Contextual targeting is a form of advertising which matches digital ads to the most relevant websites within the display network based upon keywords and topics of a web page.  In short, it maps ads to the websites and web pages with the most direct relevance to the product, service or whatever else is advertisers are promoting.

Artificial Intelligence (AI) and Machine Learning (ML) have made contextual targeting much smarter.  Recent advances in AI/ML can now deliver highly accurate categorization and understanding of web content across a growing number of languages. Sophisticated algorithms enable machines to achieve a deeper level of understanding and better identify content topics, sentiment analysis, and even nuances such as homonyms.  The increased level of sophistication work to mitigate the risk of mismatched content and ad placements to protect and maintain brand safety.


Contextual Intelligence

Recent studies show the next generation of advertising, focused on contextual intelligence, is poised to eclipse behavioral targeting. Contextual intelligence allows advertisers to combine the relevancy of contextual targeting with key first-party data to serve the right digital ad, to the right person, at a time/place which is relevant to the other information being consumed — maximizing the opportunity for engagement and memorability.

Rise of Contextual Targeting—Why It's Here to Stay.

The Rise of Contextual—And Why it’s Here to Stay

Less than a decade ago, contextual was poised to dominate online advertising—delivering on the promise of providing relevant ad content to the consumer at exactly the right time. Over the past several years, the industry has taken a long and costly detour down the audience/behavioral path, only to hit what is increasingly looking like a dead-end due to regulatory, privacy, technical, and other issues. Now, the pendulum is rapidly swinging back to contextual.