Digital advertising relies on high-quality targeting to ensure that the right ads are delivered in the right place to the right audiences. For native ads, which match the editorial format of the publisher site and so, ideally, want to match the tone and content as well, correct targeting matters even more, writes Julien Verdier, CEO and co-founder, ADYOULIKE. 

That’s because the power comes from the editorial content and the native ad endorsing each other. Whereas in banners, and the like, the ad placement is next to the editorial and not inside. Content and ads stand apart and don’t endorse each other, which makes contextualisation less critical. 

But for native, context is everything. This is where AI comes in, and software like IBM’s ground-breaking Watson artificial intelligence platform can create vastly better semantic targeting for native advertising. The potential is enormous: even stronger than Google AdWords. AI in native advertising is a game changer.  

That’s because AI can give advertisers a big picture contextual and semantic analysis for every page where they've generated an ad. It provides these details in real time at huge scale, providing a relevancy percentage on keywords, entities, IAB categories (which are the industry’s guidelines and categorisations), concepts, sentiment of the page, whether it’s positive, negative, or neutral and emotions such as anger, disgust, fear, joy, or sadness.

This analysis, working on thousands of pages a second, means advertisers perfectly know the context of each and every page in their network and so can always serve the right ad in the right context. So, when a network like ADYOULIKE creates a native campaign, we agree with the advertiser on the relevant keywords it wants to be associated with and target those keywords when we run the ad.

For instance, if a brand is launching a new lipstick, we can target our publisher pages where the keywords 'lipstick', 'makeup', 'lips', and 'beauty' will appear. We can also target publisher websites matching the IAB category fashion/beauty/cosmetics/lipstick and pick only the pages that have a positive sentiment score above 70%.

AI software like Watson obviously wasn’t meant for advertising originally. However, the industry is beginning to realise its potential. It has an unrivalled ability to understand the content of a page in a very deep way, from emotions to sentiment, categories to keywords. This goes beyond regular advertising targeting, which is more about device, capping, and website and socio-demographic categories that are often poorly relevant. 

Everyone does regular targeting, but its limitations mean irrelevant ads and bad user experiences. This can be part of the reason that ad blocking is on the rise. 

The impact on publishers is going to be equally positive. Currently, they’re facing an uphill battle. The quality of ads that come from external partners and run on their pages must be high, as publishers know that their value lies in their editorial content and they don’t want it to be wasted by poorly targeted ads. Additionally, they can’t let ads that negatively impact on their brand to run, which is an issue that has been known to happen. 

Julien Verdier, Co-founder & CEO, ADYOULIKE

AI integration will mean publishers can set a blacklist to prevent any ads on pages that aren’t appropriate – such as dealing with sensitive issues about politics or war. And they can be sure that external ads will be targeted correctly, adding real value to the user’s journey. 

Programmatic is also going to transform. Combined with native, it led to native 2.0, which meant networks could serve creative ads at a huge scale. What AI integration means is that these creative ads will be served at scale, but will also be highly targeted to each individual user.

For example, providers will be able to understand the context of every page that a user browses, then for each page offer a semantic relevancy score that is aggregated along the user’s browsing journey. In the long run, based on a person’s web browsing, native ad businesses will know what they care about and like, and can make sure that the ads served to them are pieces of content and information that they will genuinely enjoy seeing and find useful.

This will mean that even banner and pre-roll video campaigns will be better targeted and offer an improved experience. In the long run, we are expecting a big uplift for the whole ad industry, not just native campaigns.

For more than twenty years, we’ve had to make do with poorly-targeted ad experiences. The advent of AI will create an environment where targeting understands not just what a page is saying, but how it’s saying it and why. Is it light-hearted or serious? Positive or negative in attitude? Are the reader comments on the editorial piece supportive or dismissive? Knowing the answer to those questions means serving the best and most appropriate ad every time.