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“Without the right data, decisions can often be guesses,” BIA/Kelsey’s executive-in-residence Maribeth Papuga observes in her new report, “Data-Driven Audience Planning and the Local Market Advantage.”

Papuga finds that while (media-oriented) advertisers used to emphasize media environment (e.g., ad placement in a particular TV show), this is being trumped by data-driven placement to automate the process of matching specific ads to audience target segments. In other words, rather than buying media placements with the expectation that the audience will come to that program, advertisers now deliver ads directly to specific audiences using literally thousands of targeting signals far beyond gender and age demographics.

Papuga argues that, “the shift to automated ad technology has made the complex activity of a sale between an advertiser and media channel more effective and efficient while directing spending away from traditional media channels.” Data-driven audience planning uses quantitative and qualitative measures to define, target, and expose advertising to consumers. As media audiences fragment by distributing themselves across more platforms, devices and content it becomes harder for advertisers to match their messages to appropriate segments. Within the online channels the collection mechanism to build a language of audience attributes is referred to as the Data Management Platform (DMP) that serves as a central hub for collecting, integrating, managing and potentially activating large volumes of data.

Papuga is passionate about the relevance of the local market context in how advertisers target audience segments and optimize messaging. And she cautions that not all data is created equally, “Without considering the source of the data, and the context within the market, the long  term value of the data that fuels audience planning may not demonstrate the true value of all consumers.” This really sets up two industry trends. First, we see why the rise of the data scientist is occurring as we need professionals who really understand data sources and can effectively develop analytics to drive the creation of meaningful insights. Second, as Papuga cautions, “it is important to develop universal standards that insure proper representation and enhancement of data across geography as well as platform to enable comparison against both small and large sample aggregations.”

Basically, advertising campaigns will run both on traditional media audience metrics that are typically based on relatively (these days anyway) samples and digital audience metrics with sample sizes often in the millions. So data scientists need to understand and meld both the differences and the enhanced views multiple data sets can provide when developing audience targeting strategies. These are among the issues we’ve highlighted previously in for example our blog post about the “programmatic secret society” that is dedicated to addressing these kinds of issues in programmatic television advertising.

Local markets are microcosms of the U.S. that reveal individual traits that are critical to the foundational insights supporting marketing, media and advertising decisions. There is a tremendous amount of data already accessible and more created daily. Ultimately, Papuga concludes that all these data provide an incredibly powerful window into the local market context and the consumers living in these markets. But the care, feeding and use of disparate data sets must be transparent and compliant with both current and emerging industry standards that need to be developed. Otherwise, going back to the first line of this post, we won’t have “the right data” and we may as well be guessing after all.


BIA/Kelsey is providing this comprehensive white paper to the industry with our compliments as we feel this is such an important area for collaboration. We’d be delighted to hear back from you.

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