Every adtech company says they use AI. But what really matters is what they can actually do with AI that they couldn't do otherwise and how it affects performance for advertisers.
To understand how AI drives better performance with contextual advertising, let’s review how most companies approach contextual targeting and how AI allows advertisers to generate better performance through more granular targeting.
How most companies do contextual targeting
Most companies use cookie-cutter taxonomies to facilitate contextual targeting. For example, they might borrow a taxonomy of roughly 300 topics, categorize content on the web based on those topics, and then use keywords to place their ads on content supposedly relevant to their audience.
This is a level of content analysis you don’t need AI to perform because the taxonomy is simple and unchanging, and the targeting mechanism is a simple question of matching advertising keywords to pages of content on which those keywords appear.
The problem with this approach is that it is insufficiently granular, which leads to irrelevant advertising and poor performance. For example, a travel advertiser using keywords to describe travel might end up advertising on a story about people fleeing natural disasters. Or a Bahamas hotel chain might end up advertising on stories that are about travel but have nothing to do with the Bahamas. That doesn’t exactly capture the dream of highly relevant contextual advertising.
Enter AI.
How AI helps Advanced Contextual drive higher performance
AI allows us to process vast swathes of information at a scale and pace impossible for humans. This allows us to do two things.
First, we’ve used AI to develop and leverage a much more granular taxonomy of topics than most cookie-cutter taxonomies. Our taxonomy is 1,500 topics, and we’re able to use it to categorize content more finely, generating more relevant ad targeting and higher performance.
Second, we process 1 million auctions per second. That means we’re able to understand content much better, match the advertiser with a page and audience relevant to them, and drive conversions more efficiently than alternative solutions.
Finally, we use AI to generate synonyms for our advertisers’ keywords. Using generative AI allows us to develop a consistent, rigorous strategy for each client instead of allowing each human team member to freestyle when developing the keywords that will facilitate ad targeting.
AI is neat. Driving performance is imperative
Every company should be straightforward about where and how they use AI — and also be able to show both how it works and the impact it generates. Let us know if you’d like to see our AI-driven solutions in action.