In 2026, digital marketing fully enters the era of “no third-party cookies.” The planned removal of advertising cookies has seen many twists and turns in recent years. After several delays, Google surprised the industry in April 2025 by ultimately deciding not to block third-party cookies by default in Chrome, opting instead to present users with a “global consent prompt.”
In practice, this approach—similar to Apple’s App Tracking Transparency—lets people choose whether to enable ad tracking. Experts expect a large majority to decline, effectively creating an environment comparable to Safari or Firefox (which already block third-party cookies) and, according to some observers, “sealing the coffin of third-party cookies.” In other words, even without an absolute technical ban, the reach of third-party cookies in 2026 will be extremely limited.
At the same time, regulations have tightened to protect privacy. The GDPR in Europe has required explicit consent for non-essential cookies since 2018, and authorities are stepping up enforcement. In 2025, France’s CNIL imposed a record €325 million fine on Google for failures related to advertising cookies and consent. This sanction illustrates increased regulatory severity: showing targeted ads without explicit user consent or conditioning a service on cookie acceptance is illegal. Other recent texts, such as the European Digital Services Act applied at the end of 2024, also regulate targeted advertising (banning targeting of minors and sensitive data, transparency requirements, etc.).
The global trend is clear: user privacy comes first, even at the cost of a profound transformation of advertising practices.
This shift also reflects public expectations. We are increasingly sensitive to how our personal data is used. According to the CNIL, 40% of users now refuse cookies when given the choice. Cookie consent rates fell by about 15% in one year, dropping to an average of 39%. As a result, nearly 99% of marketing leaders say privacy concerns are already impacting their personalization strategies. Even without waiting for a law or a browser change, the market itself is moving cookieless: regulatory pressure, user preferences, and technical innovation are converging to reshuffle the deck in 2026.
- High-stakes for publishers and advertisers
- Alternatives to third-party cookies: where to start?
- Bet on contextual advertising
- Explore alternative identifiers (shared unique IDs)
- Adopt probabilistic targeting and identifier-free methods
- Leverage Web Push: a cookieless, direct opt-in lever
- A successful privacy-first marketing playbook in 8 steps:
- Comparison table of third-party-cookie alternatives
- Toward effective and ethical advertising
High-stakes for publishers and advertisers
The end of third-party cookies poses a major challenge for both website publishers and advertisers. For publishers, the concern is the business model. Historically, cookies enabled precise visitor targeting, synonymous with high ad revenues.
The IAB estimated that with the demise of third-party cookies, publishers could lose more than $10 billion in ad revenue worldwide. Less targeting means, in the short term, less “monetizable” inventory and downward pressure on CPMs. Publishers must therefore reinvent the value proposition of their ad placements to protect revenue.
For advertisers, the fear is losing performance and measurement. Retargeting, tracking the customer journey across multiple sites, and multi-touch attribution could collapse if cross-site identification disappears.
Some campaigns already perform worse on Safari/Firefox due to cookie blocking. Affiliate marketing, for example, has faced a real “tracking crisis” in recent years: with the inability to reliably track users across sites, brands struggle to attribute conversions to specific partners. Without adaptation, a portion of the marketing budget will become “blind” again (you no longer know which channel converts) or less profitable.
However, this turning point is not just a constraint: it’s also an opportunity to rebuild trust with audiences. By adopting more privacy-respectful solutions, publishers and brands can improve the user experience (fewer intrusive banners, more contextual relevance) and strengthen perceptions of reliability. Advertisers face less rejection or ad-blocking from users tired of incessant tracking. For publishers, shifting toward privacy-first practices can cultivate a higher-quality, more engaged audience. Done right, going cookieless can reconcile marketing effectiveness with user respect, where the previous ecosystem had eroded public trust.
Finally, following the cookieless path also means managing legal and financial risk. Beyond the fines mentioned, ignoring consent obligations or trying to circumvent the law (e.g., hidden tracking) exposes you to heavy penalties and disastrous bad buzz. Conversely, players who get ahead in 2026 and comply with the new rules will gain a competitive edge: they will have already optimized campaigns with new methods while others are still adjusting. Anticipating the transition now limits short-term damage and positions you as a leader in responsible advertising for the future.
Alternatives to third-party cookies: where to start?
