Marketers need to know as much as possible about their customers, and every granular bit of data is a clue to be stitched together with others in a relentless pursuit of new ideas to drive the business forward. “Data in” is the method by which we construct user profiles from everything we know and “data back in” is the way we look at user engagement across channels to enrich our understanding of users.
A powerful example of “data back in” is the History Channel’s tune-in campaign for Vikings. After debuting in 2013, Vikings was an immediate hit, drawing over six million viewers. Owner of the History Channel, A&E, was eager to leverage the success of the debut, stabilize its viewership base, and most importantly, drive people to tune in on the weeknight when the show aired.
Because Krux could time-stamp every addressable interaction and align that data back to individual users, we detected trends in media performance data that immediately made sense. We noticed a spike in engagement on mobile devices prior to the show airing on Thursday nights.
These were people at home on tablets and mobile phones settling in for “appointment television.” Vikings was a show that viewers wanted to watch live rather than record and watch later, a phenomenon enjoyed only by a few blockbusters such as Game of Thrones and Westworld.
People who had seen at least three website banner ads for Vikings were more likely to engage with mobile tune-in ads on the night of the show. We dubbed this effect the “mobile nudge.” The tactic was simple: focus on people likely to watch Vikings and engage them with display creative all week, building anticipation for the show, then switch to mobile ads to capture people who were at home and remind them when the show was airing.
This simple channel-switching tactic created massive uplift in tune-in for Vikings and helped A&E capture and hold a greater number of Vikings fans. Most critically, it enhanced viewership on the actual air date of the show, increasing ratings.
Without data back in and the insights that the data offers, even seemingly simple addressable tactics are hard to see — and impossible to validate.