Why Third-Party Tracking Is Being Eliminated

Executive Summary

Third-party cookies are small text files that have underpinned cross-site behavioral tracking for more than two decades. They are being systematically eliminated, not because the industry chose to move on, but because regulators, browser vendors, and courts decided the privacy tradeoffs were no longer acceptable.

This report is organized around three questions: How did third-party cookies enable the tracking ecosystem that now exists? What specific technical and regulatory forces are dismantling that ecosystem? And what replaces it, both technically and from a user privacy standpoint?

The answers reveal a system whose privacy implications were largely invisible to the users it profiled. A typical web session generates dozens of tracking calls to ad networks, data brokers, and analytics platforms, none of which the user deliberately engaged with. Browsers and operating systems are responding with enforcement mechanisms that make cross-site behavioral profiling technically impossible without user consent.

Scope & Objectives

This report addresses three objectives:

1. Explain the technology. Provide a technically accurate account of how third-party cookies enable cross-site tracking, including the HTTP mechanisms, the ad tech stack that uses them, and the specific privacy harms they create.
2. Document the deprecation. Trace the multi-year process by which browser vendors, mobile operating systems, and regulatory bodies dismantled cookie-based tracking, and clarify what has actually changed as of early 2026.
3. Assess the replacements. Evaluate the technical alternatives being deployed in the post-cookie environment, their capabilities, their genuine privacy properties, and their limitations.

How Third-Party Cookies Work — and Why They’re a Privacy Problem

To understand why third-party cookies are being eliminated, you first need to understand what they are, how they function at a protocol level, and what they made possible at scale. The privacy problem is architectural: it was not an accident or an abuse of the system, but a consequence of what the system was designed to do.

Cookie Protocol Primer

A cookie is a small key-value data store set by a server and persisted in the user’s browser. When a server includes a Set-Cookie header in an HTTP response, the browser stores it and returns it in the Cookie header of every subsequent request to that domain. This mechanism was introduced in 1994 by Lou Montulli at Netscape as a way to implement session state in an otherwise stateless HTTP protocol.⁵

A first-party cookie is set by the domain the user is currently visiting. A third-party cookie is set by a different domain, one whose resources are embedded in the page you’re visiting. That cookie will be sent back to the third party every time you visit any other site that also loads its resources, enabling it to recognize you across unrelated websites.

The Tracking Stack

Third-party cookies became the foundation of a multi-layer data infrastructure. The table below details the major layers of the third-party cookie tracking stack.

The real-time bidding (RTB) auction that underlies most programmatic advertising depends on all of these layers functioning together. When a user loads a web page, the publisher’s supply-side platform broadcasts an auction opportunity including the user’s cookie-based ID. The entire system depends on a persistent, shared identifier.⁷

Studies from Princeton’s Web Transparency and Accountability Project found that a majority of the top 1 million websites load third-party tracking code from Google, Meta, or both. On a typical news or retail site, a user’s browser makes 50–300 third-party requests per page load.¹

Privacy Violations by Design

The privacy implications of third-party cookie infrastructure operate on several levels:

• Cross-site behavioral profiling. An ad network embedded in thousands of publisher sites can observe and record every page a user visits that includes its tracking pixel. Over time this creates a detailed behavioral profile: political interests, health conditions, financial situation — none directly provided by the user.
• Re-identification of supposedly anonymous data. Cookie-based profiles can be linked to real identity through cookie syncing, in which two ad networks exchange cookie IDs and link their respective behavioral datasets.⁸
• Data persistence and breadth. Cookie-based behavioral data persists across sessions and devices, and can be sold to parties the user never interacted with. Data brokers built multi-billion dollar businesses on this supply chain.
• Lack of meaningful consent. Prior to GDPR, most third-party tracking required no user notification. Post-GDPR consent banners are widely criticized as dark-pattern implementations that make refusal intentionally difficult.⁹

The Regulatory Response

The table below details key privacy regulations and their implications for cookie-based tracking.

