• by Charlene Weisler , Op-Ed Contributor, July 15, 2021

I have known media veteran and consultant Jeff Boehme from our days at NBC in the 1980s. Since then, he has had a varied and interesting career path.  A veteran of local broadcast rep firms, NBC, ABC, NCC Media, Nielsen, Kantar Media, Rentrak and Comscore, he concentrated on audience evaluations and processes for media currency acceptability.

Charlene Weisler:  What role should data play in media today?

Jeff Boehme: Data always played a critical role in media. Content is now distributed on more types of technology than ever. Virtually all of these digital devices collect usage information and have been enabled in the marketplace by a multitude of companies.

Brand marketers realize the potential of reaching customers with far greater efficiency and effectiveness through addressable advertising across multiple platforms and content.

But defining the benefits of efficiency and effectiveness is not a standardized process; there are real issues surrounding the massive data sets collected from these digital devices and becoming ubiquitous as media currency. Ultimately data can and should be leveraged to maximize the effectiveness of the three basic pillars of brand advertising: creating awareness, reinforcing equity and driving purchases.

Weisler: What types of data are most important? What is currently missing?

Boehme: Over five years ago we understood the remarkable advantages of ‘big data’ expressed as the three Vs: volume, velocity, and variety. The sheer scale of anonymous, passively collected user information provides much more statistically sound results than traditional small panels and surveys.

However, most every big data set is incomplete and may not include essential data elements required for currency acceptance, making traditional tools still necessary to supply missing data points. I would add there should be a few more Vs to consider – the validation of the data (how accurate it is) and the ultimate V – its value. The value of the data ultimately answers the questions posed by the brand and can be accepted as currency on all sides of the ecosystem with confidence.

The good news is we now have more data than ever before. The bad news is that there are significant inconsistencies with the sources, collection techniques, methodology, standards, transparency and importantly – conclusions. All major cable MSOs are offering their tuning data to a variety of companies, as are virtually all connected TV (CTV) manufacturers. I have seen significant disparities on results depending on whom and how a company processes, manages, applies statistical corrections and matches census segments.

Weisler: Should age and gender still form the basis of currency?

Boehme: It really wasn’t until 1987 when Nielsen launched their people meter service that age/gender metrics became the de facto currency. However, many brand marketers learned that age/gender weren’t enough to efficiently plan or buy media – specifically for high spending categories such as automobiles. Most consumer purchaser data sets available today are household-specific and include information more relevant than just age/gender. Knowing that a household has pending lease expiration for a BMW is more valuable than simply counting adults 25-54.

Weisler: What do you think of the general state of attribution?

Boehme: Channeling Sergio Leone’s epic masterpiece western film “The Good, the Bad and the Ugly”:  The good is, we now have a plethora of consumer-based intelligence and media companies able to use attribution techniques to see a finer view of the customers’ behavior across screens and determine what components of media campaigns work (or don’t).

The bad is the complexity of data, multiple data sources, missing data points/deprecation and differing methodologies.

The ugly is, there doesn’t appear to any consistent standards – resulting in significant outcome discrepancies.

Last year, CIMM completed a study on attribution which found the inconsistency of key television attribution inputs, not technology, is the main cause of variance in outcome measurements. They compared eleven different providers and determined, “more stringent media measurement standards are required to ensure attribution results that are consistent and comparable from provider to provider, with exposure data, more than occurrence data having the biggest impact on outcome results.” 

I agree with their findings and with their report’s other recommendation requiring additional standardization, such as commercial IDs similar to Ad-ID, for identifying ad occurrences and in defining exposure and reach.

Weisler: What do you think is the most important issue facing research at this time?

Boehme: Most research groups are a cost entry on a ledger, requiring investment without a direct responsibility for cash flow. Many successful researchers have learned to move quickly, adopt better data skill sets and provide actionable input into a sales process and discover how their company can be more profitable.

Many companies see data scientists as a replacement for the research process, but smart companies see the value of both, with complementary skill sets and valuable disciplines. The simplest distinction may be that the data scientist determines what could be accomplished with data, and the researcher helps define what should be done with the data.