The Buzzword tech is not even on the cards to support media buying.
To help in the forecasting process in media buying, there have been murmurs of the efficacy of AI, owing to its ability to analyze massive amounts of consumer data and campaign content to measure campaign performance. That can help marketers strategize – to redirect budget toward highest performing media options.
One more advantage touted is that of helping marketers diminish their cost-per-acquisition. At the same time, it can help in generating higher-quality leads. By identifying the right match of images, videos, headlines, and calls-to-action in campaign materials, AI helps higher customer converts, theoretically. Besides, over the last year, AI media buying capabilities have grown quite significantly. AI platforms have now started allowing DSP access about a year ago, and hence it can be used for analyzing multiple and disparate campaigns simultaneously.
But there is a big glitch on this horizon- most marketers don’t understand AI well. In a recent survey, almost half the respondents ranked their company’s understanding of AI as a C on a grade scale from A to F. There are other hurdles for AI in media planning that remain. The biggest is skilled resources and the fear that unskilled resources have, of losing out to the tools. But the fear is largely unfounded. Experts know that AI does not work itself, skills will still be needed to define the processes, datasets and many other elements.
Another challenge is that AI still does not have a stable cost structure. It’s difficult to fix the cost because most companies are not even clear on what it can do.
But the biggest challenge of all is the ambiguity and inaccuracy in consumer data- unless it is properly classified and documented, it is not in a fit enough shape to be used for media planning using AI systems. In fact, one industry expert says, even before marketers can think of using AI, they need to ensure that the tools they use to match consumer data are accurate.