>> READ MORE