Feature
The Gist
- Contextual clarity. Contextual targeting emerges as a key player due to its relevance and scale, offering a viable alternative in the evolving programmatic advertising landscape.
- AI advancements. With AI's progress, contextual targeting now delivers nuanced and precise advertising, surpassing pre-AI capabilities in understanding audience interests.
- Expanding horizons. Contextual targeting's revival, fueled by AI, promises expanded reach and brand safety, challenging traditional targeting methods in 2024.
Brands evaluating targeting-at-scale options, including contextual targeting, for 2024 are already battling the quality versus quantity dilemma.
First-party data offers high quality but restricts reach to existing ecosystem members. While deterministic matching with first-party data is effective, it falls short in scale and isn't ideal for broadening audience reach in prospecting.
Third-party data offers scale but is increasingly constrained thanks to the cookie phaseout and brand safety concerns in terms of consent and ad placement.
Among the remaining programmatic options, advertisers can choose from demographic and geographic targeting to behavioral, device, and even weather-based targeting. But none of those options offers the blend of relevance and scale that contextual targeting does.
Will that be enough to help it make a comeback as the programmatic targeting option of choice?
What Is Contextual Targeting and How Is It Different From Cookie-Based Targeting?
Unlike cookie-based targeting, which uses past historical behavior of individual visitors, context-based audience targeting lets advertisers target ads based on the page, app, video, or audio content being currently consumed or the context it's being consumed in, without the use of cookies or alternative IDs.
While not new, it took a backseat to the "reach and scale" promise of cookie-based targeting.
Thanks to cookie deprecation and advancements in AI, however, all that is set to change.
Related Article: How Contextual Targeting Delivers Personalization Without Cookies
Cookie-Based Targeting Won the Last Round. What Will Change in 2024?
Contextual targeting is making a strong comeback thanks to advancements in AI which make a deeper analysis of video and content and content consumption signals possible.
AI-powered network analysis transforms what's possible with programmatic contextual, especially on key parameters valued by advertisers, says Albert Nieto Riera, co-founder and co-CEO of Seedtag, a contextual advertising company.
Heightened nuance and specificity: These real-time insights help brands target precise interests rather than broad stereotypes and capture audience attention at the moment that matters, to maximize campaign effectiveness.
For example, pre-AI contextual targeting might identify a piece of content as “an article that mentions toys in a parenting publication,” while advanced contextual technology today can specify that it is “an article providing advice for parents about the most sustainable and educative toys for children under 10.”
This offers several interesting insights about readers consuming that content. For instance, they are young parents, care about sustainability, and seek more learning-oriented toys, etc. This information can be leveraged to improve contextual targeting for other categories, such as sustainable home care products, ethical clothing brands, activity-based learning products for children, etc.
Daniel Lee, VP of product, demand, and data solutions at immersive online advertising solutions provider Emodo agrees that contextual targeting capabilities have evolved way beyond keywords and themes, adding that advances in natural language processing (NLP) and machine learning (ML) algorithms have increased the ability to accurately interpret the meaning of text, images and videos.
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“Interpretation of the same content varies across audiences. The ability to analyze video or audio content and draw out its true meaning through context was not possible in a scalable way before AI. By marrying content and audiences, AI generates contextual messaging that drives the highest ROAS for brands,” he suggests.
Improved Ad Efficiency
AI improves not only the quality but also the efficiency with which content can be classified because ongoing insights lead to a virtuous cycle of iteratively smarter contextual targeting. Because AI-driven image and speech recognition can go beyond the content objects or subjects and also extract emotions, settings, sentiment, demographics, contextual understanding, etc. within the video or audio content, further personalization and customization of the ad experience is possible, says Lee.
Real-Time audiences
Real-time analysis of web content and how audiences interact with that content ensures relevant and up-to-date audiences that evolve based on network-level insights. This “in-the-moment” understanding of the viewer’s preferences and behaviors powered by AI also improves the ability to dynamically optimize ad creatives based on real-time contextual data.
Expanded Reach
Current digital advertising practices are skewed toward optimizing transactions and KPIs for existing clients, neglecting the acquisition of new customers — and this skew toward known audiences will only intensify in a transition to first-party data, says Riera.
Prospecting for New Audiences
Today, prospecting for new audiences is done with various forms of deterministic audience extensions — matching first-party data with another data set in a secure environment (like a clean room) and then activating against that data. “It can be resource-intensive and involve significant privacy risk, and the scalability of such deterministic targeting is limited by the size of the original customer file,” he argues.
Contextual targeting can be a more transparent, effective, and unbiased way of finding new customers. AI will identify the territories, sub-territories, and keywords inside each of these sub-territories that have relevance for the brand and its message. Contextual targeting can capture these affinities in a way that demographic and behavioral data often miss — and some of the results are counterintuitive to the human biases or assumptions inherent in those datasets.
Contextual intelligence, he adds, provides not only a means for finding new customers but also a means for learning more about their interests while challenging false assumptions about what the “right audience” really looks like.
Brand safety: Ad placement impacts both — brand perception and reputation. AI-powered contextual targeting is based on a content and context analysis of a page, so brands can ensure ads are displayed in a brand-safe environment while optimizing relevance for the audience.
Related Article: How Retail Media Is Powering Smarter Contextual Marketing
Effective Ad Targeting in 2024 Still Needs a Balanced Portfolio
Despite its strengths, contextual targeting is not an either-or choice. Advertisers seeking to improve overall ROAS still need a balanced portfolio of “reach at scale” targeting options in 2024, suggests Lee.
Advertisers should test various targeting methods to build audiences, including
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Traditional ID-based targeting: Where an ID or cookie still exists, it should still be used and leveraged
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Leading alternative identifiers: RampId, UID2 or ID5 help increase scale beyond just cookies or mobile ad IDs
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Contextual targeting: Targeting based on the content of a site, app, video, or audio, and signals based on how audiences interact with or consume that content
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Geo-contextual targeting: Especially useful for environments such as CTV, where identifiers are either highly fragmented or limited in scale, geo-contextual targeting based on location can be an effective way to reach desired audiences without an identifier
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Predictive audiences: This can mean many things to different people, but at Emodo, says Lee, it is an AI-driven approach to predict which audience segment a bid request might fall into based on the combination of signals that are seen within the bid request and derived attributes
Every marketer will need to embrace a combination of deterministic, probabilistic, and contextual targeting methods to reach their audience across platforms, agrees Riera. Experimenting to find the right balance will be key, especially given the omnichannel reality and the fact that every channel, when measured properly, has shown to be a legitimate vehicle for performance — even linear TV and print.
Related Article: Contextual Advertising: What You Need to Know
Are Publishers Ready for the Contextual Advertising Opportunity?
The shift toward privacy-focused advertising and cookie deprecation will also make contextual advertising more relevant for publishers, especially as they look to maintain the addressability of their inventory.
With cookies gone, a handful of major publishers will be able to drive registrations or subscriptions and gather enough first-party data to support scaled campaigns, and many will rely on the alternative IDs to scale further, says Riera. But most publishers won’t be able to shift directly to first-party data alone, and even those that do can benefit from the kind of audience extensions offered by contextual.
In short, he predicts contextual targeting will become a critical support in maintaining cookieless addressability, and it will represent a substantially higher share of publisher income in 2024.
The best way for publishers to foster more effective contextual ads, recommends Lee, is by developing comprehensive contextual targeting categories from which advertisers can choose. The ability to overlay contextual data with user behavior data for new or united seller-defined audiences will also be key, he finishes.
