“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Tony Chen, CEO at Channel Factory.
As the EU’s General Data Privacy Regulation (GDPR) loomed last year, many industry leaders asked if limitations on consumer data would disrupt ad targeting.
Major US advertisers and publishers put GDPR controls in place, but it was mostly a concern for the European marketplace. A year has gone by with no major implosions in the US data targeting market, although there are signs of change – and a move to contextual targeting is one of them.
Now, new regulations across states such as California and Nevada could accelerate the contextual trend. Unlike GDPR, which provides a broad recommendation for a set of countries, the state-level privacy laws do not follow similar approaches. This will make it harder for media buyers to manage data-driven targeting in the United States, and will pave the way for other targeting options with less legal complexity.
How states laws differ from GDPR
As US privacy regulations emerge, the talk about a move to more contextual targeting becomes more realistic. There are many nuances that can make it very hard for a brand to manage individual state privacy laws. For example, California defines a consumer as anyone living in its state, while Nevada’s more specific definition shows an intent to buy. Nevada also doesn’t require a data opt-in, while California does. These logistics affect data collection, data storage – redefining people as they purchase and opt in or opt out – and data targeting.
The IAB recommends that brands implement a data privacy management platform such as TrustArc or TrustRadius, but there are logistical issues there, too. For media buying, for instance, does the agency take responsibility for porting data through the privacy platform in real time?
While less legally sensitive, contextual targeting is not simple. Like everything else in digital advertising, there are layers of sophistication that media buyers will need to grapple with as they make their move. And that’s a good thing, because it means they will have the opportunity to create a unique approach for their brands.
Contextual targeting is data-driven, too
There are no looming regulatory issues around contextual targeting. And context is a concept that many brands, and even regular consumers, are very familiar with.
But for brands looking to replace the granular control they get with data targeting, contextual offers a surprisingly sophisticated option that many media buyers have not fully tapped into.
MediaMath, for example, recently announced a new contextual video advertising product with IRIS.TV. This offering helps brands deliver ads against contextually relevant content in real time. This capability is only possible because IRIS.TV has integrations with publisher content management systems and can evaluate lots of metadata and keywords very rapidly.
Last year, Channel 4 in the United Kingdom debuted an AI-driven contextual ad product called Contextual Moments that helps brands place ads near relevant scenes in TV shows using audio and visual linear elements.
Products like Placements.io can be customized to help publishers feed contextual data to advertisers to buy in real time. Publishers may have thousands of different products with all sorts of different contextual elements to tap into, and each publisher is very different, requiring sophisticated technology to normalize it all for the online media market.
The platforms have been profiting from contextual targeting for longer than they have had data targeting. Google still makes a huge profit from search advertising that is mainly based on keyword data. Same with YouTube, where the vast catalogue of content is organized with layers of contextual data such as categories or keywords.
Brands have not scratched the surface with the different ways they could be using contextual targeting. For example, many content creators and influencers on social platforms have a treasure trove of insights about how their content performs with different audiences, and why. And yet, few brands have tapped into this knowledge for a more relevant approach.
Similarly, publishers have long offered insights about the performance of their own content without many takers, as third-party data segments were easier to use on the open exchanges.
These opportunities are heating up. Not only does contextual targeting offer value in the current market, advances in predictive AI models are emerging to deliver even more real-time, scalable opportunity. Today’s contextual targeting requires a technical approach plan and willing partners that will embrace the opportunity to dive deeper with individual creators, publishers and platforms to get maximum value.
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