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November 29, 2016

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How secure analytics can turn big data into big bucks

One of the most exciting developments for Verimatrix and our customers has been harnessing the scope and reach of our Verspective Operator Analytics platform for big data analytics, which lead to lucrative actionable insights.

Our play in analytics has three elements, the first and most obvious being the application of analytics data with our revenue security technology, exploiting its well-proven pedigree for video content. We can now help protect sensitive customer data and ensure that subscriber privacy is upheld so that operators can in turn convince their customers that the benefits of analytics greatly exceed the risks.

Secondly by virtue of our privileged position in the ecosystem as custodians of premium content we have access to a variety of subscriber and service related data not otherwise readily obtainable. Such data spans the whole delivery chain from the head end through the network to client devices.

Finally, we secure the overall integrity of all the data collected, ensuring that the source of that data is authenticated and encrypt it so it cannot be corrupted or misappropriated, ultimately increasing the value of the data to operators and advertisers.

Yet while we are well placed to obtain and protect big data as a security specialist, we recognize we can offer the best analytics solution by partnering with specialists in the various divisions of that field. Now that we have examples of significant benefits resulting from these collaborations we are keen to promote this activity.

Real world examples

In a recent webinar, Turning Big Data into Big Dollars, which is part of a series on analytics, we discussed how big data analytics can be harnessed with two of our key partners, ThinkAnalytics with its leading recommendation engine and Genius Digital, a specialist in deriving actions from return path data and other third party data sources. During the webinar, examples were given of major benefits gained by combining our respective platforms, including churn reduction, increased viewer engagement, upselling and targeted advertising.

ThinkAnalytics VP, Product Services, Richard Dowling, highlighted how the UI (user interface) can be personalized through data based on what subscribers are viewing and purchasing, obtained via the Verspective Operator Analytics interfaces. The improved UI enables the ThinkAnalytics recommendations engine to ensure the first piece of content presented to users when they switch on the TV is something they really want to watch. This has led to significant increases in consumption, which have been measured using A/B testing.

Dowling pointed out that testing can be conducted over time by comparing viewing levels before and after deploying the recommendations engine. Alternatively, the testing can be done on a head-to-head basis where the impact of the engine is compared with a control group within which recommendations are made by a traditional editorial team. Both methods have revealed similar massive improvements in engagement, with a recent head-to-head A/B test finding a 40% higher level in viewership for the group exposed to the recommendation engine compared with control. 

Genius Digital’s CEO Tom Weiss elaborated on the benefits achieved for one operator by segmenting subscribers by genre and VoD payment model. This operator, like many others, had a mixture of free VoD, subscription VoD and transaction VoD services with usage levels in each case split into low, medium and high categories. Viewing in each category was then analyzed via a heat map across 10 genres (Educational, Factual, Kids, Lifestyle, Movie, Music& Dance, News, Special Characters, Sports and TV shows).

The analysis had clear objectives to counter lapsing from the bottom end while encouraging subscribers to move up the value chain to higher tiers of consumption, converting free VoD to SVoD for example, or SVoD to the still more lucrative TVoD. One finding was that viewing of factual content was higher among paying VoD customers than free ones. The obvious implication was that those free VoD customers watching a lot of factual content were more likely candidates for promoting to SVoD. This could be achieved by targeting free VoD customers with suitable offers. Interestingly Dowling interjected by pointing out that the ThinkAnalytics engine could then kick in within the SVoD user category by increasing bias in recommendations towards factual content, exploiting the Genius Digital findings.

There is also scope for drilling down further within categories, noting that Factual, for example, can be broken down into sub-genres such as Reality and Instructional, with potential for further gains in engagement. This process can continue, branching out to identify ever smaller sub-divisions which may then be grouped in various ways according to behavioral traits that may indicate they can be aggregated fruitfully for ad targeting for example. It may be that people with seemingly unrelated viewing habits share common interests in particular products or services.

Indeed apart from upselling, data analytics also has great potential for revenue generation through advanced advertising and Weiss described how this could be enabled by matching general audience data with third party databases. In one case this identified how buyers of smart watches were much more likely to watch TV late after midnight than the average, perhaps in part reflecting this being a young demographic. This means operators can make money selling such late night slots by pitching at smart watch advertisers, who in turn can target their audience without having to buy even more expensive prime time spots.

Such use cases do not require any advanced technology, which Weiss identified as a key point because TV operators are mostly unwilling to invest in analytics tools without some reassurance that ROI (return on investment) will come quickly.

This gels with Verimatrix’s view that big data analytics should and can deliver immediate benefits. We encourage you to watch this on-demand webinar, as well as the others in the analytics series: How Analytics Can Make Operators More Competitive and How Operators Secure the Integrity of Video Analytics Data.  

We’d love to hear about what other topics you’d be interested in for upcoming webinars. As always, ask questions at any time!

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