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https://www.thedrum.com/opinion/2021/08/18/how-machine-learning-can-help-us-build-effective-contextual-advertising

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Yaroslav Kholod, director of programmatic operations at Admixer, explains what the industry must do to build a convincing contextual advertising infrastructure capable of taking the pressure off the soon-to-be dismantled third party cookie.

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How machine learning can help us build effective contextual advertising | The Drum back to thedrum.com Advertisement Skip to content Contextual Targeting Media How machine learning can help us build effective contextual advertising Share Twitter Linkedin Email Facebook Facebook Messenger Whatsapp Reddit Flipboard By Yaroslav Kholod August 18, 2021 | 6 min read Listen to article 4 min Yaroslav Kholod, director of programmatic operations at Admixer, explains what the industry must do to build a convincing contextual advertising infrastructure capable of taking the pressure off the soon-to-be dismantled third party cookie. Across the digital marketing world, you hear the sound: advertisers are on the march towards a land beyond cookies, prompted by consumer demand for increased privacy, Google’s promised cookie shut-off and the efforts of companies such as Apple to curb excessive targeting.What brands hope to find in this promised land are new ways to reach audiences. Contextual advertising – the privacy-first targeting method that displays relevant ads based on the content of a web page – is a source of particular excitement, and I share that feeling too.Context, of course, was the means by which ads always used to be targeted, both in traditional media and in the early days of the web, before ID-driven targeting triumphantly – and, as it turns out, temporarily – rewrote the game.In recent years, however, machine learning has dramatically boosted the potential of this old favorite, unlocking the opportunity

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