It’s time to target interest, not identity
How would you describe yourself? You might say you’re a football fan, a parent or someone who loves running
The industry has changed drastically
Consumers are no longer unaware of the fact that the digital advertising industry is constantly collecting data, including a lot of personal information, about them every time they go online. In fact, it’s this awareness, and the apathy and dissatisfaction it creates, that is seen as one of the key factors in the dramatic transformation of the digital advertising industry.
Advertisers have been targeting based on stereotypes essentially since the very beginning. Just look at advertising during the rise of TV. Without any data to go off of, advertisers had to make sweeping generalizations about the audiences of the channels they were buying ad slots on; men watched sports channels, women were more interested in lifestyle programming etc. For many advertisers, this was often worth the investment, especially on more niche channels that attracted smaller but highly engaged audiences.
The emergence of the internet and especially the birth of the cookie saw this form of stereotype based but also somewhat contextual advertising fall by the wayside. Instead of generating proxies for their audience, brands could use the data they collected to generate a pretty good idea of the person on the other side of the screen, and where that person could be found.
The death of demographic targeting
In the last thirty years or so since cookies first emerged, advertising has devolved into a race to the bottom, where more and more data has been collected on consumers and time and resources have been poured into following users incessantly around the internet. Demographics and stereotyping have also been turned up to eleven, to the point where some adtech players are placing users into tens or even hundreds of thousands of increasingly narrow categories, from “picture perfect families'' to “tattoo addicts''. It’s simply too much.
When it comes to targeting, the line between being helpful and being intrusive is very thin, and it’s one that brands still need help to walk. Developing incredibly detailed profiles of users, based on this strict, narrow categorization, won’t cut the mustard. It’s time for a solution that is as nuanced as we are, and can allow brands to reach us based on what we are interested in in the moment, not what we might have been interested in in the past.
Contextual is more inclusive
In the last few years, contextual advertising has reemerged as the most viable solution for brands, especially as they look towards a cookieless future. The most modern forms of contextual are driven by AI and unsupervised machine learning and allow us to go way beyond standardization, both in terms of the audiences brands want to reach and the content they can target.
In truth, we actually know far less about each individual consumer but the reality is we don’t need to know. Demographic targeting and placing users into categories relies heavily on stereotyping, which can lead to missed opportunities. If we only focus on the users demographics suggest will be interested in our brands, we are potentially missing out on vast swathes of people who could also engage with our messaging.
Contextual targeting, on the other hand, targets based on a user’s interest, not their perceived identity. We don’t need to know who’s on the other side of the screen, what matters to us is what content they’re consuming, and what that means in terms of the brands they’re most likely to engage with. This means contextual targeting is a lot more inclusive.
Going beyond standardization
Strict standardization has also limited brands and adtech players when it comes to the content they look to target. Despite the recent technological advancements, contextual has been somewhat constrained by narrow standard categories. This has led to ads ending up within content that has no relevance to the brand and not being placed where it does.
However, adtech players on the bleeding edge of contextual have used AI and unsupervised machine learning to develop custom categories based on each brand’s brief, analyzing the relationship between editorial pages and placing ads only where they are relevant. This also gives brands the flexibility to narrow or expand the range of content they want to target, based on the requirements of the brief.
Human beings are complex and nuanced, and it’s about time advertising recognized that. Placing users into neat little boxes doesn’t work anymore, and only adopting a solution that takes these nuances into account will ensure brands are properly positioned for the cookieless future. Brands shouldn’t be scared, in fact it’s a golden opportunity to better engage with their existing audiences and reach new ones that they had previously never even considered.