“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 Gerard Broussard, principal at Pre-Meditated Media.
The transformation of TV from a blast-the-masses medium to a laser beam ad-targeting mechanism seems destined to accelerate over the next couple of years.
More hypertargeted addressable TV inventory is available for sale than at any point in TV’s history, while granular set-top box data is being deployed to smartly reach an increasingly fragmented consumer audience. Advertisers’ purchase of commercial time is now beginning to focus on buying specific audience and consumer behavior segments, rather than the TV program-based approach.
All markers indicate that the industry is ready for change, and now is as good a time as any to prepare for what’s to come. But before the industry can take larger strides toward advanced TV targeting, it needs to take several essential and transformative steps to redefine the television advertising landscape.
It must speak the same language and participate in an incubation phase to brainstorm successful industry approaches, synthesize what the new demographic parameters will look like and then crystallize the outcomes into successful results.
All TV advertising targets experience de-evolution from the time they’re created by marketers to the point when they are deployed to purchase TV ad inventory.
For example, an insurance marketer may characterize a highly profitable customer segment with nine descriptive points, including business ownership, net assets and annual miles driven. The media agency then crafts the media plan using a slimmer version of the profile with syndicated research data. Finally, when TV negotiations begin, the target audience guaranteed by TV networks is reduced to one amorphous group: adults aged 25 to 54.
Now imagine the insurance example repeated for every product and service category and brand advertised on national TV – that’s 9,800 brands, according to Kantar Media Intelligence. Each advertiser may have a slightly nuanced approach to defining their target audience with the expectation that TV networks would have the data and systems to fulfill their description.
Buyers and sellers must be prepared for when the industry begins using effective targeting. The first step will be choosing big data partners, taking into consideration data quality, recency, industry popularity and cost. Every activity beyond this initial data acquisition step will be about managing the sheer volume and complexity of TV transactions, which of course includes the proliferation of targeting descriptors.
TV networks will need to homogenize multiple targets and data sources and tie them back to the pricing of ad inventory. Somehow the networks must create a Rosetta stone of audience segments, a key to mapping a diverse array of targets to conditional pricing rules (Chart B).
Seeds have been planted for the re-evolution of descriptive consumer targeting during the TV commercial transaction process. The explosion of effective targets across thousands of brands will ultimately stymie TV buying and selling without automation to mitigate manual coordination in the more complex transactional environment.
Programmatic platforms made for the TV space are now being introduced to both buyer and seller, and will assume a key role in managing myriad targets and ad placement across networks, dayparts and programs.
While automation is a viable solution for handling the proliferation of target audiences, there will likely be a time of transition when buyer and seller are toggling between manual and programmatic processes. During this period it would make sense to explore ways to properly ramp up for full automation. There are several issues ripe for discussion:
Target audience-naming conventions: The industry must decide on common shorthand for targets names. For example, women aged 25-54 with children can be listed as W 25-54/kids, Women 25-54 with children 2-17, W2554/children and so on.
Number of allowable targets: Buyers and sellers should consider agreeing upon a maximum number of targets during the initial phasing in of effective descriptors. This ceiling would help make for a more manageable transition period.
Personal vs. household targets: There’s a need to make a clear distinction between individual and household consumption in target definitions. Consider adults 25-54 who purchased a tablet vs. adults 25-54 living in homes where tablets were purchased, a situation where the purchase decision-maker could be anyone residing in the home.
Self-reported vs. electronically gathered data: With all the big data mash-ups in progress, it’s critical to understand whether targets are derived from surveys where consumers recall their media habits and purchases or whether the data are gathered electronically.
Representativeness: There needs to be transparency about how well a data source reflects the general population and consumer targets. For example, are loyalty card user profiles sufficient for describing targets or should consumer data from other credit card sources supplement the effort?
Given the swirl of issues, the advertising industry should now begin to lay groundwork that’s in sync with the transition to effective targeting as a TV currency.
Industry organizations, such as the American Association of Advertising Agencies, Association of National Advertisers, Advertising Research Foundation, Cabletelevision Advertising Bureau and the National Association of Broadcasters should form an uber-committee to create guidelines for addressing the targeting issues outlined above.
Taking these steps now will streamline the transition towards automation and, ultimately, result in a needed re-evolution of audience targeting.