Using TV data analytics to see why 4K's failing

Using TV data analytics to see why 4K's failing

Jan Lindquist, Mon 13 November 2017

Deploying 4k video requires a considerable investment and many operators are finding that it does not have the expected uptake amongst consumers. We've been working with operators to use predictive analytics to help understand consumer uptake of 4k.

Although a lot has been written about the technical factors that effect consumer uptake, we have found that consumer engagement, content investment, and changing consumer habits can be equally key.

Consumer engagement

When we talk about consumer engagement, we look for ways we can measure it. This comes down to how often people use the service, how long they use it for, and how deeply they engage with it. A subscriber that uses many premium features - of which 4k is only one - is significantly more engaged that one that one that only watches a single show.

When we build a churn model, we'll typically extract a set of features that we can use to measure engagement and then score it according to how likely it is to indicate churn amongst subscribers. The higher the score, the better the indication of churn. In the example below, the features of top importance are sports genre, number of days in a month of viewing content, and tenure. Tenure represents how long a consumer has subscribed to the service. High scores on these three features indicate loyalty; low scores indicate a higher risk of churn.

Customer engagement

To better understand how importance (y-axis) applies to features, consider tenure. The example below shows that the longer the subscription, the lower the likelihood that the consumer will unsubscribe. It also shows that within 2 to 6 months, almost half of the consumers left the service. This information provides valuable insight, allowing operators to create a consumer scorecard showing the likelihood a consumer will drop the service. The scorecard, in turn, makes it easier to take strategic steps to prevent churn.

Customer engagement

Data on consumer engagement provide a baseline that operators can use to measure the influence that introducing 4k content has on consumer behaviors in three key areas: consumption habits; content rights investment; and targeted marketing.

Consumption habits

Consumers' bandwidth limitations are probably the biggest concern when deploying 4k, as they affect the quality of experience. Consumers with limited bandwidth (caused, for example, by poor coverage) will not notice 4k but simply see content at lower levels of resolution. To understand whether 4k is likely to increase revenue, it may be less important to know consumers' bandwidth limitations than their consumption habits; for example, where and how they consume content? Do they use the operator's service when commuting, when abroad, or when at home? Do they view content on different screens (e.g., the primary device or a secondary screen, such as a tablet)? A mobile data plan can make consumers very reluctant to view 4k content when on the road, and they are willing to suffice with standard definition quality. It would not make sense to invest in 4k content if the target group uses the service most frequently when commuting and has an average of 20 minutes of viewing time.

Content rights investment

We need to take multiple factors into account when selecting content, including consumer engagement, consumption habits, and target group. Before investing in 4k, it is essential to determine which consumer group would value such content the most. In fact, depending on consumption habits, investment in tier-1 4k content (like blockbuster movies) may not provide same return as investing in tier-2 content (like documentaries or lower-budget films).

Targeted marketing

Understanding user's preferences are crucial to preparing marketing campaigns. The consumer scorecards described above enable operators to identify and focus on consumers whose low scores suggest they are most likely to leave the service within six months of subscribing. Operators can target new campaigns or provide free content or other incentives to such consumers. Not every promotion will work?a reason to use AB testing and try different approaches before starting a broader campaign.

Consumer engagement, predictive analytics, consumer scorecards, and AB testing are vital tools for operators to understand consumers better. To deploy 4k successfully and cost-effectively, analytics need to play an influential role. Like any good venture, it is essential to think of the effort of introducing new features, including 4k, as a Minimum Viable Product. If results are not meeting expectations, the operator benefits from quickly stopping the effort or pivoting in a new direction.

Operators need to review consumers' engagement to understand how 4k can make most impact; understand the consumption habits of the primary 4k target group; match 4k content to consumer engagement for the most cost-effective 4k investment, and then target marketing campaigns to consumers at highest risk of dropping their subscriptions.

That way, you can make a real success of 4K.

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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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