Internet platforms · Deep dive
Third-party cookies became the open web’s portable identity layer: a small browser mechanism that helped advertisers recognise, value and measure audiences across unrelated sites. The debate is now about far more than cookies—it is about who may observe behaviour, who controls identity and which businesses can still prove that advertising worked.
The argument in five points
A third-party cookie is a context, not a special file type. It is ordinary cookie state used when the cookie’s site differs from the page in the address bar.
Its economic value came from portability. The same identifier could be recognised across many publishers, supporting audience targeting, retargeting, frequency control and conversion attribution.
The browser market is fragmented. Safari blocks third-party cookies, Firefox confines them to separate site-specific jars, and standard Chrome retains user choice rather than blocking them by default.
No single replacement reproduces every job. First-party relationships, contextual signals, clean rooms, server-to-server connections, experiments and modelling each solve a different part of the problem.
Privacy reform can alter competition. Restricting cross-site identifiers reduces surveillance, but can advantage companies with large logged-in audiences, proprietary commerce signals or control of the browser and ad stack.
1. What exactly is a third-party cookie?
A cookie is a small name–value record that a server asks a browser to store and return on eligible later requests. It can preserve a login session, a shopping basket, a language choice or an advertising identifier. “First party” and “third party” describe the context in which that cookie is used—not two different cookie formats.
If the cookie’s domain and scheme match the site shown in the address bar, it is same-site or first-party. If they differ, it is cross-site or third-party. A news page at publisher.example might embed an advert, video, analytics tag or sign-in component from service.example. A cookie sent to that embedded service is third-party in that visit. MDN’s current third-party-cookie guide uses this site-context definition.
The same cookie, two contexts
Visit service.example directly and its session cookie is first-party. Load the same service inside an iframe on publisher.example and that cookie is third-party. Company ownership does not decide the classification; the sites in the browser context do.
A cookie is also not the same thing as “all tracking.” A browser or server may recognise activity through account login, URL parameters, IP and device characteristics, local storage, mobile advertising identifiers, customer records or statistical inference. Removing third-party cookies closes one important channel; it does not make a service anonymous.
2. How one identifier follows a browser across sites
A simplified advertising journey
- EmbedSite A loads an image, script or iframe from AdCo
- Set or readAdCo stores or receives browser ID 7F3
- RecogniseSite B also calls AdCo, which sees ID 7F3 again
- Link outcomesAdCo associates impressions, clicks or conversions with that ID
The publisher does not need to redirect the person to AdCo. The embedded network request can carry the cookie when browser policy and consent permit it.
When the browser requests an embedded third-party resource, the third party may respond with a Set-Cookie header. On a later eligible request to that domain, the browser returns the cookie. To permit cross-site use, current cookie syntax normally requires SameSite=None; Secure. Secure protects transport over HTTPS; it does not make cross-site profiling private.
One ad-tech company rarely sees the entire market. Historically, companies matched their identifiers through redirects or server calls—a practice called cookie syncing. A supply platform might learn that its identifier A17 corresponds to a buyer’s identifier B94, allowing bid requests and later measurement to refer to the same browser. The result was an identity graph assembled across intermediaries, not one universal cookie.
Three boundaries matter. A cookie generally identifies a browser profile, not a verified human. Deleting cookies or changing devices breaks continuity. Shared devices can merge people, while one person using several devices can appear as several identities. Logged-in platforms may bridge some of those gaps, which is one reason account relationships became strategically valuable.
3. The five jobs third-party cookies performed
| Job | What the cookie enabled | What becomes harder without it |
|---|---|---|
| Audience addressability | Recognise a browser as belonging to a segment across many publishers. | Buying the same audience consistently outside large logged-in platforms. |
| Retargeting | Remember that a browser viewed a product or abandoned a basket, then bid for it elsewhere. | Person-level follow-up across unrelated sites. |
| Frequency control | Count how often the same browser saw a campaign across participating sites. | Avoiding repetitive ads across fragmented inventory. |
| Attribution | Connect an earlier impression or click to a later conversion. | Event-level, cross-site paths and long attribution windows. |
| Optimisation and fraud | Feed response histories into bidding models and detect repeated or suspicious activity. | Fine-grained training labels and cross-site anomaly detection. |
These jobs should not be collapsed into “personalisation.” Frequency capping can improve user experience; attribution helps budget allocation; fraud prevention protects both sides of a market. Conversely, the same portable identity can reveal visits to health, financial, political or other sensitive pages. The browser cannot infer the commercial purpose merely from the cookie.
