"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 Ran Ben-Yair, co-founder and CEO at Ubimo.
Transparency has always been a hot-button industry word. In the past year, it’s gained even further currency, often from the heated rhetoric of industry leaders clamoring for more of it. Transparency and accountability have become the two-headed crusade of prominent brand marketers railing against fraud, brand safety, black-box media arbitrage and bloated supply chains.
The focus on transparency may also apply to data. Data transparency refers to marketers’ newfound ability to dive deeper into their collective data sets and retain the resulting knowledge within the organization in contrast to black box practices. It’s a topic that’s a lot less sexy than brand safety or fraud but is equally as important. What binds them together is that the lack of transparency leads to the same unfavorable result: wasteful and inefficient marketing and advertising.
First-party consumer data signals are being amassed at unprecedented levels. Brands can create more accurate and sharply nuanced consumer segments than ever before, because of the proliferation of consumer signals and the emergence of better technology. It is a far cry from the early days of RTB and programmatic advertising, when flimsy audience segments were based primarily on third-party data that often weren’t particularly accurate or up to date.
Despite these improvements, I see much hesitation in the marketplace to invest in in-house data infrastructures, which would enable data transparency. I don’t mean investing in the construction of the technology; I’m referring more to a shift in mindset, whereby the brand takes control and ownership of the data. The primary goal is to retain and build upon as much data as possible within the organization, including CRM, sales, location signals and device data, among other data sources.
What can full data transparency accomplish? Recently, a Fortune 500 marketer told me about an internal research initiative run by a third party. After a year, he was unhappy with the results. Any attempt to change the underlying data or questions in the research would have required going back to square one. Instead, if he had invested in an internal, transparent infrastructure to house and query the data, he could have had the flexibility to adjust his research parameters to produce a more useful result.
Only when brands have this freedom can they truly dig deep and employ even counterintuitive hypotheses to explore, unearth and accrue organizational knowledge in ways they hadn’t previously considered.
The historical primary reliance on black-box practices has to stop. I can’t tell you how many times I’ve seen marketers gain data visibility only to be surprised about glaring inaccuracies, such as significant percentages of audiences identified as both male and female. The litany of concerns also includes control groups defined for foot traffic attribution studies that turn out to be materially different from the exposed audience. Other thorns in marketers’ sides are sequential campaigns started without the ability to use past campaign data.
In contrast, by organizing and housing data in a systematic way and holding partners to a higher level of accountability, brands can begin making headway in achieving data transparency.