Trade Complexity for Elegance

What are the most compelling ways to measure marketing success?

Over the past 10 years there’s been more energy spent on identifying new ways to measure marketing than there has been over the preceding 90 years. A host of new research firms, software providers, and academic papers aim to help us better understand the value of our marketing efforts. The fragmentation of customer touchpoints has accelerated the number of techniques, while the growth of large-scale data analytics has increased the availability and diversity of information.

The problem, however, is that very little of this work is actually compelling.

Yes, we have bigger, better, and faster analytic models. Yes, we can now do a more effective job estimating ROI. And yes, we have a better sense of which audiences are seeing our work. Yet, what is truly compelling are the methodologies and systems that are intuitive, actionable, and communicate simply. Unfortunately, we see few of these in the marketplace. This holds particularly true in digital media, where the growth of metrics and platforms are driven more by vendor needs to increase market share or margins, rather than by client needs.

So, while it would be easy to focus on attribution vendors and advanced analytics systems, we should turn to what’s most compelling—and for the most part, missing. What’s most needed to compel change is elegance.

To promote the idea of elegance, we should focus on the central questions that marketing analytics are supposed to answer. A former colleague at Nielsen once told me that there are only four questions that really matter in marketing:

  • Who? What are the characteristics of the people the campaign reached?
  • How many? How many people saw it?
  • Did it work? Did the campaign achieve the stated goals to change consumer behavior or perception?
  • Can it be better? How do I improve the campaign results next time?

Over the past decade the industry has done a decent job at advancing the first two questions. In many ways, the ongoing fragmentation of consumer attention has precipitated the need to find solutions that answer basic questions about cross-platform reach, frequency, and demographics. The Nielsens, Adobes, and Googles of the world simply wouldn’t be able to meet the need of their customers if they didn’t provide these solutions.

Unfortunately, the industry has struggled with the last two questions, despite a need in the marketplace. Rather than consolidating around a few core metrics, the broad group of marketing effectiveness and optimization players has gravitated toward black box software solutions or proprietary metrics. They’ve added so much complexity to the process that they’ve eliminated the ability for any of these systems to “compel” change in marketing. In fact, they’ve done quite the opposite; the opacity of their processes has made marketing teams rightfully question every result.

It’s unlikely that a solution to this problem will appear overnight, so we have to use what’s available to fill the gap today. Rather than rely on a single convoluted system, we’ve developed a philosophy of how to use multiple marketing analytics platforms together to maximize the impact on a client’s business:

  • Elegant solutions are more convincing. Use systems that are transparent and methodologies that can be easily explained. Don’t be attracted to complexity because it’s cool or new.
  • Focus on optimization, not impact. It’s tempting to use marketing effectiveness to answer a basic binary question: Did it work? This, however, misses the point. The goal should be continuous improvement and optimization to KPIs. A focus on optimization will improve the client’s business; a focus on impact will only highlight problems without solutions.
  • Evaluate the system. Since no system is perfect, understand what works, as well as its weaknesses. Judge systems on several criteria, including replicable results, speed of data delivery, insight provided, transparency of the methodology, and ease of use. Also critical is the total cost of ownership, including licensing, maintenance, third-party data, and the need for specialized staffing.
  • No single-use systems. If a system can only be used for one specialized function and other multipurpose systems can accomplish the same task, defer to those other systems. It’s a waste of money and resources to have multiple systems that do the same job.

Our philosophy doesn’t solve the problem about the lack of compelling tools. What it does do, however, is provide guidelines that will help marketing analytics professionals do a better job at measuring success. Understanding and measuring consumer engagement with brands are becoming more complicated, but our role as marketing analytics professionals is to make the world a less complicated place. And the first step is striving for elegance and shedding our natural inclination toward complexity.


Jon Gibs, Huge

As VP of Analytics, Jon Gibs guides the development and growth of Huge’s advanced analytics business. Previously, Gibs, who boasts 15 years of industry experience, was the SVP of research and analytics at NBCUniversal. Prior to NBCU, Gibs was the SVP of analytics and insight for the media and advertising analytics team at the Nielson Company. News outlets such as Ad Age, CBS Marketwatch, CNBC, MSNBC, and The New York Times have sought out Gibs’ expertise, and he’s spoken at conferences such as ad:tech, Digital Hollywood, SXSW, and CES. Gibs holds a bachelor’s and a master’s degree—both in geography—from Clark University and SUNY Buffalo, respectively.

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