CTV and FAST players need to take three crucial steps to make the burgeoning medium more appealing to advertisers.

Free ad-supported streaming TV (FAST) platforms have gained immense popularity in recent years, offering viewers a wide range of content options without spending money on subscriptions. Of course, access to free content through FAST comes with an increased amount of advertising.

While consumers with tight budgets may not mind this trade-off, they may become overwhelmed by the sheer volume of ads that don’t directly appeal to them. If done right, advertising in FAST can eliminate advertising fatigue and promote viewer engagement, thereby meeting branding goals and increasing monetisation.

Thanks to the growth of FAST and connected televisions (CTVs), content owners can begin to envision new opportunities for contextual targeting and monetisation. This includes better ad personalization, innovative ad formats, and new pathways for viewer interactivity.

Shifting to contextual targeting
Content owners and advertisers have always been concerned with how they can more accurately tailor ads to viewers’ interests, thereby growing viewership numbers and increasing the chances of converting casual viewers into customers. FAST helps them deliver a superior and uninterrupted viewer experience by utilizing contextual targeting as a personalisation strategy.

Like most streaming services, FAST platforms often base their advertising on audience and viewer data. At the core of this approach is an audience ID, which may constitute a user-made profile, IP address, or another concrete identifier.

This identity may be decorated by other data, such as viewing history, seasonal information like holidays, and affinities with themes and news topics. However, identity will always remain at the centre.

With the demise of third-party identifiers and cookies, it has become even more important to rely on first-party data and behavioural insights to make advertising more personalised. This shift has led to the evolution of contextual targeting, which centres on short-term, very recent audience consumption patterns.

Contextual targeting is concerned primarily with the language and genre of the content being watched, adding the ability to collect more extensive pieces of data, including patterns in the time of day when the content is viewed. Rather than create and keep an extensive profile over time, contextual targeting limits its data gathering to a select number of viewing sessions, adding more weight to the recency of data.

For example, imagine a viewer who has shown a strong interest in nature documentaries on a FAST channel. Each ad segment in the channel shows products or services that are different from each other yet somewhat relevant to the content, from reusable water bottles and travel backpacks to vacation getaways and campaigns for environmental sustainability. That viewer could then switch to a cooking channel, where the brands would be replaced with local supermarkets, kitchen appliances, or classes at a community centre.

While mobile and desktop users are often resistant or annoyed by this form of advertising, especially if it’s a full-page pop-up, linear TV users are much more receptive due to their familiarity with the medium.

Contextual keeps viewers engaged with ads that are relevant to them at that moment rather than over time. Not only does this reduce the likelihood of repeat ads, but it also respects how viewers’ interests can change at any time. Grabbing their attention at the right moment with the right message will boost revenue for advertisers and the FAST platform.

Major challenges to contextual targeting
When viewers can finally connect with brands they like, it increases revenue for the advertiser and boosts monetisation for the platform, fuelling the cycle for more content and personalised ads.

However, digital technology in broadcast and media is not at the point where platforms can begin developing the tools necessary for those opportunities. Content owners must recognise these challenges and make foundational steps toward their development and implementation.

Before they can make these opportunities possible and further their innovation, platforms need to be realistic about the current state of CTV technology. For instance, developers may try to slowly explore methods for turning in-scene content into metadata that will enable more relevant contextual targeting. This metadata may soon lead to less intrusive and more immersive ad formats, including 2D and 3D inserts on in-scene flyers, billboards, and product packaging, as well as small pop-ups and graphic overlays.

Nevertheless, while this method of contextual targeting on CTVs is comparable to the advertising practices of online retailers, the capacity for this technology on CTVs is not as sophisticated as it is on mobile and desktop. With limited client-side measurements in the OTT ecosystem, it is far too early to begin any real development on CTV interactivity that will replicate what viewers experience with mobile and desktop.

Additionally, if this technology were suddenly developed, the average ad-network company would face the challenge of managing both slow- and fast-changing dimensions without knowing what the ROI is to the cost of mining every user’s behaviour.

Keep in mind that contextual targeting is serving millions of users concurrently — personalising, segmenting, and stitching together different kinds of ads and linear content in real-time. Tapping into this data, building a time series around it, figuring out what is and is not monetisable, and then ensuring that ads remain monetisable in certain marketplaces — these tasks further complicate the technical and practical nature of building interactivity into CTV and FAST.

Key steps in making the shift and innovating onward
To address these challenges for CTV and FAST in the long-term, players in the ecosystem can start by taking three crucial steps:

1. Addressing the issue of demand fragmentation

Gone are the days of being nostalgic over “we’ll be right back” statements appearing on screen.

In today’s live-streaming ecosystem, these slates are taken as a sign of failure in securing advertising for the service. And in a content-based system, streaming services need a pool of more than enough advertising to target viewers adequately. This will require service providers and their distribution partners to bring advertisers over to CTV and FAST.

More demand means more opportunities for contextual targeting, which translates into increased viewer engagement and ad revenue.

2. Supporting the creation of an established standard

As we’ve discussed, what keeps CTV from rising to the level of interactivity on mobile and desktop is the limitation in client-side interactivity standards. An established standard for CTV would open more opportunities for monetisation.

To get there, the industry needs to unify the fragmented CTV and OTT ecosystem of standardising ads, which means bringing the major mobile, desktop, and internet players into the mix. Only then can the ecosystem have a foundation to build from.

3. Unifying content consumption and ad metrics

Coming from a traditional mindset of video advertising, the industry continues to split metrics into those that are related to content consumption and others that are related to ads.

To help platforms approach all the challenges FAST presents with content, ad insertion, ad instrumentation, and measurement, metrics for content consumption and ads need to be joined together and seen as one unified metric.

Content-based personalised advertising is essential for driving increased viewer engagement and ensuring better viewer privacy on FAST platforms. However, FAST platforms must balance their eagerness for personalised advertising with a realistic view of where CTV technology currently stands.

Only by collaborating across industries to change how ads are licensed and metrics are established can major players foresee a next-gen FAST ecosystem that provides far more opportunities for monetization.