Google says it is considering building APIs into its Chrome browser that make it possible for advertisers to more clearly measure ad click conversions – a move likely to be welcomed by industry, but which has drawn fire from civil society groups.
In a series of six proposals last week the company (which generated over $30 billion in advertising revenues in the past quarter) introduced what it has dubbed a “Privacy Sandbox”, or “set of open standards to fundamentally enhance privacy on the web.”
Google “Brainstorming” a Post-Cookie World
While privacy is, ostensibly, the focus of the initiative, campaign group the Electronic Frontier Foundation (EFF) described the proposals as “Google brainstorming ways to continue serving targeted ads in a post-third-party-cookie world”, as user and regulatory concerns about the detailed information cookies used for targeted ads.
In a blog post, Justin Schuh, Chrome’s engineering director, said: “Some ideas include new approaches to ensure that ads continue to be relevant for users, but user data shared with websites and advertisers would be minimized by anonymously aggregating user information, and keeping much more user information on-device only.
“Our goal is to create a set of standards that is more consistent with users’ expectations of privacy.”
He added: “We are following the web standards process and seeking industry feedback on our initial ideas for the Privacy Sandbox. While Chrome can take action quickly in some areas… developing web standards is a complex process, and we know from experience that ecosystem changes of this scope take time. They require significant thought, debate, and input from many stakeholders.”
Could New Chrome APIs be the Ads Conversion Holy Grail?
A Conversion Measurement API
The proposed approach would see API-based technologies built into Chromium (and conceivably other browser engines, if industry adopts the suggestions) that allow advertisers to mark up their ads with metadata like a destination URL, a reporting URL, and a field for extra “impression data”.
The browser would then store this metadata in an ad table, and fire off a conversion for a given reporting domain through an HTTP GET when the user goes on to that specific advert’s url; a limited proxy for advert conversion.
The impression data field would contain a hefty 64 bits of information, allowing advertisers to attach a unique ID to each and every ad impression they serve, and, potentially, to connect ad conversions with individual users.
(This would, in theory, allow advertisers to build detailed pictures of browsing habits. Google hedges on this, saying: “Adding or removing a single bit of metadata has large trade-offs in terms of user privacy and usability to advertisers. Browsers should concretely evaluate the trade-offs from these two perspectives before setting a limit. As such, this number is subject to change based on community feedback.)
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As the advertising giant says of the proposals in an explainer posted in a GitHub repo: “A new API surface can be added to the web platform to satisfy [ad conversion/user tracking] use-case without [cookies], in a way that provides better privacy to users.
“This API alone will not be able to support all conversion measurement use cases, such as view conversions, or even click conversion reporting with richer / more accurate conversion metadata.
“We envision this API as one of potentially many new API’s that will seek to reproduce valid advertising use cases in the web platform in a privacy preserving way. In particular, we think this API could be extended by using server side aggregation to provide richer data”.
A detailed technical explanation of the proposal can be found here.
FLoC: “Interest-Based Advertising” or a “Digital Tattoo”?
Among its other proposals, a mechanism that would let Chrome user “Federated Learning of Cohorts” (FloC) to group together people with similar browsing habits into small cohorts. This would let the browser underpin “interest-based advertising”.
As Google puts it: “Browsers would need a way to form clusters that are both useful and private: Useful by collecting people with similar enough interests and producing labels suitable for machine learning, and private by forming large clusters that don’t reveal information that’s too personal, when the clusters are created, or when they are used.
“The browser uses machine learning algorithms to develop a flock based on the sites that an individual visits. The algorithms might be based on the URLs of the visited sites, on the content of those pages, or other factors. The central idea is that these input features to the algorithm, including the web history, are kept local on the browser and are not uploaded elsewhere — the browser only exposes the generated flock.”
The “flock” would update and optimise over time as its members traverse the web, with the value made available to websites via a Chrome client hint; a set of HTTP request headers that allow content to be delivered according to local conditions like device or network.
Bold, But Potentially Controversial
For a series of proposals based around the titular Privacy Sandbox, the proposal went down like a lead balloon with the privacy-focussed EFF, whose Bennett Cyphers wrote this Friday: “The problem with FLoC isn’t the process, it’s the product.
“FLoC would use Chrome users’ browsing history to do clustering… In Google’s proposal, users would then share their flock name, as an HTTP header, with everyone they interact with on the web. This is, in a word, bad for privacy.
“A flock name would essentially be a behavioral credit score: a tattoo on your digital forehead that gives a succinct summary of who you are, what you like, where you go, what you buy, and with whom you associate. The flock names will likely be inscrutable to users, but could reveal incredibly sensitive information to third parties. Trackers will be able to use that information however they want, including to augment their own behind-the-scenes profiles of users.”
To advertisers however, in a world in which cookie blockers are growing in popularity, moves by Google to make it simpler and more transparent to identify user behaviours and ad campaign impact down to granular conversion rates would be only too welcome.
A detailed technical explanation of the proposal can be found here.
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