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Greg Wasserstrom is a featured contributor to Programmatic Advertising: A Modern Marketer's Definitive Guide report.

Here's the complete contribution:

In the very near future, machine learning will become a core element of all integrated (or holistic) marketing strategies. That technology is already revolutionizing programmatic advertising. In 3-5 years’ time, B2B marketers will expect their marketing platforms to leverage predictive data to drive targeting, personalization, and automatic optimization of practically every kind.

It’s likely that we’ll see another round of explosive growth for programmatic advertising as machine learning, and artificial intelligence will make it even smarter and more effective than it is today.

However, in some platforms, this technology already allows for more insight before ads are programmed, making them better targeted. For example, delivering ads to fit customer engagement strategies at nearly every level, from determining which publishers to target, down to content elements as specific as which colors prospects prefer.

Machine learning provides the ability to learn from the responses to ads, feeding that data back into the algorithm in a closed-loop predictive system. Additionally, machine learning means programmatic advertising delivers better ROI. As the machine ingests more customer engagement data and gets smarter, the algorithm shifts media spending plans to invest more in advertisements that are converting better.

Budgets should be able to automatically adjust to invest in more winning positions and fewer lower-converting areas. Already, programmatic advertising rooted in machine learning allows clients to track which accounts are viewing, clicking on, and converting from a client's advertisements and incorporate that data back into the algorithm.

Programmatic advertising offerings are becoming less one size fits all and better built specifically for the customers they serve. For instance, programmatic advertising for B2B marketers is moving away from a reliance on limited or out-of-date cookies in favor of more inclusive and up-to-date IP targeting. IP targeting can more effectively reach whole groups of stakeholders, serving everyone involved in a buying decision with the most relevant ads.


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