80% Stay Loyal to Businesses Offering Personalisation in the Streaming Era

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Have you recently tried to find a web series or movie surfing your Smart TV app at home? Then you know what I am getting at. Hundreds of thousands of titles, but nothing that catches your attention!

Welcome to the video content jungle! Frustration and resignation reign supreme for the viewer. There’s even the possibility that they will quit that streaming app and move to a new one. It’s the harsh reality of users navigating most current video OTT offerings. The options available for the viewer keep increasing—new platforms and new video experiences. But do these services offer a good viewing experience? We know the answer.

Change is slow, but it’s steady

Fortunately, the use of machine learning algorithms is helping users in the content discovery phase of their OTT user journey. A recent study by McKinsey back the consumer and business benefits of robust personalisation:

• Organisations that grow faster get personalisation right, and generate 40% more revenue from personalisation efforts compared to their slower counterparts.
• 71% of consumers demand personalisation, and a little over three-fourths get frustrated when companies don’t offer it.
• Almost 80% stay loyal to businesses offering personalisation, and an equal number recommend such services to family and friends.

As early as 2017, Netflix, the big boy of OTT streaming and one of the first services to offer personalised recommendations claimed that 80% of its watched content comes from recommendations.

These are some significant statistics, and I only expect them to grow as more OTT services adopt AI and ML technologies to offer personalisation.

It’s abundantly clear that personalisation is no longer an option for content owners and OTT providers, with the ultimate goal of retaining users on their platform, decreasing churn and offering engaging content discovery experiences.

Personalisation is essential, but how do we get it right?

The thing with AI and ML algorithms is that they need to be fed the right and high-volume data to turn insights into action. These technologies, combined with data, enable platforms to optimise their content recommendations, improve video quality, and enhance the overall user experience.

Here are a few ways AI and ML improve video OTT streaming, personalisation and viewer experience:

• Content recommendations: AI and machine learning algorithms analyse user data, such as their watch history, search queries, and demographic information, to provide personalised content recommendations. These algorithms use natural language processing and predictive analytics to understand user preferences and suggest content that matches their interests and affinities.

• Quality optimisation: AI and machine learning algorithms optimise video quality by analysing network conditions and adapting the video stream to match the available bandwidth. This ensures that the video is delivered smoothly, free of buffering and lag, providing a seamless viewing experience to users.

• Predictive analytics: AI and machine learning algorithms analyse user data to predict which content their specific viewers are most likely to watch and when. OTT platforms can use these insights to optimise content delivery and scheduling for each viewer, ensuring users can access the content they want at the right time. Think new binge-worthy shows on Friday nights for binge-watchers, short sitcoms on weeknights for busy mums, and more.

• Personalised user interfaces: AI and machine learning algorithms can be used extensively to personalise the user interface of OTT streaming platforms. This includes customising the layout, colours, and fonts to match user preferences and recommending content based on user activity. For example, serving Chris Rock on the thumbnail for the 2021 thriller Spiral would engage the star’s fans. Likewise, the same movie can appear with a Samuel L Jackson thumbnail for his fans.

AI and machine learning are undoubtedly critical in helping video OTT streaming platforms deliver personalised experiences to their users. These technologies improve user engagement and retention by analysing user data and optimising content delivery, leading to higher revenue and loyalty-winning viewer experiences.

But there’s more to personalisation

Beyond content discovery and interface, AI enables video OTT streaming platforms to create personalised marketing approaches catering to their users’ individual needs and preferences.

These platforms use machine learning and predictive analytics to deliver targeted and relevant advertising and marketing content that resonates with each user. In addition, getting in-depth insights into users’ in-app behaviours help content owners not just to deliver a better and personalised experience and drive personalised communication with each viewer.

When you own the user’s opt-in data, you can precisely impact the user, their journeys and in-app experiences. There’s a reason most content owners we work with today believe that data is the new gold and an essential driver for their growth. 

Interests, behaviours and other patterns can significantly decrease the cost of users’ acquisition and retention and help content owners to predict potential churn or even prevent disengagement.  

The OTT market is competitive, and your viewer demands that you keep pace

For over 70% of millennials and Gen Z, “watching TV” means watching content online. They make up a significant portion of the population and are the most avid consumers of video content on a variety of platforms. And this cohort has grown up in a world where personalisation is the norm. 

They have been early adopters of OTT’s top platforms like Netflix, Hulu, and Amazon Prime Video. It is only natural that this generation of viewers has concrete and very demanding expectations for how content should be personalised to their tastes. With so many options at their fingertips, they are more discerning content consumers than previous generations. They want to be able to find what they’re looking for quickly and easily, and they expect that the recommended content serves their interests, values and beliefs. They are far more likely to engage with content that speaks directly to them.

Content and OTT owners that act on this viewer expectation and cash in on personalisation opportunities will be the ones that thrive. Now and in the future.