With a surge in the uptake of FAST channels, we look at the key factors that help boost viewer engagement and monetisation.
The free ad-supported streaming television (FAST) market is expanding at an extraordinary rate. Digital TV Research predicts that global FAST revenues for TV series and movies will reach $17bn in 2029, and the MENA region is expected to be a significant contributor. With FAST channel revenues in the region hitting $7.2m in 2023, MENA is poised for even more growth in the coming years, according to industry analysts.
In this booming market, personalising video content is crucial for several reasons. By tailoring content to individual preferences, service providers can significantly enhance the viewer experience, making it more engaging and relevant. Personalised content also enables more effective monetisation strategies. By understanding viewer preferences, service providers can offer targeted advertisements, personalised channels and content bundles that are more likely to resonate with the audience and result in higher ad revenues.
With content personalisation becoming a necessity, video service providers need to solidify their standing in the ultra-competitive FAST market and find ways to drive viewer engagement.
Personalisation strategies and targeted TV advertising
To elevate the user experience, video service providers must offer more advanced forms of personalisation, such as targeted TV advertising, personalised channels, tailored personal pages, personal search and recommendation results, and content bundles.
In the past year, targeted TV advertising has transformed the media industry, outpacing all other business models to help video service providers maximise their revenues. Worldwide, addressable TV revenue is expected to climb to $87bn in 2027, accounting for one-fifth of all global video ad buying.
Targeted TV advertising is an important pillar for monetising video streaming services; however, its success relies on attaining valuable, in-depth insights into viewers’ behaviours and preferences. Forming partnerships with local and regional advertisers is also critical to personalising FAST channel ads. Such collaborations can ensure video service providers deliver tailored adverts that are accurate and culturally and linguistically relevant. Furthermore, integrating interactive and shoppable ads is an effective way to boost viewer interaction and drive higher ad revenues.
Personalised FAST channels
Offering personalised FAST channels is another solid strategy to boost viewer engagement, reduce churn and increase monetisation. Driven by usage data, viewing preferences and subscriber consumption patterns, personalised FAST channels address the age-old dilemma of viewers not knowing what to watch.
Content bundles
A major trend in the FAST market is content bundles. Some of the biggest names in the media space have joined forces to offer consumers all-in-one packages of entertainment choices. Bundling FAST channels increases advertising revenue by attracting larger audiences and enhancing cross-promotion. Furthermore, this approach improves customer retention through a varied content offering and better user experience.
Content bundles can be personalised through advanced technology and data analysis, allowing platforms to tailor media collections to individual user preferences, enhancing engagement and satisfaction by making the content more relevant and appealing. While the degree of personalisation can vary, the ultimate goal is to optimise the viewing experience for each user.
Bundling also provides operational efficiencies, greater negotiating power with content creators, and market differentiation. It also enables targeted advertising and subscription upselling, further boosting revenue opportunities for video service providers.
Why audience segmentation is essential to personalisation
The key to successfully delivering all the above lies in effective audience segmentation. Broadcasters and service providers can effectively isolate specific audience segments based on first-party TV data, analysing usage flows and identifying consumption patterns. Broadcasters and service providers can further fuse additional data from third parties, including shopping and browsing interests of their viewers, leveraging AI and ML algorithms to generate sophisticated, highly accurate audience segments.
Benefits of audience segmentation
Audience segmentation combines intuitive rule-based queries, AI/ML models and generative AI capabilities to segment viewers based on various geographic, demographic, psychographic and behavioural criteria. This includes age, family composition, TV consumption preferences in terms of both content (specific programmes, movies) and genre (cooking, sports, soaps), as well as viewing hours and viewing habits (late night or morning, binge watching). Once video service providers gain a holistic understanding of their audience, they can then target distinct groups with common characteristics or preferences.
For targeted TV advertising, audience segmentation allows the replacement of ads aimed at specific audiences during linear primetime content. Consequently, channel providers can charge premium rates for advertising while also reducing churn rates, as viewers tend to respond more positively to targeted ads, resulting in increased monetisation.
Audience segmentation can also be used for engagement monitoring and improvement purposes. Audience segmentation technology allows video service providers to identify viewers who are not watching personalised channels, enabling them to improve the personalised FAST channel experience.
Essential requirements for audience segmentation beyond data aggregation
Today’s service providers are inundated with data, but they don’t know how to maximise it to drive viewer engagement and increase monetisation. Audience segmentation brings video service providers solutions that go beyond mere data aggregation, providing actionable insights.
Adopting an audience segmentation solution that collects and analyses data from every part of the video delivery ecosystem – backend servers and databases, set-top boxes, player apps, content metadata, user interactions, even third-party data – will ensure that video service providers have a complete understanding of an audience and the market dynamics guiding their decisions.
Likewise, pre-trained AI/ML models are invaluable. Allowing video service providers to create sophisticated segments that maximise impact, these expand on the capabilities of making simple queries to produce cross-referenced segments that pull data from multiple categories.
Anne-Sophie Cornet is Product Marketing Manager and Eyal Yoskovitz is Director of Data-Driven Products at Viaccess-Orca.
