Twitter is a veritable gold mine of real-time social data for advertisers, brands, and entertainment studios. The much-vaunted phenomena of the second screen — viewers browsing and posting to social media while watching a TV show or a movie — yields far richer viewer data than old-school Nielsen numbers produced. But as demonstrated by new research released by Twitter, there are many subtleties to how viewers of various shows are communicating on those second screens.
As Tim Carmody details at The Verge, Twitter performed analytics on the viewing and tweeting habits of 10 million active users in the UK. Rather than revealing broad behavior patterns, the research showed that viewer behavior varied widely across shows and demographic segments:
Most of this data is intuitive, but some of it is not, and even contradicts itself. For Downton Abbey, Twitter use fell off during commercial breaks, as viewers changed the channel or shifted attention; for Dynamo: Mission Impossible, tweet volume picked up on breaks. The lesson appears to be that advertising against or during these shows needs to be microtargeted to the specific behavior profiles of their fans. On the plus side, if you’re an advertiser, the data now exists to help you do exactly that.
Such distinctions typify both the challenges and the potential of performing deep analytics on social data. Insights revealed may initially appear counterintuitive, but there’s great value to be found by those who crack the code. Read more about Twitter’s research at The Verge.
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