Nor does attribution prove causality. A cookie can show that an exposed browser later purchased; it cannot by itself show that the advert caused the purchase. Incrementality requires a credible counterfactual, usually a randomised holdout or a carefully designed quasi-experiment.
4. Why the model became unacceptable
The central privacy problem is invisible reuse of state across contexts. A person may understand that a shop remembers its basket, yet not expect an advertising domain embedded in that shop to recognise the same browser on hundreds of other sites. The scale, duration and downstream combination of those observations make meaningful anticipation and consent difficult.
Cookie banners did not resolve the architectural problem. They moved a complex network of parties and purposes into a repeated interface that users often dismiss. The European Data Protection Board’s cookie-banner task-force report addressed common practices such as missing reject options, pre-ticked boxes and misleading link design. Browser restrictions instead change what the software permits by default.
In the UK, the rules cover more than cookies. The ICO’s final April 2026 storage and access technologies guidance applies PECR—and where relevant UK GDPR—to cookies, tracking pixels, fingerprinting, web storage, scripts and tags. Non-exempt access generally requires clear information and valid consent; strictly necessary and newer statutory exceptions are purpose-specific. A server-side implementation does not remove data-protection duties.
That last point is crucial. Moving a browser event through a first-party domain or sending it from the advertiser’s server may improve reliability and governance, but it can still disclose personal data to an advertising platform. “First-party,” “hashed,” “server-side” and “clean room” describe architecture or controls; none automatically establishes necessity, consent, anonymity or fairness.
5. What browsers actually do in 2026
| Browser | Default position | Practical meaning |
|---|---|---|
| Safari | Blocks all third-party cookies by default through Intelligent Tracking Prevention. | Authenticated embeds can use controlled mechanisms such as the Storage Access API; unrestricted cross-site state is not the norm. |
| Firefox | Total Cookie Protection gives third-party state a separate jar for each top-level site. | An embed can retain local state but cannot normally reuse the same cookie to follow the browser from Site A to Site B. |
| Chrome | Standard mode does not block third-party cookies by default; Incognito does, and users can change the setting. | Chrome abandoned a universal phase-out and a proposed standalone choice prompt. Availability therefore varies by setting and context. |
| Edge and Brave | Apply their own tracking-prevention policies. | Chromium engine lineage does not imply identical privacy behaviour. |
Safari’s tracking-prevention documentation states that ITP blocks all third-party cookies by default. Mozilla describes Firefox’s default Total Cookie Protection as a separate cookie jar for each site. MDN’s June 2026 browser summary states that Chrome blocks third-party cookies in Incognito or when the user explicitly enables blocking, not by default.
Blocking and partitioning differ. Blocking denies the embedded cookie. Partitioning double-keys it by both the embedded domain and the top-level site. With CHIPS, for example, a chat widget can remember state within one publisher without carrying that state to an unrelated publisher. MDN reports broad current support for partitioned cookies.
Browsers preserve escape valves for legitimate functions. The Storage Access API lets eligible embedded content request access to unpartitioned cookies, usually in a user-mediated, site-specific context. FedCM moves federated login towards a browser-mediated flow. These are functionality tools, not general replacements for cross-site behavioural advertising.
6. Chrome’s reversal and the rise and retreat of Privacy Sandbox
Chrome matters because browser policy can change the addressable supply available to advertisers and publishers. It also sits inside Alphabet, whose businesses include Google Ads, publisher tools, YouTube, Search and a large logged-in identity base. That combination made both the privacy design and its competitive effects unusually consequential.
| Date | What changed |
|---|---|
| January 2024 | Chrome restricted third-party cookies by default for 1% of browsers to support testing. |
| July 2024 | Google proposed user choice instead of universal deprecation. |
| April 2025 | Google retained existing settings and cancelled the planned standalone third-party-cookie prompt. |
| October 2025 | Google announced retirement of Topics, Protected Audience, Attribution Reporting and most other advertising-focused Privacy Sandbox technologies. |
| August 2026 | Google’s status page lists those technologies for deprecation or removal, while CHIPS, FedCM, Storage Access and state partitioning remain supported. |
Google’s April 2025 announcement is explicit that Chrome would maintain its current approach to third-party-cookie choice and would not launch a standalone prompt. Its October 2025 technology update cites low adoption and expected value when retiring the advertising APIs. The living feature-status page, updated 14 August 2026, separates the retiring APIs from supported privacy and identity primitives.
This history contains a wider lesson. A replacement needs more than technical availability. Advertisers, publishers, ad-tech intermediaries and browser vendors must integrate it; its privacy guarantees must survive scrutiny; its auction and measurement utility must justify cost; and competing browsers must converge sufficiently for the open web to rely on it.