The most significant enforcement actions: French CNIL fined Google €150 million and Meta €60 million in January 2022 for making it harder to refuse cookies than to accept them.¹⁰

The Deprecation Timeline

Safari ITP (2017–2020)

Apple’s WebKit team shipped Intelligent Tracking Prevention in Safari in September 2017, using machine learning to classify third-party domains as tracking domains. ITP 2.0 (2018) blocked all third-party cookies from classified domains entirely. ITP 2.1 (2019) added a 7-day cap on all script-writeable first-party storage set via third-party scripts. ITP 2.3 (2019) closed the cross-site link decoration workaround by stripping tracking parameters from URLs. Safari held approximately 20–25% of global browser market share,¹¹ meaning roughly a quarter of web users were no longer trackable via third-party cookies.

Apple ATT (2021)

In April 2021, Apple shipped iOS 14.5 with the App Tracking Transparency framework. ATT requires all iOS apps to explicitly request user permission before accessing the device’s IDFA. Opt-in rates globally settled at approximately 25%,² meaning three in four users denied permission when asked directly and clearly.

Prior to ATT, the IDFA was available to all apps unless the user manually disabled it, very few did. When Apple changed the default to opt-in with a clear prompt, 75% of users said no. This gap between “default-on” and “genuinely-asked” consent rates is the most important data point in the privacy debate.

Google Privacy Sandbox (2019–2026)

Google announced the Privacy Sandbox initiative in August 2019,¹² proposing to replace third-party cookies in Chrome with privacy-preserving APIs. Google originally proposed deprecating third-party cookies by late 2022. The deadline was extended five times. Google then revised its approach: rather than deprecating third-party cookies entirely, Chrome now presents users with a one-time choice, a change driven by pressure from the UK Competition and Markets Authority.¹³

Where Things Stand in 2026

• Safari and Firefox: Third-party cookies blocked by default since 2020 and 2019. Combined ~30–35% of global web traffic.¹¹
• Chrome: Third-party cookies remain available but users have been presented with a one-time consent choice. Estimates suggest 40–60% of Chrome users will disable third-party cookies when prompted.
• iOS App Tracking: The IDFA is unavailable for approximately 75% of iOS users.
• Privacy Sandbox APIs: Deployed in Chrome but adoption is uneven. The APIs do not provide equivalent functionality for all use cases.

Technical Alternatives

No single technology replaces third-party cookies. The ecosystem is replacing a general-purpose cross-site identifier with a set of purpose-specific, architecturally constrained tools.

Privacy Sandbox APIs

The Privacy Sandbox APIs are browser-native alternatives to specific third-party cookie use cases. Their key architectural innovation is moving processing from servers, where data can be freely collected, to the browser, where it can be restricted and audited.

Technical constraints of the Topics API: Topics are limited to a predefined public taxonomy. A maximum of 3 topics are returned per call. Topic epochs rotate weekly, limiting persistent profile accumulation. The API includes a noise mechanism: 5% of the time, a random topic is returned.

Protected Audience architecture: Interest groups are stored in the browser, not on any server. Bidding functions run in isolated JavaScript worklets with no network access. The auction result is subject to k-anonymity requirements (k=50 in current implementation). On-device auctions are computationally constrained, complex ML-based bidding strategies cannot run in browser worklets.

First-Party Data Infrastructure

The highest-value investment in the post-cookie environment is first-party data collected directly from users through owned channels. Building genuine first-party data infrastructure typically requires:

• Identity resolution layer. A system linking authenticated users across devices using email-based or phone-based identifiers — deterministic rather than probabilistic.
• Consent management platform (CMP). A system for recording, storing, and honoring user consent choices in a technically enforceable and legally auditable way.
• Customer data platform (CDP). A unified database aggregating first-party data from web, app, CRM, and offline sources into persistent customer profiles.
• Server-side event tracking. Sending conversion and behavioral events directly from the advertiser’s server to ad platforms’ Conversion APIs, bypassing the browser entirely.

Server-Side Tracking

Server-side tracking routes user event data through the advertiser’s own server before forwarding it to advertising and analytics platforms, rather than firing client-side pixels directly from the user’s browser.

Architecture: User takes an action → browser fires an event to the advertiser’s own server-side endpoint (first-party request) → server enriches the event with CRM data and authenticated user ID → server forwards to platform Conversion APIs (Meta CAPI, Google Ads Conversion API, TikTok Events API).

