Why AI means the return of contextual targeting


The slow death of the third-party cookie means that contextual targeting will become increasingly important – and marketers should use the insights they generate from current cookie data to inform their future contextual strategies, an industry specialist advises.

In a WARC Best Practice paper, Ben Plomion, Chief Growth Officer at media and tech company GumGum, explains that contextual targeting is making a comeback, as brands use it to find new ways to reach audiences, and publishers use it to communicate the value of their inventory.

All this is taking place, he says, “at a moment when transformation is not only welcome, but necessary”.

That’s because privacy legislation is forcing publishers and advertisers to develop digital advertising strategies and technologies that are not dependent on user tracking and third-party user data sources. And platforms like mobile and OTT have never been friendly to audience-tracking through cookies in any case.

“Contextual is one strategy for targeting in an increasingly cookie-less world, and, thanks to advances in machine learning and other technologies that make large scale content analysis possible, it is perhaps the ripest for the picking,” Plomion states.

The notion of contextual advertising – reaching relevant audiences by serving advertising either a) adjacent to content that is product and/or brand-relevant or b) adjacent to content customarily consumed by a target audience – is hardly new, although it’s been overtaken during the past decade by the rapid rise of programmatic and cookie-based targeting.

During that time, however, context has continued to quietly evolve in the background, thanks to technological advances and the development of industry standards for contextual categorization.

Plomion cites the Interactive Advertising Bureau’s Content Taxonomy (1.0 in 2015, 2.0 in 2017), which works in conjunction with its OpenRTB protocol to give providers the ability to target on context and audience simultaneously within a programmatic bidding environment.

Today, he says, contextual targeting capabilities are advanced because AI and other technology can be used to:

• discern web page sentiment

• understand the nuance of language

• ascertain the content and tone of images and video

• automatically configure ad creative to complement context

That means that advertisers can begin deploying contextual targeting techniques in conjunction with audience targeting to maximize the value of the ad market today, while preparing for tomorrow.

This article first appeared in www.warc.com

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