There’s no doubt that TV media planning, buying and measurement will be disrupted by the smart application of technology and data. There is a clear opportunity, given that $70 billion-plus is being managed largely by people with spreadsheets.
But unfortunately, programmatic TV in its current form isn’t a big enough step forward. While it might generate some revenue for investors, it’s hard to imagine the category achieving the rapid growth and media market share that was anticipated.
Today’s programmatic TV focuses on a combination of advanced targeting and buying automation. In the digital realm, these were two large problems. When you have a bottomless swamp of inventory from a mind-boggling number of sources, targeting and buying automation make a lot of sense. The result was more immediate, rapid scale for programmatic digital platforms.
The problem with applying the digital model to TV is that the value of attaching advanced targeting to automated buying is relatively low. Because there are a limited number of sources for TV inventory and since targeting is indexed versus one-to-one, there is no critical need to combine the two in an automated fashion.
This is proven out by the fact that brands and agencies are taking advantage of advanced targeting by simply working with third parties that have access to both viewing and consumer data to make smarter targeting decisions. This targeting can then be applied to current buying methods, which are far less cumbersome than they used to be with digital.
If the programmatic TV ad tech industry continues to pursue advanced targeting as the primary value-add, it will also experience a rapid increase in competition from Experian, Acxiom, SambaTV and many others that deliver the same or similar targeting services. MVPDs and networks are also in the mix, including addressable TV from AT&T and the newer audience-guarantee offerings from NBCUniversal. Access to advanced targeting data sets is getting easier and easier and the pitches are now falling out of the sky.
What’s interesting is that advanced targeting does belong in a centralized, more automated solution to enable application across all programming – not just one network or addressable platform – using a single, validated data set. Programmatic TV with advanced targeting should be used for a brand’s entire TV buy, not just as something to “test.”
This isn’t happening because programmatic TV is not solving a big enough set of problems. While targeting in and of itself is certainly important, it’s just one piece of the media puzzle. There are even some programmatic TV offerings that deliver a black box of inventory or have no pricing transparency. If you want to limit scale, that’s a perfect recipe.
The advancement of programmatic TV will require taking new steps back to consider the largest problems that brands need to solve. The highest-order problem, of course, is connecting media investment to revenue and market share. This problem is being tackled by an adjacent set of companies focused on channel attribution and optimization, such as VisualIQ and Convertro.
There are also companies, such as Tapad and VideoAmp, focused on delivering device graphs that promise to link devices within a household so that an impression viewed on one device, such as a connected TV, can be linked to an action performed by another device, such as a mobile phone.
The problem with these analytics and device-graph solutions is that they are necessarily black boxes of data, so you must somehow gain a high degree of confidence in the IP to make big media moves based on results. Strong validation of these solutions is still pending, but you can believe that they will get better and better over time.
These are just some of the examples of how programmatic TV can evolve into a larger, more encompassing solution that solves bigger problems and achieves more rapid scale. The problems are out there to solve and there is no lack of point solutions that appear promising – at least in their PowerPoint presentations.
The winners will be those who tackle the biggest problems and create a cohesive solution that better justifies moving more of the $70 billion-plus toward more automated solutions.