2. Unlocking the Future of OTT TV with AI-Driven Personalised Recommendations TECHNICAL
The Imperative of Personalised Recommendations in OTT TV
These cutting-edge algorithms can sift through a multitude of factors in real- time, from user behaviour to similar user profiles, to deliver highly personalised content suggestions. However, AI bias as a potential risk can inadvertently skew recommendations and limit content diversity, thereby affecting the overall user experience. The Value Equation: A Win-Win for Users and Telco Companies For Users: Personalised recommendations driven by AI dramatically elevate user engagement by minimising the time spent on content discovery. Scientific studies underscore that users are prone to disengagement if they don‘t find compelling content within 60-90 seconds. AI effectively addresses this challenge by swiftly offering accurate and tailored content suggestions, thereby enhancing the overall user experience. For Providers: For telecommunications companies branching into OTT services, AI-driven recommendations offer a significant competitive advantage. These algorithms not only enhance user retention but also furnish invaluable data insights. These insights can be strategically leveraged for targeted marketing campaigns, content acquisition strategies and even pricing models.
Case Study: Sky Deutschland, a leading OTT TV service provider in the DACH region, exemplifies the transformative power of AI-driven personalised recommendations. Their sophisticated system employs a blend of content- based and collaborative filtering methods to deliver a highly individualised viewing experience. This has led to measurable outcomes, including increased user engagement, higher average watch times and a notable reduction in subscriber churn. The success of Sky Deutschland serves as a compelling testament to the immense value that AI-driven personalised recommendations can bring to both users and OTT service providers. CONCLUSION AI as the Foundation for Personalised Recommendations in OTT TV The advent of AI-driven personalised recommendations heralds a new epoch in OTT TV. As the industry matures, the spotlight will increasingly be on AI models that are not just algorithmically advanced but also capable of learning, adapting and improving. This promises a more personalised, ethical and engaging user experience, thereby cementing AI‘s role as a foundational element in the future of OTT TV.
In an increasingly crowded OTT TV landscape, personalised
recommendations have transitioned from being a nice-to-have feature to an absolute necessity. These are finely tuned suggestions of movies, series or other types of content, crafted based on intricate analyses of user behaviour and preferences. As the OTT TV market is on track for substantial growth through 2030 1 , the role of personalised recommendations in enhancing user experience and content discoverability has become indispensable. The AI Paradigm Shift: A New Era for Personalised Recommendations AI and ML are revolutionising the way personalised recommendations are generated. While in the past, recommendations were mainly based on curation from the platform operator or traditional methods often relied on static algorithms, AI introduces dynamic, real- time analytics and predictive modeling into the equation. Generative AI models, although still under research, hold the promise of creating even more adaptive and responsive recommendation systems.
3. The Role of Predictive Content Discovery for Long-Term Customer Loyalty on OTT Platforms
The Relevance of Predictive Content Discovery in the OTT TV Landscape In today‘s highly competitive OTT TV landscape, characterised by frequent subscriber fluctuation, platform providers need to offer an attractive content library that constantly evolves according to the interests and preferences of their users.
production of original content is one of the major cost factors in the industry, these decisions are crucial for success and the ability to stay competitive. OTT TV platform providers face the challenge of not only acquiring content that appeals to a diverse and sophisticated audience, but also ensuring that this content remains attractive and exciting over time. As subscriber preferences evolve and users tend to prefer flexible, monthly plans, providers must make informed, forward- thinking content acquisition and creation decisions to attract and retain users. In this dynamic and ever-evolving landscape,
content selection and production are therefore not only about meeting current demand, but also about sensing future trends. AI is Changing the Course of Predictive Content Discovery AI and ML can have a significant impact, empowering OTT platform providers to make data-driven predictions about what content will resonate most with their audiences. This goes beyond mere recommendations for users; it extends to
Since the purchasing or licensing of external content or even the in-house
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MARCH 2026 Volume 48 No.1
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