Contextual Targeting

Contextual targeting serves ads based on the content of the page being viewed rather than the behavioral history of the user. Modern contextual targeting uses NLP models to classify page content across hundreds of topic and sentiment dimensions. From a privacy standpoint, contextual targeting has genuine advantages: it does not build or require user profiles, generates no cross-site tracking data, and requires no consent under GDPR since it does not process personal data.

Identity Solutions

The table below compares major identity solutions for post-cookie environments.

Data Clean Rooms

A data clean room is a secure computing environment that allows two parties to analyze overlapping datasets without either party directly accessing the other’s raw data.

Architecture: Advertiser uploads hashed first-party customer list → publisher uploads hashed authenticated audience → clean room executes queries over overlapping dataset in an isolated compute environment → differential privacy techniques add statistical noise → neither party receives the other’s raw data.¹⁵

Major implementations: Google Ads Data Hub, Meta Advanced Analytics, Amazon AWS Clean Rooms, Snowflake Secure Data Sharing, InfoSum.

Privacy Implications

What Users Actually Gain

• Reduced cross-site behavioral profiling. Without a shared identifier, ad networks cannot silently observe and link a user’s activity across sites they did not choose to engage with.
• Profile data stays in the browser. Privacy Sandbox APIs keep user interest data on the device rather than uploading it to servers.
• Consent becomes more meaningful. ATT’s 25% opt-in rate demonstrates that when consent is genuinely informed and easily exercised, a large majority of users choose to limit tracking.
• Fewer data brokers in the loop. Browser-level partitioning directly reduces the surface area of data sharing.

What Still Threatens Privacy

• Browser fingerprinting. A browser can be identified through user agent, screen resolution, installed fonts, canvas rendering behavior — without any cookies. Studies suggest 80–95% of browser instances can be uniquely identified through fingerprinting.¹⁶
• Walled garden consolidation. The decline of open-web third-party cookies strengthens Google, Meta, and Amazon because their tracking infrastructure is first-party within their own ecosystems.
• Authenticated identity infrastructure. Solutions like UID2 replace cookie-based cross-site tracking with authentication-based cross-site tracking. Privacy outcome depends on consent mechanism quality.
• Server-side and CNAME workarounds. CNAME cloaking routes third-party tracking through a DNS alias, maintaining significant tracking capability outside browser restrictions.

Practical Guidance

For Engineering and Technical Teams

1. Audit your cookie inventory using browser DevTools, a privacy scanning tool (OneTrust, Cookiebot), or web application firewall log analysis. Categorize each by purpose: strictly necessary, functional, analytics, or advertising.
2. Classify and remediate SameSite attributes. Any third-party cookie in a cross-site context must carry SameSite=None; Secure. First-party session and authentication cookies should use SameSite=Strict or SameSite=Lax.
3. Implement server-side Conversion APIs for each ad platform you use (Google, Meta, TikTok, LinkedIn).
4. Evaluate and implement Google Privacy Sandbox APIs. Test Topics API integration for Chrome-targeted campaigns. Prototype Protected Audience API integration for retargeting.
5. Implement CHIPS for functional third-party embeds. If your service is embedded in other sites, migrate third-party cookies to use the Partitioned attribute.
6. Audit your consent management implementation. Verify your CMP correctly enforces consent choices at the tag/pixel level. If using Google Consent Mode v2, ensure the default state for analytics and advertising tags is ‘denied’ until consent is collected.

For Marketing and Advertising Teams

1. Audit your current attribution model. Identify what percentage of conversion attribution currently depends on third-party cookies. Multi-touch attribution models relying on cross-site cookie stitching are already broken for Safari and Firefox users.
2. Invest in authenticated value exchange. Email subscription programs, loyalty accounts, and gated content are the mechanisms by which users voluntarily provide authenticated identity.
3. Build platform-specific audiences natively. Within walled gardens, first-party customer match lists are more reliable than behavioral targeting built on third-party data.
4. Test contextual campaign structures. Many marketers find the gap smaller than expected for categories with strong content-intent correlation.

