With the phasing out of third-party cookies on the horizon for users of Chrome, the world’s most popular web browser, several alternatives are being proposed.
Key motivators:
- The writing has been on the wall for third-party cookies since the introduction of legislation like GDPR, which specifies that consumers should know who has access to their data and why.
- Apple’s Safari browser and Firefox both announced that they would block third-party trackers by default in 2019, followed by Google who said they would be “phased out” on Chrome over the next two years.
- “Users are demanding greater privacy – including transparency, choice, and control over how their data is used – and it’s clear the web ecosystem needs to evolve to meet these increasing demands,” said Justin Schuh, director of Chrome Engineering at Google.
The alternatives:
Trust tokens
Trust tokens are being proposed by Google as an alternative to third-party cookies.
- A trust token is non-personalized and cannot be used to track users across the web. They aren’t designed to replace the job of third-party cookies, but rather to stop ad fraud
- Its purpose is to distinguish between a real user and a bot using cryptographic signing. This would also stop tokens being forged
The catch: This deals with the authentication issues around removing third-party cookies, but doesn’t allow advertisers to track users or build up a picture of their identities. Without identity, there is no data targeting. Whether that’s a bad thing or not depends on where your interests lie in the ad ecosystem.
Conversion Measurement APIs
Conversion Measurement APIs are in the early stages of being developed and tested by Google, and Safari has also released an experimental feature. This is also known as ‘Privacy-preserving ad click attribution’.
- These APIs would allow advertisers to measure ad conversions such as purchases and attribute them to clicked ads without using cross-site identifiers like third-party cookies
- Ad clicks would be stored by the page hosting the ad, and conversions would then be matched against stored ad clicks.
Read more about this privacy-focused approach here.
FLoC and PIGIN
These two methods would enable interest-based advertising, but without having to individually identify users.
- Federated learning of cohorts (FLoC) would use on-device machine learning to group behavior by cohorts, which would enable advertisers to target by grouped interests rather than one-to-one. Thousands of people with similar browsing histories would be grouped into a ‘flock’, with various preferences and behaviors assigned to the group.
- PIGIN is a similar proposal, which stands for ‘Private Interest Groups, Including Noise’. The browser would place people into interest groups rather than the advertiser, and these groups could be used for targeting. There would have to be thresholds set on the minimum size of groups so this wasn’t exploited for microtargeting.
Learn more about the proposals for FLoC and PIGIN here.
The publisher’s perspective: Some publishers are taking matters into their own hands, either doubling down on first-party data solutions or developing their own targeting products.
- Conde Nast announced a cookie-less advertising solution called Obsidian last month which uses AI-powered machine learning to reach high-intent audiences with contextual advertising
- The Washington Post’s own ad tech suite Zeus is going from strength to strength this year. Just weeks ago, it licensed its performance adtech to Tribune Publishing and has partnered with the Local Media Consortium to optimize ad performance across 3,500 local media outlets.
The last word: Google acknowledges that a hard stop to third-party cookies is hugely problematic, and is pushing for an agreed-upon set of standards to draw a balance between privacy and targeting.
