Contextual In Context: The Role Of Contextual Targeting In A Post Cookie Era

By Aqilliz  

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Contextual advertising has been around for nearly two decades, but over the years, the promise of big data and behavioural targeting has pushed it to the bottom of the modern marketer’s agenda — until now. With the impending elimination of third-party cookies and deprecation of IDFAs likely to impact measurement and attribution, brands need to take steps to ensure they don’t get left behind. A study conducted by GumGum and Dentsu Aegis last year found that digital advertising campaigns which employ contextual targeting are more cost-efficient than behaviourally targeted campaigns.

Faced with tighter advertising budgets and major privacy changes to the advertising ecosystem, the opportunity for contextual to take centre stage has never been greater. As behavioural targeting becomes more challenging, contextual targeting will become increasingly important in a world where user-level data has been reduced. Centred around the context and meaning of advertising environments rather than the online behaviour of consumers, contextual targeting is a way to deliver personalised ads while remaining privacy-compliant. For that reason, advertisers are starting to look at ways they can push contextual targeting beyond its current capabilities and how that fits into their marketing toolkit.

Context is Critical Currency

Given the industry’s collective move towards privacy-first advertising strategies, it’s now more important than ever to find inventive ways of understanding the context of an ad placement to drive more creative targeting. By analysing information such as search terms, key phrases, and topics, contextual advertising determines the most relevant environment in which to engage consumers with a particular creative message — for instance, running an ad for laptops on CNET or in the technology section of the New York Times.

In the digital world, contextual targeting can go much further than textual analysis and targeting for appropriate media placements. Brands can get very granular with context by targeting video metadata, titles, and descriptions, related keywords, audio transcripts, and even comments within and surrounding content. All of these additional data points give contextual targeting some of the benefits of behavioural targeting, by drilling deeper into the things consumers are actively looking for when they search for content. By mining these signals, brands can deliver even more personalised messages to their consumers.

Furthermore, the use of machine learning and AI-powered technologies today provides a more accurate understanding of content. This means brands can now target their audience in a brand-safe way, through sentiment analysis and image mapping.

From Brand Safety to Brand Suitability

In an era of misinformation, hate speech, and COVID-19, the politically and economically volatile landscape today has made brands ultra-sensitive to where their ads are placed. With the prevalence of ad fraud in programmatic advertising, brands are having to pull their ads from inappropriate contexts and platforms — and amid a climate of increasingly controversial news and content, these pitfalls are rising.

Contextual targeting solves this issue, ensuring brand safety by analysing content and excluding placement on verticals and content deemed to be unsafe. What’s more, technological advancements today allow advertisers to go beyond keywords to understand the nuances and sentiments of a page to better determine its relevance and safety.

While brand safety is about protecting a brand’s reputation online by not placing their ads next to inappropriate content, brand suitability on the other hand looks at matching a brand’s values to the context of the content that might surround their ads. In addition to protecting brands from appearing next to unsafe content, brand suitability provides more granular control of content adjacencies. For example, avoiding placing a travel ad next to a news story about a plane crash — which is technically related to what you’re selling, but unsuitable in terms of sentiment and context.

Contextual Intelligence: Tailoring to Sentiments

Sentiment refers to the general mood of the page, and is often inferred as positive, neutral or negative. Today, natural language processing allows for a deeper understanding of the context and can, more often than not, effectively discern the semantics and nuances of any given content. These capabilities allow advertisers to move away from keywords and whitelists, leaning instead on algorithms and AI to not just identify the most relevant content but also capture the consumer’s frame of mind.

For example, the goal of a luxury car ad is to appeal to the reader’s sense of exclusivity, status and aspiration — in this case, the ads may be placed entirely outside of the automobile context, but next to content that evokes those feelings. In addition to text analysis, machine vision can also analyse associated images and videos to understand their meanings. Audio can be analysed and understood, as well. This can add to the overall understanding of a page and give advertisers other inventory options, like in-video ads and OTT or CTV.

When it comes to contextual advertising, its value is in relevance combined with reach, safety, affordability, and ease of implementation. To succeed in the post-cookie, privacy-first era of digital marketing, advertisers need to be willing to evolve how they source, manage and utilise first-party data for personalisation and targeting. As the sun sets on third-party cookies, contextual advertising presents an alternative avenue of opportunity to engage consumers with relevant and personalised ads, in a brand-safe and privacy-compliant way.

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