Andrew Morsy, MD UK at Sizmek, considers the attractions of AI-powered contextual advertising in a post-GDPR world.
In the past quarter of a century, the world of advertising has become almost unrecognisable. Explosive growth in digital media spend has produced a rich, diverse digital marketing landscape. And digital has clearly become the dominant force across the ad market, with £11.55bn spent on digital advertising in the UK in 2017 alone – far out-ranking print and TV advertising. The reason behind this lies in the wealth of data created from digital sources that enables marketers to target their audiences like never before.
Although contextual targeting has always had a slice of the media planning cake, its value was typically outweighed by audience-based targeting; but in recent years, context has become far more important to brands and agencies. An ad that is not displayed in a contextually-accurate environment is not only a waste of advertising spend, it can also lead to embarrassing – or even worse, brand-damaging – placements alongside inappropriate content online.
A clear example of this was the 2017 brand safety scandal involving internet giant YouTube. Ads were found to be appearing next to extremist content, which led a whole host of publishers and brands to turn to contextual targeting as a way to avoid such placements.
When we look at the reason for the rise in contextual targeting on the buy-side of the advertising equation, we can clearly see the impact of the General Data Protection Regulation. While there were widespread concerns that the GDPR would decimate the digital advertising industry, there has in fact been a rise in demand for risk-free buying options. As a result, contextual advertising has seen a happy increase thanks to its precision, and by 2030, is expected to be worth almost $300bn (£232bn) globally.
So, how does contextual targeting work to solve advertisers’ digital headaches? The key to its success lies in artificial intelligence (AI) which analyses words and phrases, and the relationships between them to fully understand the context and category of any webpage. It can help brands achieve sophisticated targeting to reach audiences in the right time and place —without the need for cookies or opt-ins and consequently, is becoming increasingly appealing to brands and agencies.
AI not only understands how consumers interact with advertising, but it can apply this understanding faster and more accurately than a human ever could. It presents an ideal solution to the challenge of audience and context.
A surge in contextual targeting
The struggle with digital advertising lies in striking a balance between audience and context. Often you can achieve one, but not the other; our recent study in fact found that more than seven in 10 marketers in the US and Europe agreed with this statement. Consequently, the vast majority (81 per cent) admitted they don’t even try to target both, arguing that doing so negatively impacts the scale and performance of campaigns.
If matters did not seem complicated enough, marketers must also contend with a crowded landscape of suppliers, partners and agencies in the digital media space. Almost two-thirds of marketers agree that there is simply too much complexity – and with the introduction of GDPR, there’s yet to be even more as brands and agencies continue to find their footing in the new data privacy landscape.
Despite facing these complexities, the majority of marketers still believe that achieving both audience and contextual targeting at scale is a critical priority in the coming year; many of whom also plan to improve their contextual targeting capabilities in the same time frame. The ideal, it seems, is still worth striving for.
Creating context at scale
Our study also found that almost nine in 10 brands are looking to scale up their contextual capabilities – as long as it’s not at the cost of performance. In order to make this a reality, they will have to work hard at customer acquisition. And while gaining new customers is no easy feat, it can be made less complicated with contextual targeting, which uses algorithmic models based on contextual campaigns to create custom lookalike audiences with similar patterns of behaviour.
In doing it this way, brands can extend the reach of the campaign to new consumers and find audiences at the lowest media cost – which explains why almost nine in 10 marketers intend to use contextual targeting in their upcoming campaigns.
AI is also another indispensable tool in the contextual targeting process, with more and more marketers wanting tech at the heart of their campaigns. And the beauty of it is that there’s more to it than the automation itself – the same survey revealed that over eight in 10 believe that by automating workflows, AI frees time up for marketing staff to focus more on value-generating tasks. This likely explains why over eight in 10 marketers plan to increase the use of AI technology in digital display advertising over the next 12 months.
Right audience, right context
While personalisation and audience data can tell a brand who someone is, it is context that builds a picture of the frame of mind and receptiveness of an individual at the time at which they’re delivered a certain ad or brand message. As well as this, brands that use AI to build their digital advertising strategy will be better placed to evolve alongside changing technologies, platforms and models.
And more importantly, AI can lead brands through the vast quantities of first- and third-party consumer data, to help them segment their target audiences more accurately, and consequently align the characteristics of their current consumers with the consumers they hope to target in the future.
Ultimately, an AI-driven solution enables brands to define who their real audience is, as opposed to the pre-defined, vague segments they may have relied on previously. By doing so, it provides answers to the industry’s biggest question about context vs audience which is, ultimately, that you can achieve both.