25 MAR 2024

Streaming wars: what's beyond the Play Button?

Information from Hub Intel revealed that, while securing a rich content library remains pivotal, companies often underestimate the power of how they design the experience.

25 MAR 2024

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A recent study by Hub Intel has revealed that in the past couple of years, the streaming entertainment industry has pivoted from a relentless pursuit of subscriber acquisition to a more measured quest for profitability and efficiency. However, this shift may have brought unintended consequences, notably an uptick in churn rates, hinting at a potential oversight in long-term retention strategies.

Recent data revealed customer churn rates are on the rise. Across the industry, the rate of customer defections rose to 6% at the end of January, an increase from 5.2% a year earlier. Despite these challenges, a focus seems to remain on acquisition, as evidenced by aggressive promotions and high-profile content deals seemingly designed to draw in subscribers. For example, Starz, estimated to have one of the highest churn rates among streaming services, recently had a promotion offering 6 months for $20. And Peacock’s large $110 Million Wild Card Game deal seems to have been a successful acquisition deal.

Content plays a crucial role in subscriber retention for streaming services. Engaging and relevant content drives subscriber satisfaction and loyalty, leading to higher retention rates. Content quality, variety, exclusivity, and freshness all play critical roles in satisfying subscribers across a variety of needs. For services to ensure adequate content within current financial constraints, expect to see more mergers, partnerships, and bundles this year to boost content offerings. Beyond the content itself lies a key challenge of connecting viewers to that content. 10% of consumers feel fully satisfied with the recommendations provided by their streaming services, suggesting a significant failure to connect subscribers to the right content.

Connecting subscribers to the right content is critical to maximizing the large investments in that content. And despite the ability to deliver more personalized content promotions online, linear TV appears to be more effective at introducing new content via its promotional strategies than streaming services have been where users are relying more on external recommendations. This suggests a real opportunity to improve how we promote our content on the service.

When it comes to recommendations, the role AI and machine learning have in improving recommendation algorithms is undeniable. Yet, in order to truly resonate with viewers and reduce churn, these technologies must be complemented (and even trained) with a human touch and a deep understanding of user experience. Trust is the bedrock upon which effective recommendations are built. The first chart above shows that nearly one-third of viewers perceive recommendations to be skewed toward the interests of the service rather than their own. In cultivating an effective recommendation system, authenticity serves as a cornerstone, ensuring that suggestions genuinely resonate with the viewer's interests rather than merely acting as covert promotions, thus fostering trust. Transparency and clarity are vital, offering clear justifications and evidence behind recommended titles to provide insight into the rationale driving these suggestions. Responsive feedback mechanisms are integral, allowing viewers to contribute their input and visibly influencing future recommendations. Consistent engagement strategies maintain communication with viewers across multiple platforms, subtly guiding their next viewing choices and enhancing anticipation and involvement. Demonstrating empathy and passion by aligning with viewers' interests transforms recommendations into compelling invitations, which showcase shared enthusiasm and emphasize personalized selections over generic offerings.

To enhance recommendations, storytelling and presentation play a crucial role, employing engaging narratives, video clips, and trailers to imbue suggestions with personality, fostering a sense of uniqueness and special selection. Additionally, contextual sensitivity significantly impacts the personalization of recommendations, considering factors like time of day, device usage, and viewing circumstances (whether alone or with others). Recognizing individual preferences, such as favoring horror films on a phone late at night versus family comedies on a SmartTV during the day, contributes to a more personalized experience. Moreover, the presentation context itself, including the juxtaposition of recommendations, influences their reception; for instance, a new recommendation appearing alongside familiar ones can be perceived differently than when surrounded by unfamiliar titles.

With the vast amount of content continually being added to libraries, viewers are increasingly confronted with unfamiliar titles. People will always gravitate towards what’s familiar whether or not it’s the best match for them. To create a compelling viewer experience, it's crucial to highlight connections between new titles and familiar elements, be it recurring actors, directors, thematic links, or settings, which can draw in audiences who may otherwise overlook certain genres. Additionally, strategic placement of unfamiliar titles within thematic collections or alongside familiar content in the user interface serves as a contextual anchor, sparking curiosity. Providing sneak peeks through trailers, clips, or behind-the-scenes moments further enhances engagement, making viewers feel like privileged insiders with exclusive access to the content.

As the streaming industry evolves, so too must the approach to viewer engagement. By prioritizing sophisticated, trust-based recommendation systems, companies can not only enhance the viewer experience but also pave the way for sustainable growth and retention. This journey beyond the play button into the realm of smart content discovery marks a pivotal step towards redefining and strengthening relationships with viewers moving forward.