If you thought that programmatic made advertising smart, wait until you see what machine learning (ML) can do. Despite the hype, there should be no mystique – machine learning algorithms simply suck up historical data to find patterns that can inform future decisions. Applied to advertising, that means code can use historical conversion patterns to find the best inventory or audience for a campaign – and continually re-optimise those choices, mid-flight, for a huge effectiveness bump.
But machine learning’s complexity can double-down when buyers are faced with selecting and implementing the technology. ML effectiveness got refined last year thanks to training on big datasets. But kicking the tyres of algorithms that, by necessity, could operate a million different ways can bamboozle buyers, whilst some advertisers may need to go beyond off-the-shelf solutions – necessitating they appraise themselves of how data science fundamentals can apply to their business.