Contextual 3.0: Why the future of advertising is already here

As the advertising industry continues to highlight the importance of respecting consumer privacy, you’re going to read countless think pieces about “new” measures that are coming to shake up targeting for a cookieless world

For me, the most sustainable, effective and most importantly future-proof solution is nothing new: it lies in the roots of advertising, where targeting was strictly contextual, going as far back as cave paintings and hieroglyphics.

Contextual advertising is the only form of targeting that is truly focused on protecting consumer privacy and supporting an open and vibrant internet.

Contextual is also much more inclusive, as it allows brands to reach their desired consumer without excluding people based on declining data match rates or personal data, whether good or bad.

Contextual 2.0: Machine learning and AI

Until around a decade ago, contextual advertising consisted solely of targeting certain keywords and discarding others. However, in these last few years, players have brought innovative solutions to market that have significantly improved the way brands do contextual targeting. This has allowed for a much deeper and more accurate understanding of content.

Natural language processing models (NLP) offer a precise sentiment analysis, going beyond keywords and understanding the true meaning of content. Think of the word “crash”; NLP models can infer that “crash” has a negative connotation in an article about road safety but doesn’t in a piece talking about the most recent Grand Prix.

These tools have significantly improved contextual targeting’s effectiveness, and have greatly helped advertisers when it comes to brand safety. Not only do they guarantee that ads don’t appear alongside inappropriate content, but also that ads are aligned with the tone and sentiment of an article.

Contextual 3.0: Comprehensive analysis and greater personalization

As advertisers continue to allocate more and more attention and budget to contextual advertising, they are putting themselves in position to take advantage of the new wave of innovation in contextual technology.

Rather than just targeting specific URLs and being limited to predefined categories, new contextual technologies developed by Seedtag are capable of analyzing a whole universe of content (network level analysis). This holistic analysis of the entirety of the network allows us to understand trends within content and the key topics that consumers are engaged with at that moment.

Combining this analysis with advanced unsupervised machine learning models allows us to offer the most effective personalized targeting for each campaign. We can take a client’s needs into account, scanning the entire network of URLs to target the most relevant articles to the campaign brief. This means the campaign is directed only towards the most relevant audience.

But it’s also scalable. While the combination of network level analysis and machine learning creates a very specific custom AI category for each campaign, we can expand this to increase the size of the audience the brand can look to target, while still ensuring a high level of precision.

In short, this development is redefining the concept of campaign affinity, ensuring ads always appear in the most appropriate settings for each brand. This ensures the ad’s messaging and creative aligns perfectly with the tone and sentiment of each article or group of articles, effectively impacting consumers in the moment that they’re most open to that brand in real time.

Contextual: Flipping the industry on its head

Demographic segmentation has become problematic and obsolete. Having a predefined audience opens the door to prejudice and stereotyping, while ignoring those consumers that stereotypically don’t fit within the target group.

Brands shouldn’t see cookie deprecation as a threat but as an opportunity. As an industry, we need to recognize the need to change the way we reach our target audiences. Instead of targeting people, we should be targeting moments where users have shown that they’re interested in your product based on what they’re doing or consuming at that moment.

We can only unlock the true potential of AI-driven contextual targeting when we integrate three key pillars: high-quality inventory, personalized creatives and the most advanced technology. Therefore, brands need to find solutions that leverage consumer-focused creatives while also supporting high-quality journalism. Combined with the most sophisticated contextual targeting and personalized machine learning models, advertisers are finally able to develop bespoke campaigns while avoiding stereotyping and respecting user privacy.