Smart TV Advertising Isn’t Truly Smart… Yet


Stephanie Magnan

Targeted advertising on TV causes headaches when it comes to using personal data, as gaining consent in the TV environment is tricky. In this piece Stéphanie Magnan, head of marketing at Media Distillery, argues that broadcasters and operators should use AI to create personalised TV experiences, and then use the data around how audiences interact with these experiences for targeted advertising.

Streaming services have raised the bar for the TV industry 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, scalable revenue sources and how can they redefine the TV experience? And how can linear TV providers save themselves from sinking into irrelevance?

The key lies in making TV a ‘UX-first’ experience – an approach which is made possible by machine learning to enable deeper content recognition and smarter user insights.

How to Target Ads in a Cookieless Environment

UX-first means TV is addressable for both users and advertisers: whilst users sit in the driving seat, advertisers get an 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 target ads with immense granularity.

But beyond this, UX-first means in-depth content personalisation, using applied artificial intelligence (AI) to peer inside video and understand user decisions. This gives advertisers an end-to-end view of audiences 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.

It also make for more privacy conscious advertising. Regulation has been a big obstacle for addressable TV advertising and getting a more nuanced understanding of consumer context in the cookieless TV environment is at best tricky, and at worst a GDPR nightmare.

The answer to this is to enrich consumer profiles with their content preferences, so as not to solely rely on collecting audience data. Rather than a viewer’s personal information and immediate surroundings, broadcasters and operators instead might think about topic detection, facial recognition within content, viewing habits and search behaviour – and not just age, gender and geotargeting.

What do the closely personalised TV experiences of tomorrow look like? What does it mean to closely understand what someone is watching, and what does it really say about them?

Contextual Advertising Refined

As our ability to understand video content grows, the experiences we deliver to consumers can get exponentially better more customised, through applied AI to understand content preferences.

As an example, a sports-crazy user could 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 would also be completely tailored to her search behaviour.

Then, if she shows specific boredom patterns by switching between tennis match clips and The 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, this could qualify her profile for potential advertising campaigns based on logo exposure and active interest.

This really expands the sorts 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 is still a better reflection of who she is – a more representative attribute than her home address.

This new world of advertising opens up doors to reeducate the entire ecosystem about what valuable data and consumer behaviour actually mean.

To create a TV advertising ecosystem which 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 which is willingly used as currency by the viewer in exchange for better content experiences.

In this transaction, the user finds what they are looking for with the ultimate convenience; TV operators and broadcasters can thrive, and both brands and traditional players can avoid solely relying on demographic data which has a high regulatory price tag and looming expiry date.

UX-y and You Know It 

Linear television’s stakeholders are reaching an inflection point where finding new ways to monetise users is a must.

But as I mentioned above, privacy regulations and competition from SVOD services are putting the user in the driving seat, and changing revenue models need to be on their terms. That’s why we’re entering a world of TV advertising driven by better user experiences:

  • Embracing addressable TV broadens the scope for broadcasters and operators to make the most of deep content analysis
  • By making the most of smart devices, service providers can focus on tailoring content experiences and applying AI-driven insights, instead of targeting entire demographics en masse
  • This means enriching profiles in creative new ways, and productising audiences based on their preferences whilst steering clear of regulatory red-tape
  • Don’t go it alone. It’s time for TV providers to forge new partnerships with applied AI specialists, to make sure precise video insights can be extracted and used at scale

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 and interact with.

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.


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