Macro Programmatic Vs. Micro: Stepping Over Dollars In The Pursuit Of Pennies

tomflanagan"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.

 Nearly every programmatic RFP I see focuses on micro-optimization functionality, such as display demand-side platform (DSP) targeting and bidding features. I certainly support these channel-specific targeting capabilities and see the value they create for unit-level media performance and efficiency. But is an ever-more-accurately targeted banner ad really going to make or break a brand’s fiscal year? It’s highly unlikely.

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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3 Comments

  1. Rodrigo Palacio

    A great piece, but I think you missed the mark slightly.

    "...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..."

    I think pretty much every marketer with P&L responsibilities does this, probably up-front with management as every marketer has to justify budget allocation. Macro-optimization has it's place in the lifecycle: at the beginning before any dollars have been spent and before any campaign has begun; and again at the end of the campaign - a post mortem - that analyzes what was good, what worked, and what could use improvement. Granted, not every marketer performs a post-mortem, but this is wishful thinking.

    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.

    "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.

    Marketers should already be doing this, no? This sentence boils down to "marketers need to assess their performance in the face of their KPIs and adjust accordingly" Obviously TV works for some marketers more than other; a marketer is probably going to discover this fact quickly on their own.

    Reply
    • I agree with Rodrigo's comments. You're basically describing marketing mix modelling which has been around for decades. Nothing new here.

      Reply
  2. The point here is that we're talking about programmatic now -- and buying every variety of media programmatically, including TV. Media mix modeling has completely changed due to the fact that the mix can now be optimized according to software that didn't exist as recently as last year (and which certainly didn't exist decades ago). The technology has advanced, but marketing strategy has not necessarily followed at the same speed. When marketers talk about programmatic today, the conversations frequently center around ad fraud, viewability, low CPMs and other tactical concerns -- and haven't yet moved on to the incredible potential of full-mix programmatic.

    Reply

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