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News | With AI’s Help, Native Can Mean More Than Made For Advertising Links

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With AI’s Help, Native Can Mean More Than Made For Advertising Links

197 Views / Article by Advert On Click / 5 January 2024
Source: adexchanger
With AI’s Help, Native Can Mean More Than Made For Advertising Links

Ask 10 people in digital advertising what “native” ads are, and you’ll get 10 different answers. 

But the recent controversy around spending on made-for-advertising (MFA) sites shined a light on a dark corner of the native advertising universe: MFA articles placed in the so-called “chumboxes” that appear in the footers of premium news sites.

At its best, native isn’t just different from these low-quality content links; it’s antithetical to them. As the name suggests, the category should refer to sponsored content that feels consistent with the high-quality publisher content surrounding it. If a native ad runs on the site of a premium news publisher, it should be authoritative, engaging and visually appealing – just like the editorial content.


Native advertising needs a redefinition, not just for the sake of advertisers and publishers but also for consumers. Let’s consider what native can be, why it matters for the three key stakeholders in digital advertising and how recent advancements in AI can help native advertising meet its potential.

What native advertising should be

Most ads, especially display ads, leave a lot to be desired. They take over the screen with an image that feels jarring in contrast to the content the reader is trying to consume. 

For example, when I navigate to a premium business publisher news site, an ad for Latin American tourism interrupts my experience. Such messaging has nothing to do with the mindset I’m in when I’m trying to read up on business developments. 

Native exists to solve this problem. The publisher should be able to connect advertisers with audiences who are primed to be receptive to the sponsored message based on the content they’re consuming. 

And not only should the ad make sense in context, but it should also seamlessly blend into the content environment instead of wrenching the audience out of it. Native ads can accomplish this by dynamically optimizing creative to match the style of the publisher, down to font and color scheme.

Ad tech, including AI, powers native innovation

After more than a decade of essentially unrestricted data collection, the industry is refocusing on ways to drive ad performance that aren’t linked to individualized tracking. Creative, which has been the cornerstone of good advertising for decades, is a good place to start.

Through the use of AI, native can be a key element of that creative renaissance, realigning advertising with the high-quality content environments that are the backbone of the attention economy. 

For example, AI is fueling advances in dynamic creative optimization (DCO) that are especially relevant to native advertising. 

Historically, DCO has entailed the customization of ads based on advertiser-identified components. A brand might develop three different headlines, images and sets of copy for an ad. With DCO, the advertiser can identify the one of those 27 combinations that is most likely to drive conversions for a specific audience at a specific time.

AI enables this type of optimization at greater speed, scale and scope. Advertisers can optimize ads based not only on a few predetermined parameters, but also on advertiser KPIs, while seamlessly blending their creative into publisher environments at programmatic scale. Advertisers can generate thousands of different ad experiences tailored to blend in with each publisher’s content without the pain of custom integrations. 

This innovation also extends to advertising’s medium of the moment, CTV. CTV ads are generally anything but native. They feel like old-school TV commercials, divorced from the context in which they appear and undermined by frequency-capping issues. 

But recent advancements in large language models and compute power have made the data-intensive CTV medium accessible to AI, in turn enabling the same next-generation DCO that learns from the content surrounding it and optimizes for both the user experience and ad performance. 

The explosion of interest in AI means now is the perfect time for advertisers, publishers and their technology partners to reimagine the potential of native. 

As digital advertising continues to evolve alongside AI, native should be about making advertising experiences as immersive and engaging as the content environments in which they appear – not shuttling traffic away from these environments and toward MFA sites.