Google begins slow phase-out of third-party cookies, finally

Google finally took the first bite out of the third-party cookie on January 4, 2024. Around 1% of Chrome users globally, constituting roughly 30 million people, are now cookie-less, paving the way for a fully cookieless Chrome by the end of this year. This comes after multiple delays and false starts.

It’s a slow rollout, Google says, to give advertisers, publishers, and ad-tech firms time to “test our readiness for a web without third-party cookies”.

Safari, Apple, and Firefox beat Chrome years ago in cookie deprecation.

Google’s plan is to come up with privacy-focused alternative technologies for advertisers. The new Tracking Protection feature automatically cuts off a website’s access to third-party cookies.

Google Vice President Anthony Chavez said that the tech giant is taking a responsible approach to phasing out third-party cookies in Chrome. “If a site doesn’t work without third-party cookies and Chrome notices you’re having issues... we’ll prompt you with an option to temporarily re-enable third-party cookies for that website,” he added.

Though Google had announced the decision to do away with cookies from Chrome in 2020, the plan was postponed twice.

Google’s cookie deprecation announcement caused tremors in the ad world, triggering widespread scepticism about ‘Privacy Sandbox’ filling the gap. Fears abound that these untested substitutes will prove inadequate, further entrenching Google’s already-dominant position in online advertising.

Understandably, publishers’ online ad businesses rely heavily on the granular data gleaned from third-party cookies, enabling them to personalise ads and maximise revenue. Google’s replacements like Privacy Sandbox are raising concerns about their ability to deliver the same level of targeting and revenue generation.

And the industry is witnessing different technologies as alternatives to third-party cookies. Brands are slowly shifting to cookieless alternatives such as contextual targeting, geo/ location-based targeting, first-party data, etc., to target customers. All these are privacy-centric targeting methods.

Using AI and machine learning to analyse user behaviour patterns and make accurate predictions about user preferences without relying on individual user-level data.

AI and operational machine learning will be increasingly used to analyse user behaviour patterns and predict user preferences without taking recourse to personal-level data.

This is an ongoing process with no immediate answers. While challenges abound, the quest for a more privacy-respecting online advertising landscape is a positive step for both users and publishers. By fostering open dialogue and collaboration, the industry can hopefully navigate this transition and create a future where targeted advertising thrives alongside user privacy.