“On TV And Video” is a column exploring opportunities and challenges in programmatic TV and video.
Today’s column is written by Andreas Schroeter, co-founder and chief operating officer at wywy.
Programmatic TV promises the automation of the TV buy and a data-driven approach to TV campaign planning. Using available data, in combination with the more granular automated planning possibilities, will allow advertisers to target the right viewers way beyond the standard gross rating point (GRP) metric used today.
At the same time, users’ TV viewing behavior has changed fundamentally. With the rise of the smartphone, Nielsen reports that 84% of viewers now use their mobile, tablet or laptop in parallel to watching TV. After seeing a product advertised on TV, 37% of viewers in a recent IAB study immediately researched the product, while 31% visited the advertiser’s website. The VAB found that 82% of TV advertisers show a direct correlation between TV advertising and web traffic.
This immediate engagement with TV ads can be measured, be it the number of viewers tweeting the hashtag of the TV ad or visiting the advertiser’s website. Instead of using audience data to determine who might be interested, advertisers can now focus on engagement data of who actually is interested.
Marrying engagement data with the ad airing times allows advertisers to understand which time of day, channel and TV creative offer the highest engagement, and then buy the TV slots with the highest engagement rates.
Smartphones have inspired consumers to act quicker on impulse and influenced the need to get things researched, bought, commented and understood right in the moment, which Google calls micro moments. The TV ad can be one of those moments. Immediate action, such as calling a phone number to order, is not confined to infomercials and the direct response TV industry anymore, as more people instantaneously react by expressing their opinion on social platforms, searching for more information or visiting websites.
Using engagement metrics in combination with the granular automated TV buy, advertisers can define and buy against their own success metrics. For example, advertisers could measure buzz. If advertisers want to create the most buzz around a TV campaign, they can use as their success metric the number of tweets and Facebook posts or comments referring to the TV ads. This concept is similar to the virality aspect of online video advertising. Based on text analysis, it also allows to capture the general mood of the viewers, giving unparalleled insights into how the TV ad is perceived.
Advertisers can also measure interest. If they want to drive interest in their product, advertisers can use the number of relevant search requests and visits to their website as their success metric.
Another potential engagement metric: impact. If advertisers want to drive purchases, they can track the website’s conversions. Although many products are not purchased online, conversions, such as locating a car dealership, come very close to the actual buy.
Even if TV viewers choose not to immediately engage with the TV ad, the smartphone can also serve as the missing link between the TV ad and the actual store visit. Stores have started to set up in-store analytics using various technologies such as Wifi or iBeacon, identifying the customer through the smartphone. Using cross-device targeting technology, it will be possible in the future to tie viewing a TV ad to a store visit and purchase.
So, while more granular audience targeting is the first step in the data-driven programmatic TV buy, the next step will be to measure immediate engagement on top of the audience metrics. The automation part of programmatic TV will ensure that advertisers can continuously optimize their TV buy against their chosen success metric, driving the most engagement with viewers who have a real intent and interest in their product.
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