7. The competition argument: privacy can redistribute power
The privacy case against unrestricted cross-site identifiers is strong. The competition question is different: if those identifiers disappear, which firms retain comparable information inside their own services? A logged-in search, social, video or retail platform can observe behaviour and outcomes in a first-party environment. A stand-alone ad-tech company or small publisher usually has a narrower view.
The UK’s CMA investigated whether Google’s original Privacy Sandbox plan could transfer important functions into Chrome and favour Google’s ad-tech services. After Google abandoned the Chrome-wide restriction and standalone prompt, the CMA concluded in October 2025 that those specific competition concerns no longer arose and released the commitments. This was not a finding that privacy and competition can never conflict; it reflected the plan Google ultimately chose not to implement. See the CMA’s case record.
The CMA’s 2025 testing summary offers a useful but time-bound counterfactual. In 2024 tests, publisher revenue per impression was around 30% lower without third-party cookies even when the then-current Privacy Sandbox was available. Results varied, retargeting-focused businesses were more exposed, and the CMA identified important limits: low adoption, participation imbalances, leakage between test groups and an evolving product. Google later retired the APIs. The result should therefore be read as evidence that signal loss had material economic value—not as a forecast of a future market that will use different tools.
The policy trade-off
Leaving portable identifiers unrestricted exposes people to cross-site surveillance. Removing them without interoperable substitutes can reduce publisher yield and strengthen large first-party platforms. A durable design must minimise information about individuals while preserving enough aggregate measurement, fraud control and market interoperability for competition.
8. What replaces the third-party cookie?
The answer is a stack, not an identifier. Each layer should be judged by the job it performs, the parties that receive data and the privacy risk it creates.
| Approach | Best suited to | Limit or risk |
|---|---|---|
| First-party accounts and consented data | Personalisation, customer relationships and measurement within a service. | Favours scaled services; sharing or matching still needs a lawful, understandable basis. |
| Contextual advertising | Choosing an ad from page topic, language, location or current session without persistent cross-site identity. | Less suitable for person-level retargeting, frequency or long conversion paths. |
| Publisher first-party audiences | Subscriptions, declared preferences and behaviour inside a publisher’s own properties. | Fragmented reach and uneven capability among publishers. |
| Hashed customer matching | Connecting an advertiser’s consented customer data with a platform’s logged-in accounts. | Hashing is pseudonymisation, not anonymity; match scale accrues to identity-rich platforms. |
| Server-to-server event APIs | Reliable conversion or product events despite browser loss. | Can move data collection out of sight rather than reduce it; requires data minimisation, consent and controls. |
| Data clean rooms | Joining protected datasets and returning constrained, aggregate analysis or audiences. | Governance, query controls and input legitimacy determine privacy; interoperability and cost remain issues. |
| Experiments and aggregate models | Incrementality, media-mix allocation and conversion estimates when event paths are incomplete. | Less granular; assumptions, calibration and confidence intervals matter. |
| Partitioned storage and access APIs | Embedded chat, payments, fraud controls and federated login. | Preserves functionality but intentionally prevents general cross-site reuse. |
| Private attribution standards | Aggregate campaign measurement with technical privacy guarantees. | Still evolving; does not recreate every targeting and optimisation use case. |
Google’s enhanced conversions illustrate identity-rich matching: hashed first-party customer data is compared with signed-in Google account data to improve measurement. Amazon Marketing Cloud illustrates clean-room collaboration: advertisers query pseudonymised Amazon Ads and their own signals, with only aggregate outputs available. Both can be useful, but both deepen the strategic importance of platform-held identity or commerce data.
The open-web standards effort continues. The W3C Private Advertising Technology Working Group, chartered through November 2026, is developing interoperable features for advertising with strong technical privacy assurances, beginning with private attribution. A working group and draft specification are evidence of serious coordination—not proof of universal deployment.
