As the World Churns: Using Data to Increase Retention and Engagement

There’s never been a better time to be in the streaming business. Or a more expensive one. Operators need to maximize subscriber lifetime to stay ahead of the game.

Launching any new product or service is expensive, especially in the entertainment business. A new offering is competing for share of wallet (subscriber or advertiser), and just as importantly, for share of perhaps just a few minutes of attention per day.

There are endless options just in the video category, from SVOD and live sports to YouTube to trending Gen Z apps like Triller and TikTok. Just to watch a fraction of the current scripted dramas available would require a committed viewer to forgo both sleep and employment.

That’s why the major streaming services are spending big to build awareness. In fact, the combined spend of Disney+, Apple TV+, Netflix (with HBO Max and Peacock still to come) is moving the entire advertising market.

Since September, Disney has run over 5,000 national TV spots and Apple has run over 4,200. They will account for billions of dollars in new ad spend as they build their subscriber bases.

On top of these high subscriber marketing and acquisition costs is the content itself. Disney is spending $24 billion on original shows, Netflix $15 billion, Amazon $8 billion and Apple $6 billion. Even smaller, niche services have high content production and acquisition costs relative to their subscriber bases.

Another major cost component is the multi-platform user experiences required to support the service. Mainstream apps need to not just be on iOS, Android and browser (and all the flavors of these – folding phones, anyone?) but other devices like Roku, Smart TV and Apple TV. Even voice-powered devices need to be on the roadmap. There is always another operating system to plan for just around the corner.

These massive investments combined with generous trial periods have seen strong subscriber growth (or at least new sign-ups), which says that the acquisition strategies are working.

But the most important question is now that you have the subscribers, how do you stop them going away?

Churn is top of mind for every OTT marketing team. With no long-term contracts, subscribers add and delete services as they move between the shows and seasons they like, with no long-term loyalty.

An interesting approach taken by DAZN, among other services, is to offer a discounted annual subscription. Subscribers can choose to pay $100 upfront for the year, or $20 month-to-month. Annual pricing can smooth out the seasonality of viewership, but the 12-month content roadmap needs to be compelling for subscribers to get the commitment.

Apart from pricing strategies, data-driven approaches to churn prediction and management are becoming more sophisticated, and more widely adopted.

The first part of successfully implementing a data-led approach to churn is truly understand the subscriber. This means collecting data from multiple sources, ideally housed in a data lake (a repository of structured and unstructured, raw data e.g. content catalog, UX events, subscriber management system). Machine learning techniques are then used to analyze and predict churn trends by querying the data lake.

Looking at the entire user population, analysis can provide current trends and predicted churn rate for each segment. Major churn influences can be identified, like average minutes watched per day, total lifetime minutes watched, number of days since last viewed content.

Drilling down further, audiences can be scored according to their likelihood of churning over say the next three months, allowing marketing to focus resources on the at-risk users. With knowledge of the cohort of subscribers most likely to churn, and a good understanding of the reasons why, marketing can engage in focused engagement, retention and win-back campaigns.

The most well-targeted campaigns are worthless without detailed effectiveness measurement. Tying back specific messaging and offers to audience actions closes the loop and continuously improves both subscriber understanding and marketing efficiency.

Given the cost of acquiring a subscriber it makes sense that retention and churn reduction is a high priority. Even a 3-5% reduction in churn rate can translate to millions of dollars of customer lifetime value. Using advanced data analysis and machine learning should be part of every marketing team’s playbook.

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Photo credit: For All Mankind | Apple TV