Faced with these challenges, how do you practically begin the transition to advertising without third-party cookies? The good news is there are now several replacement solutions to keep targeting and personalization without violating privacy. None is a universal cure-all, but by combining approaches, you can rebuild an effective, sustainable ecosystem. A tour of the main alternatives—and how to start leveraging them in 2026:
Prioritize first-party data (first-party cookies and owned data)
First-party data—i.e., data collected directly from your users on your sites, apps, or touchpoints—is the central pillar of a world without third-party cookies. This includes first-party cookies set by your own site, as well as information from signups, customer accounts, CRM, loyalty programs, on-site behavioral analytics, and more. This data is truly yours and reflects the real behavior of your customers interacting with your brand.
The benefits of first-party data are numerous: higher quality and reliability, transparent collection (when users are informed and consenting), and easier GDPR compliance. For example, recognizing a customer via first-party data can reach 92%, versus only 65% with aggregated third-party data.
Likewise, personalizing the experience based on direct data can increase repeat-purchase rate by +35% among existing customers. Legally, relying on data users have willingly shared with you reduces privacy risk by roughly 80%: you avoid opaque processing of third-party data without consent.
How to capitalize on this first-party data?
First, strengthen its collection: encourage visitors to create an account, subscribe to a newsletter, or share preferences in exchange for real value (premium content, personalized offers…). Deploy a clear consent interface: users should understand what data they share and for what purpose.
Next, invest in tools that centralize and intelligently activate this information. For example, a Customer Data Platform (CDP) can unify customer data from multiple sources into a single profile for segmentation and personalization. Finally, build internal analytics muscle: which sections of your site did a given user view? What path leads to conversion? Insights once purchased from data brokers can now be produced in-house with a robust data-driven strategy.
That said, first-party data has limits: it mostly covers your existing or captive audience. By definition, your own data won’t reach people who don’t yet know you. And not everyone will want to create an account on every site: be realistic and don’t expect to track 100% of visitors without third-party cookies.
The key is maximizing the value exchange (relevant content, real user benefits) to encourage as many voluntary opt-ins as possible. Consider partnerships, too: publishers can pool first-party data in a privacy-respectful way (via data clean rooms) to offer advertisers broader audience segments. In 2025, clean-room solutions exploded: for instance, WPP acquired startup InfoSum to bolster privacy-safe data sharing between advertisers and publishers.
These “bunker” platforms let multiple players compare or match their customer bases without ever exchanging raw data—everything is encrypted and aggregated. Result: an advertiser can reach a publisher’s customers (and vice versa) while ensuring only matching profiles are targeted, and no personally identifiable data is revealed or stored outside its source. To get started in 2026, identify potential allies (complementary-audience publishers, retail partners, etc.) and explore these secure data-sharing mechanisms that signal the future of large-scale targeting—100% compliant and transparent.
Alongside email and CDPs, consider activating Web Push Notifications, a particularly effective lever to turn an opt-in visitor into a re-engageable contact. These notifications rely on explicit consent, use only local data, and let you send targeted messages in real time—even after the user leaves your site.
Bet on contextual advertising
One of the simplest and most proven alternatives to third-party cookies is returning to contextual targeting. This means showing ads based on the content of the web page being viewed rather than the user’s browsing history. For example, a sports-equipment advertiser places banners on sites or articles about sports; a mortgage offer appears on a wealth/finance portal, and so on.
The core idea: the context a user is in already reveals their current intent or interests, enabling relevant messaging without following them across sites.
Technically, contextual advertising relies on semantic and thematic analysis of web pages. Platforms (such as the Google Ads Display Network) scan text, keywords, and even visual elements to infer the page’s topic, then match ads accordingly. On a vegetarian cooking blog, for instance, the algorithm may serve ads for vegan cookbooks or kitchen tools rather than a random SUV or adventure-travel ad.
This contextual relevance offers several advantages
You reach people at the moment they are actively engaged with related content, making them more receptive to your message. You also reduce the risk of annoying the consumer, since the ad naturally fits the current environment instead of appearing off-topic. Finally, you enhance brand image for both advertiser and publisher by supporting quality content aligned with the ad. Crucially, no personal data is needed: no privacy violation and therefore compliance by design.
Of course, contextual has limits.
