"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 Ocean Fine, senior vice president of sales and demand at Factual.
What if you found out you were paying for your cell phone data plan twice every month but didn’t know it? Well, CMOs may not realize it, but they may be suffering a similar fate when data are “blended” into their campaigns.
For digital advertising campaigns, brands build audiences around consumer personas. Today, that process often means brands start with their own first-party data, then enhance their consumer understanding by layering on third-party data from reputable sources, including mobile location data, purchase data, online behavioral data and consumer attitudinal data, adding it all into a data management platform (DMP) to create target audiences.
Within that scenario, the big problem is disorganization. Marketers, on average, work with 28 technology companies, and brands usually team up with multiple ad agencies, which are often siloed for creative, digital and media buying efforts. Many departments turn to multiple data sources that provide the same data in different forms. When putting together intelligence-based audience segments for ad campaigns, with hundreds of potential data sources to choose from, what goes into finding, say, “Detroit moms who love hockey and buy high heels at the local mall” is often an unwieldy process.
There are too many cooks in the kitchen, independently putting ingredients into the DMP without knowing what’s already in there. As a result, CMOs often end up buying the same intelligence twice or more for the same campaigns because of overlapping data.
The good news is that it is a fixable problem.
To address the duplication, brands and agencies must first take control of their media-buying choices by working more directly with data sources. That means cutting out as many data middlemen as possible. There’s nothing stopping an in-house brand team from getting synced with its data providers and working one to one together. This field is not just currently about digital transformation; it’s also about media transformation and simplifying data operations.
There are myriad reasons why brands need to be more directly in control and knowledgeable about their data. Big brands, with so many different marketing teams, agencies and groups buying media, regularly make thousands of data choices.
It’s messy and one reason CMOs bring programmatic advertising in house, but they shouldn’t stop there. They should work directly with data sources to eliminate wasteful spending.
Empower data for multiple uses
CMOs need to not only work with their CIO and CTO, but they also need to have data activation teams. These teams would bring sanity to fragmented situations and identify overlapping data purchases, test what data works best on campaigns before they run, and turn their organization into a scientific outfit.
Data activation teams can also leverage what they learn far beyond just media buying for ad campaigns by answering questions such as, “Where do we open the next store?” Or, “How can we geoconquest competitors with our branded app?”
A brand’s data activation team can also focus on its increasingly direct relationships with data sources, asking them the tough questions about not only if the data is overlapping but about whether the data is accurate and neutral. Data buying will not just become more streamlined – it will entail more powerful data and, therefore, smarter marketing.
Since the amount of data available is extensive, it’s hard to bring it all together in a meaningful, automated fashion. Such data inefficiency is part of the reason why marketers who understand the power of data-based campaigns sometimes feel stymied. While 98% of marketers agree that personalization advances customer relationships, only 12% of them say they are satisfied with how their advertising performs.
When used to great effect, data’s potential for improving advertising and marketing is bountiful. Big data helps marketers understand customer preferences, how people shop offline and their digital behaviors. While problems persist, marketers are starting to recognize the wasteful nature of today’s data-buying processes. According to a Forrester Consulting study, 37% of marketers said marketing spend is wasted as a result of poor marketing/media data quality.
Whether CMOs know it or not, they are sometimes paying for the same data multiple times. But with a more organized data operation, marketing leads can only pay once, get better data and leverage it for multiple use cases. And most importantly, they can improve their ROI.