Big data yields the biggest bucks when insights are counterintuitive

Big data yields the biggest bucks when insights are counterintuitive

Tom Weiss, Thu 17 November 2016

Data, whether we call it big or not, only delivers value after conversion into actions and these can be most powerful when the underlying insights are counter-intuitive or at least not immediately obvious. This is as well not just for our business in TV data, but also our customers, because it means there is boundless potential for revenue gain and competitive advantage in surprising ways.

One fun example: we did a piece of analysis for one customer and found the highest performing content was not premium sports or blockbusters but second-tier horror movies that normally go straight to VoD. We were then able to advise that instead of focusing on the latest big hits that cost a lot of money on rights, this operator would be better off working through the long list of horror movies as well as other middle ranking content and pick out those assets that best match their audiences.

By focusing on mid-tier content, 20% of lapsed users started watching again and there was a 5% average increase in consumption within the group selected to test this idea.

Our insights are also delivering major benefits in advanced advertising, although a key point I often make is that these do not always come at a stroke and we encourage operators to proceed in small steps, proving the concepts as they go. A favorite example of mine came when we looked for correlations between subscriber preferences for consumer products and TV viewing, with obvious scope for behavioral ad targeting. In one case we looked at people who had actually bought smart watches and compared them with another group identified as potential buyers, along with the audience as a whole. This turned up another seeming curveball with the finding that actual buyers of smart watches view a lot more TV after midnight than the rest of the audience. This had obvious positive impacts around the effectiveness of the ad buys the maufacturer made.

Such a finding can be valuable for both the network or MVPD, and the brand. The network or MVPD can charge more for those late night slots, while smart watch advertisers can avoid spending too much on the even more expensive prime time slots.

Such examples highlight the benefits of combining viewing data with information about subscriber behavior, which can increasingly come from external sources as in the smart watch example, with potent effect. The cumulative effect for MVPDs of all such insights can be huge but we recognize that our customers want to be sure we do deliver ROI as we go. This is why it is important to start small and proceed in manageable steps, even if we are all looking forward to big gains in future.

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Dativa is a global consulting firm providing data consulting and engineering services to companies that want to build and implement strategies to put data to work. We work with primary data generators, businesses harvesting their own internal data, data-centric service providers, data brokers, agencies, media buyers and media sellers.

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