How can traditional service providers apply deeper understanding to TV experiences, to generate new sources of advertising revenue?
It’s time for TV to reinvent itself. Not only are viewers switching from Linear TV to Over-The-Top (OTT) video in ever-greater numbers, but consumer behaviours are changing rapidly too- a double-edged sword that will throw broadcaster and operator advertising models into jeopardy.
You’ve heard it before: streaming services have raised the bar in terms of how they’ve swept up their share of the attention economy. Subscription models and the switch-or-skip capabilities of on-demand services mean that users are fully in control, and they aren’t accepting ads anymore.
At this tipping point for TV, where can traditional services tap into new and scalable revenue sources, and redefine watching experiences?
How can linear TV providers save themselves from sinking into irrelevance?
Here, I explain how TV watching experiences can be redefined to keep up with consumers and keep advertisers sated; an approach that is made possible by Machine Learning, to deliver deeper content recognition and smarter user insights.
ProSiebenSat.1 and RTL Deutschland are teaming up to drive the development of addressable TV, whilst Roku and Apple TV are set to drive advertising growth to new heights.
The future of TV is smart, and advertising strategies need to follow suit. It makes sense for brand-building to digitise and move to hybrid and sustainable monetisation models – and this means user experience (UX) comes first every time.
UX-first means TV is addressable for both users and advertisers: whilst users sit in the driving seat, advertisers gain a scalable understanding of where their audience is going, and the non-linear roads they take to get there.
After all, the attractiveness of addressable TV lies in its targeting capabilities. With programmatic technology, this provides an opportunity to approach advertising inventory with immense granularity.
But let’s look further and add an extra layer: it means in-depth content personalisation, using applied Artificial Intelligence (AI) to peer inside video and understand user decisions. It guarantees end-to-end viewing and enriches user profiles based on their watching behaviour- not only based on their demographic and geolocation.
This extra layer can empower advertisers to apply user preferences at scale across any media environment, and any connected device. After all, smart TV isn’t truly smart until it has a deep understanding of the content it serves.
How does it work?
With greater data, comes greater responsibility. Regulation has been a big obstacle for TVadvertising and having a more nuanced understanding of consumer context via cookielessTV is at least tricky and at most a GDPR nightmare.
Service providers need to overcome significant difficulties around data collection and audience targeting, so our most personal entertainment channel can stay relevant, without getting creepy.
The answer is to enrich profiles with content preferences, so as not to solely rely on collecting audience data.
A near-future of video watching will force TV broadcasters and operators to think outside of that tightly regulated, digitally connected box to consider the context of what a viewer is consuming. Rather than their personal information and immediate surroundings, instead think topic detection, facial recognition, watching habits and search behaviour – and not only age, gender and geotargeting.
What do the closely personalised Total Video experiences of tomorrow look like? What does it mean to closely understand what someone is watching, and what does it really say about them?
As our ability to understand video content grows, the visual experiences we deliver to consumers can get exponentially cooler – and more customised, through applied AI to understand content preferences.
Your sports-crazy user can not only binge-watch Serena Williams in the run-up to the Wimbledon final by working through her backlog of related catch-up features, but these are also completely tailored to her search behaviour.
Then, if she shows specific boredom patterns by switching between tennis match clips, and Bachelor? The sequence of her recommendations shifts accordingly, mirroring her attention span and the rhythm of her topic preferences.
When it comes to watching the Wimbledon final, does your user pause and replay the close-up of Serena serving, as you get a glimpse of the brand and the range of her sportswear? After a couple of replays, can this qualify her profile for potential advertising campaigns based on logo exposure and active interest?
This really ups the ante on the kind of actionable data TV operators and broadcasters can offer to enrich user profiles.
Again, deep recognition within video content doesn’t tell you that your Serena fan is in fact female; it doesn’t tell you where she lives, nor does it offer advertisers any information which personally identifies her: nevertheless, an in-depth understanding of what this user watches still happens to be a better reflection of who she is – a more representative attribute than her home address.
This new world of ‘advertising’ allows TV service providers to not only become premium publishers based on localised audience targeting but opens up doors to reeducate the entire ecosystem about what valuable data and consumer behaviour actually mean.
To create a TV advertising ecosystem that doesn’t feel like advertising, service providers should use a pinch of explicit insight, but place a larger emphasis on profiling with implicit and inferred metadata; data that is willingly used as currency by the viewer in exchange for superior content experiences.
In this transaction, the user finds what they are looking for with the ultimate convenience; TV operators and broadcasters escape extinction, and both brands and traditional players can avoid solely relying on demographic data which has a high regulatory price tag and looming expiry date.
As linear television and its stakeholders struggle to stay relevant in an industry now dominated by Total Video, service providers reach an inflection point where finding new ways to monetise users is a must.
But users are in control now, and changing revenue models need to be on their terms. That’s why we enter a world of TV advertising driven by superior user experience:
In the near future, ads won’t feel like ads anymore. Instead, they will look like personal end-cards or interesting interludes made up of content users genuinely like, want to watch next, and will click.
The TV ecosystem will know this based on billions of data points about the videos users consume, the topics they love, the parts of the story they pause at, and even what this says about their emotional state. And these insights are going to be greater than the sum of their parts in mirroring our ever-changing behaviour, generating better experiences, and steering more sustainable revenue models: it’s do-or-die.
July 24, 2019