“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Tom Flanagan, director of strategic partnerships at DataXu.
It has been said that we usually fail not because of the lack of a solution, but because we set out to solve the wrong problem.
By focusing on micro-optimization within each type of advertising investment, rather than macro-optimization across all media allocations, marketers shortchange themselves and their highest-leverage decisions.
Marketers’ recent affinity for technology spending is well-documented, and much of this budget is flowing into programmatic data and media management tools. Logic would suggest that brands are busy acquiring capabilities that move the needle on their very biggest problems – but that is not what I am seeing.
For all the data science and technology being deployed within addressable channels, a lack of rigor persists when it comes to media plan-level allocation decisions. Before deciding how best to target or optimize the display budget, why not determine precisely how much budget should be allocated to display in the first place?
I call this macro-optimization, and it is best delivered by applying causal analytics to marketing data in order to help planners decide how much to invest in each unique market or channel. Marketers need to be guided to the application of data to zoom out to the macro level and make strategic adjustments about, for example, whether to move TV dollars over to digital video, based on the proven effectiveness of each channel for each unique brand.
“Everyone” in the industry may be shifting 10% of their TV dollars over to digital video, but without data to validate the shift, marketers are just following the crowd rather than being strategic.
These are the decisions that drive a brand’s presence in a given environment, and they offer marketing executives a new and powerful lever to achieve their most important objectives.
Allocation planning is ripe for optimization because in most cases it is built on historical precedents, rather than on real-time market data that is current and causal. Indeed, for all the talk of data science and technology within addressable media channels, the lack of data-focused tools in most brands’ media plan-level investment decision-making is apparent.
It’s not an either/or choice, of course. Marketers need to leverage data and analytics to improve marketing investment decisions at all levels. But by stepping over dollars to chase pennies, brands continue to miss opportunities to drive major ROI improvements for their businesses.
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