The OTT landscape is rapidly evolving, and personalised content discovery is becoming a central focus for platforms aiming to engage users effectively. As the amount of content available continues to grow, platforms are turning to advanced algorithms and data-driven solutions to help users discover relevant shows and movies. Here are some key trends shaping personalised content discovery:
AI and Machine Learning Powering Personalization
OTT platforms need to leverage AI and machine learning-powered sophisticated content recommendation systems. 60% of people globally find navigating multiple entertainment platforms frustrating, with personalised suggestions being a key factor that could increase levels of content consumption. Algorithms can analyse vast amounts of data, including viewing history, preferences, and even the time of day users watch content, allowing for highly personalised recommendations for each individual.
For example, in terms of viewing trends, data from MovieMe reveals distinct preferences across different regions and demographics. For instance, in New Delhi, action, comedy, and romance lead the way, while Mumbai viewers favour action, comedy, and drama. Bengaluru shows a penchant for crime alongside action and comedy, and Chennai viewers lean toward family-centric films, romance, and comedy. Meanwhile, Hyderabad users continue to prefer action, comedy, and romance.
When looking at content preferences by gender, male viewers tend to enjoy action, comedy, and adventure, while female viewers lean toward comedy, romance, and drama. Interestingly, agender viewers are drawn to animation, adventure, and fantasy, and bigender viewers favour adventure, war, and action.
These statistics underscore the growing need for platforms to tap into data about broader user preferences to create truly personalised content discovery experiences across the OTT landscape.
Addressing the Discoverability Challenge
With the sheer volume of content on OTT platforms, users are often overwhelmed. 73% of respondents in a study reported feeling overwhelmed by the number of choices available on streaming platforms. Personalised recommendations significantly reduce this burden by helping users find content more efficiently. Using real-time data to dynamically adjust recommendations can significantly increase user satisfaction and engagement.
The Rise of Aggregation
One of the biggest challenges in personalised content discovery within the OTT landscape is the limited scope of recommendations provided by individual platforms. Each OTT service can only suggest titles from its own library, often leaving users unaware of content they might enjoy on other platforms. This creates fragmented viewing experiences, with hidden gems going unnoticed simply because they aren’t available on the platform a user is subscribed to. As a result, users often feel restricted in their content choices and miss out on diverse and engaging content that aligns with their broader viewing habits.
Recent insights show that platforms capable of aggregating user behaviour across multiple OTT services are better positioned to provide comprehensive and personalised recommendations. By analysing viewing habits across different subscriptions, these platforms create a more unified understanding of user preferences. For example, such services can track content watched across multiple platforms and deliver suggestions based on cumulative activity rather than being confined to a single library.
The Rise of Hyper-Localised Content
OTT platforms in India are increasingly focusing on personalised recommendations tailored to regional and linguistic preferences. Almost half of OTT viewership in India is driven by regional content. Platforms must utilise data to push localised recommendations based on location, language, and regional trends. This approach is essential for increasing engagement in a market as diverse as India.
Cross-Device Personalization
Users today consume content across multiple devices, and platforms need to adapt by offering seamless content discovery experiences across mobile, smart TVs, and tablets. This cross-device personalization ensures that users receive consistent recommendations no matter where or how they are watching. A majority of OTT users own at least three connected devices and they regularly switch between devices, making this an important trend for platforms aiming to retain users across all touchpoints.
Data-Driven Content Creation
OTT platforms seeking to stand out from the competition must use personalised data to inform content creation. By analysing viewing patterns and preferences, platforms can produce original content that resonates with specific audience segments. OTT’s ability to produce and recommend content in harmony will result in hits which are targeted to align with user interests.
Interactive Content Discovery and Gamification
Interactive content discovery – through features such as quizzes, polls, and gamified elements – are the next evolutionary step in the battle to keep users engaged. These methods allow users to actively participate in content selection, further enhancing personalised discovery. Early results show that these approaches help drive up user engagement and retention, and can also serve as important barometers for measuring audience interest in particular titles.
(Views are personal)
