Streaming video subscriptions hit a record high in 2020, but so did subscriber cancellations. The U.S. OTT churn rate spiked at 41% in the first quarter. A modest improvement of 3% by the end of the year did little to assuage the providers’ concerns.
Executives are employing a range of tactics to keep subscribers on their streaming platforms. From customer experience (CX) optimization to content recommendation algorithms, the effectiveness of any churn mitigation strategy hinges on data-driven intelligence.
While data offers promising solutions to our industry’s churn problem, providers must possess the tools and know-how to enact the data-driven strategies that can achieve desired outcomes. Fortunately, that no longer requires building massive data science teams, developing custom software, or buying costly off-the-shelf solutions unfit for the particular challenges of media and entertainment. Verticalized enterprise AI and machine learning solutions can digest data, provide actionable insight, and support subscriber engagement.
There are a host of data inputs that streaming video providers can (and should) subject to machine intelligence to quickly address subscriber churn. I recently analyzed these, and examined how to build the most effective strategy to capitalize on them. You can read more here.
The key takeaway is this: to overcome subscriber churn, OTT and VOD providers must leverage their data now. Enterprise AI technology is the fastest, highest-impact way to put the entire process in motion at scale.
