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Drafting a Blueprint for Long-Term OTT Success

What happens when a platform over-relies on data from existing users to drive decisions designed to attract new users? How should a platform’s decision-making framework change over time as it increases its market penetration, when potential subscribers are increasingly more difficult to attract? Is there really a “blueprint” for long-term OTT success?

As the streaming video market has become increasingly more robust and competitive in the past couple of years, data has taken center stage as a tool to maintain a competitive advantage. However, overrelying on in-platform data can be detrimental in the long run. Looking at platform-specific data tends to over-optimize for retention and — longer term — lowers off-platform user acquisition efficacy, resulting in a lower lifetime value (LTV), as well as a lower customer acquisition cost ratio over time.

Demand for original programming is the strongest indicator of SVOD growth. Each incremental title drives value by adding to the total demand. However, only highly in-demand titles increase the average demand level for the originals slate. For OTT platforms, both the volume of library content and the perception of quality drive subscription growth at various stages of the platform’s adoption lifecycle. The premise is simple: Add more content, get more subscribers.

For growth, quality content drives higher average demand and leads to more subscribers, given that the early adopters have already been converted. Once a market becomes more established, subscription growth becomes more nuanced and retention becomes increasingly necessary, particularly with increased competition. At this phase, growth happens via two methods:

• Creating tentpole original titles that lift the average demand.
• Creating smaller original titles that are designed for specific off-platform taste clusters.

For Netflix, average demand for its original content hit its apex in Q2 of 2018 in the United States. A year later, in Q2 2019, average demand reached an all-time low, decreasing 5% from Q1 2019 and subsequently resulting in the company’s first domestic subscriber decrease. While the dip was concerning, causing share prices to drop 11% after the Q2 2019 earnings report, it does not signal the end for the streaming giant. Netflix is still the one and only home to some of the most in-demand TV content in the world. Season 3 of Stranger Things caused average demand to rebound by 9%.

New competitors introduce two threats to incumbent OTT platforms. Firstly, many linear-turned-DTC services are reclaiming their content (i.e., NBC’s takeback of The Office), lowering the per-title catalog demand average and longevity. Secondly, the entrance of these competitors and the ramping up of other streaming competitors requires the incumbents’ content to be more exclusive and in higher demand than ever before.

Familiar Content Breeds Retention

Licensed content supports retention after the adoption stage, where it contributes to a critical mass of demand volume needed to retain current subscribers. For licensed content to produce maximum value as an investment, it must appeal to existing taste clusters of subscribers, drive high demand and have high longevity. Original content, however, can drive both retention and subscriber growth as the platform continues to scale up.

In summary, if an OTT platform is looking to create a blueprint for long-term sustainability and success, the company needs to look at each phase of development and consider both on- and off-platform, market-specific data. In the early adoption phase, the volume of original content demand is key to drive subscriber growth. Once a platform achieves its growth phase, a portion of this total library should include evergreen content to create a base to sustain subscribers in the future. As a platform continues to mature with an established base of subscribers, it should not only aim to acquire new subscribers, but also retain its existing ones.

Additional titles should be evaluated based on the size and number of taste clusters they reach, the market demand they generate and the degree to which they tap into on- and off-platform populations.