"online advertising is learning to appreciate how the foundational elements of AI have been woven into the fabric of our ad tech industry. To say that focused, advertising machine learning (ML) can answer your random questions about what to make for dinner with the ingredients in your fridge is laughable. By contrast, ad tech machine learning excels in less visual ways, making digital ads perform and monetize better for buyers and sellers."
"In programmatic advertising, savvy players have applied ML at many steps of the ad decisioning process: Routing the right opportunity to the right buyers Reaching the right audience segment Finding the bid price that has the best opportunity to win Various methods for predicting whether the ad will perform, in what contexts, including creative-level performance (spoiler: the more unique data the better here)"
Machine learning (ML) is embedded in programmatic advertising to improve ad performance and monetization by extracting predictive variables from large datasets. ML routes opportunities to appropriate buyers, targets audience segments, determines bid prices with the best chance to win, and predicts ad performance across contexts, including at the creative level where unique data improves accuracy. Exchanges benefit particularly because their levers include price, efficiency, and audience. Marketing language often calls these techniques AI, but the underlying approach is ML. Additional optimization layers remain, with ad format identified as a promising area for further ML application.
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