For SMBs and Lean Organizations

For Publishers and Media Companies

1. Build first-party registration and login. Even a modest logged-in audience (10–20% of regular readers) significantly improves programmatic CPMs.
2. Implement a subscription or newsletter strategy. Email as a first-party channel is resilient to all browser and platform changes.
3. Evaluate direct data partnerships via clean rooms.
4. Pressure-test your programmatic stack for Sandbox readiness. Work with your SSP to verify Protected Audience API and Topics API integration status.

Conclusion

Third-party cookies were an accident of history: a general-purpose session mechanism repurposed at scale into a cross-site surveillance infrastructure that most users never consented to and many would reject if they understood it. The fact that 75% of iOS users declined ad tracking when asked directly tells you everything about the gap between technical capability and genuine consent.

The deprecation is real, the timeline is messy, and the replacements are imperfect. Privacy Sandbox APIs provide meaningfully better privacy properties than third-party cookies in some dimensions while introducing new concerns in others. Server-side tracking removes user-visible tracking without necessarily reducing underlying data collection. Authenticated identity solutions preserve cross-site targeting but anchor it to consent events that vary widely in quality.

Methodology

Digital 520 applies a rigorous, multi-source research methodology. For this report the following sources and methods were employed:

• Primary technical documentation. Google Privacy Sandbox developer documentation, Apple WebKit ITP technical writeups, W3C specifications for the SameSite cookie attribute, CHIPS, Storage Access API, and Topics API were reviewed in full.
• Regulatory source review. GDPR text, ePrivacy Directive, CCPA/CPRA text, DMA, and enforcement decisions from CNIL, ICO, and the Irish DPC were reviewed.
• Academic and industry research. Research on browser fingerprinting (EFF Panopticlick, Princeton WTAP), cookie syncing mechanics, and ATT opt-in rates was reviewed and cited.
• Practitioner judgment. Digital 520’s advisory experience across privacy engineering, advertising technology, and compliance engagements informs the practical guidance.

Limitations: Browser behavior and Privacy Sandbox API specifications are subject to rapid change. Policy positions from regulatory bodies continue to evolve, particularly regarding Privacy Sandbox APIs and Consent Mode v2.

Glossary

Endnotes

The following references support the data and claims presented in this report. Digital 520 maintains a full citation database for all Insight Reports.

1. Englehardt, S. & Narayanan, A. “Online Tracking: A 1-million-site Measurement and Analysis.” Princeton Web Transparency and Accountability Project. ACM CCS 2016.
2. Flurry Analytics / Yahoo. “iOS 14.5 Opt-In Rate: Daily Updates Since Launch.” April 2021 onwards.
3. Google. “Privacy Sandbox Timeline.” developer.chrome.com/docs/privacy-sandbox. Accessed March 2026.
4. International Association of Privacy Professionals (IAPP). “Global Privacy Law and DPA Directory.” 2025.
5. Kristol, D. & Montulli, L. “RFC 2109: HTTP State Management Mechanism.” IETF. February 1997.
6. West, M. & Goodwin, M. “SameSite Cookies Explained.” web.dev, Google.
7. Interactive Advertising Bureau (IAB). “OpenRTB API Specification.”
8. Englehardt, S. & Narayanan, A. (cookie syncing section). ACM CCS 2016.
9. Forbrukerradet (Norwegian Consumer Council). “Deceived by Design.” June 2018.
10. Commission Nationale de l’informatique et des libertés (CNIL). “Cookie consent: CNIL fines GOOGLE €150 million and FACEBOOK €60 million.” January 2022.
11. StatCounter GlobalStats. “Browser Market Share Worldwide.” 2025.
12. Google. “Building a more private web.” Chromium Blog. August 2019.
13. UK Competition and Markets Authority. “Investigation into Google’s Privacy Sandbox browser changes.” Final Report. 2022.
14. The Trade Desk. “Unified ID 2.0.” thetradedesk.com.
15. International Association of Privacy Professionals (IAPP). “Data Clean Rooms: Privacy and Advertising Technology.” 2023.
16. Electronic Frontier Foundation. “Browser Fingerprinting: An Introduction and the Challenges Ahead.” eff.org.