9. Who is structurally advantaged?
| Business | Structural position | What to watch |
|---|---|---|
| Alphabet | Search intent, YouTube engagement, logged-in Google accounts, Chrome and a vertically integrated ad stack. Enhanced conversions can match advertiser data to signed-in users. | Consent and data-use rules; relative performance of owned properties versus open-web tools; browser governance; independent measurement. |
| Meta | Large authenticated social surfaces and rich on-platform engagement reduce dependence on a third-party cookie for ad selection inside its apps. Off-platform conversion signals still affect measurement and optimisation. | Signal quality from advertiser sites, modeled conversions, regulatory limits on personalisation and advertiser return. |
| Amazon | Shopping, browsing, streaming and transaction signals sit close to purchase. Amazon Marketing Cloud and Publisher Cloud combine those signals with advertiser and publisher inputs under controlled queries. | Growth outside Amazon properties, clean-room adoption, data access terms and whether measured sales are incremental. |
| Large publishers | Direct subscriptions, registrations, contextual knowledge and premium inventory can support first-party audience products. | Authenticated reach, advertiser demand, yield versus consent rate and bargaining power with intermediaries. |
| Independent ad tech | Historically used portable identifiers to aggregate reach across many sites. | Alternative IDs, contextual models, publisher integrations, operating cost and differentiation without universal identity. |
| Advertisers | Own customer relationships and experiments become more valuable; smaller firms may lack data, engineering and statistical scale. | Dependence on platform-reported attribution, match rates, data quality, incrementality and consent provenance. |
Meta’s 2025 Form 10-K identifies loss of data signals, advertising consent and changes in measurement as material risks. Alphabet’s 2025 Form 10-K likewise says privacy practices and technologies that impede personalised advertising can affect its ad services. These are risk disclosures, not quantified forecasts.
The likely shift is from a relatively portable open-web identifier towards several controlled environments: publisher relationships, advertiser customer data, and large platforms’ authenticated graphs. That can improve accountability if data remains bounded and purposeful. It can also create new gatekeepers whose measurement claims are difficult for buyers to verify independently.
10. An investor and operator checklist
| Claim | Evidence to request |
|---|---|
| “We are cookie-less” | Which browsers, identifiers and flows? Does the system use accounts, email matching, device signals, IP addresses or fingerprinting? |
| “Our data is first-party” | Who collected it, for which purpose, what did the person expect, and to whom is it disclosed? |
| “The data is hashed” | Can it still be matched to a known account? What controls prevent reuse, re-identification and unauthorised queries? |
| “Server-side fixes measurement” | What additional events become observable, how is consent transmitted, and what remains modeled rather than observed? |
| “The clean room is privacy-safe” | Input permissions, minimum aggregation thresholds, query review, export rules, audit logs and who controls the environment. |
| “Performance is unchanged” | Randomised incrementality tests, holdout design, confidence intervals and results separated by browser and inventory type. |
| “Our identity is durable” | Authenticated reach, match rate, consent rate, frequency coverage, cross-device assumptions and dependence on one gatekeeper. |
The debate should not be framed as relevant advertising versus no advertising. The real design space concerns how much information leaves a context, whether individuals can understand and control that movement, which measurement can be aggregate, and whether buyers and publishers can participate without surrendering the market to a few closed platforms.
A short glossary
- Addressability
- The ability to recognise and select an audience or advertising opportunity using available signals.
- Attribution
- A rule or model assigning credit for a conversion to one or more marketing contacts.
- Cookie syncing
- Matching identifiers used by different advertising intermediaries for the same browser.
- First-party data
- Data collected through a direct relationship; the label does not by itself determine consent, fairness or permitted sharing.
- CHIPS
- Cookies Having Independent Partitioned State, an opt-in way to double-key a cookie by its origin and top-level site.
- Clean room
- A controlled environment that permits defined analysis across datasets while restricting raw-data access and outputs.
- Incrementality
- The causal change in an outcome produced by advertising, compared with what would otherwise have happened.
- Pseudonymisation
- Processing that separates direct identity from data using additional information; unlike anonymisation, re-linking remains possible under specified conditions.
Sources and further reading
Current-status and technical claims are linked to primary browser, standards, regulator and company sources. Browser policy and product roadmaps can change; the date above is the research cutoff.
- MDN — Third-party cookies: definition, browser behaviour and migration approaches.
- WebKit — Tracking Prevention: Safari’s third-party-cookie policy.
- Mozilla — Total Cookie Protection: Firefox’s site-partitioned cookie jars.
- Google — Next steps for Privacy Sandbox: April 2025 Chrome decision.
- Google — Privacy Sandbox feature status: supported and retiring technologies, updated August 2026.
- UK CMA — Privacy Sandbox investigation: competition case, testing and closure.
- UK ICO — Storage and access technologies guidance: final April 2026 guidance.
- W3C — Private Advertising Technology Working Group: current standards work.
- Alphabet 2025 Form 10-K and Meta 2025 Form 10-K: company risk disclosures.
- Amazon Ads — Amazon Marketing Cloud: first-party inputs, pseudonymised signals and aggregate outputs.