It will be less precise or personalized than individual targeting. Two readers of the same article will see the same contextual ad, whereas in the past they might have seen different messages based on their own cookies. That said, many advertisers are rediscovering that context can be an excellent proxy for intent.
Contextual also requires sufficiently relevant inventory and volume within each topic to scale campaigns. Large thematic publishers or interest-based ad networks have an advantage. You must also ensure the chosen context aligns with your marketing target: some niche markets may struggle to find suitable environments. Nevertheless, thanks to advances in NLP and AI, modern contextual targeting goes far beyond what we had 15 years ago: it can interpret page meaning more finely and even avoid unsafe contexts (brand safety), making it a top-tier alternative in a post-third-party-cookie world.
Adrena’tips: To get started, audit your current media buys: which budget lines could be redirected to pure contextual? Run pilot campaigns in 2026 on a few key segments, measure engagement and conversions—you may be pleasantly surprised, without tracking anyone.
Explore alternative identifiers (shared unique IDs)
Another avenue the ad industry is exploring is alternative identifiers, often called persistent IDs or universal IDs. The idea is to replace third-party cookies plus cross-platform syncing with a common unique identifier for a user, used across partner websites and apps. In practice, this could be an ID based on a hashed email (if a user creates an account) or an encrypted token issued by a third-party solution that many sites agree to recognize.
Well-known initiatives include Unified ID 2.0 (initially championed by The Trade Desk) and solutions from ID5, LiveRamp, Neustar, and others—often open-source or inter-company partnerships.
The promised benefits are attractive. For users, this could be a secure single login that grants access to multiple online services (akin to “Sign in with Google/Facebook,” but neutral and privacy-respectful). No more juggling 50 accounts and consents: a voluntarily created identifier could follow the user across participating sites in a transparent way.
For advertisers, it could rebuild a complete cross-platform profile (web, mobile, CTV, etc.) and reach the right person at the right time with a tailored message—in other words, retain the benefits of individualized targeting but with explicit, informed consent (the user accepted this unique ID). Moreover, because these solutions are often encrypted and pseudonymized, they ostensibly offer high security and data control.
But we’re still far from broad adoption of these alternative IDs.
They require massive cooperation among many competing players (publishers, ad networks, DSPs, advertisers…) to be effective. The sector remains fragmented and wary: not everyone is ready to share identifiers or rely on a third-party system.
There’s also the challenge of user buy-in: convincing people to create and use this universal ID everywhere is no easy feat (many already resist logging in once—let alone 20 times!). Initiatives like MyAccountID or FranceConnect (in a different context) show how complex it is to establish a universal ID even when it simplifies user life. Legally, such an ID would require ironclad consent and easy withdrawal; otherwise, it could be seen as an even more intrusive “super-cookie.”
Still, it’s worth monitoring and testing these solutions in 2026 when possible. Some ad networks or marketplaces already offer campaigns based on a unique ID (e.g., connecting to an identity graph via partners). If you have a customer base with emails, you can experiment with audience matching using solutions like LiveRamp (which transforms hashed emails into IDs usable for targeting on partner media sites).
Adrena’tips: Be transparent and strict on compliance: ensure users have consented to their email being used for this ad-matching, and explain the mechanism clearly.
Clearly, alternative IDs are a promising way to recreate deterministic targeting (based on verified data) in a respectful framework, but they may not go mainstream in 2026. Treat them as one more string to your bow—especially if you target known, identified audiences—while remembering they will complement other approaches rather than fully replace the old cookie world.
Adopt probabilistic targeting and identifier-free methods
Given the decline in accessible personal data, probabilistic targeting is emerging as a complementary alternative. Instead of targeting an individual because we know exactly who they are (deterministic targeting), we aim to reach them because we believe they match certain criteria through statistical inference.
In other words, we replace individual tracking with audience modeling. Concretely, this spans several techniques: device fingerprinting, cohort-based targeting (groups of users with similar interests), or predictive AI to find users “similar” to known customers.
Fingerprinting
This technique identifies a device or browser via its unique characteristics (configuration, IP address, plugins, etc.) rather than with a cookie. It can recognize the same user on subsequent visits even without cookies and has the advantage of not relying at all on cookie-consent mechanisms.
However, it’s a double-edged sword: used without transparency, it can be seen as a greater privacy violation than cookies because users can hardly protect themselves. Some browsers actively harden defenses against fingerprinting (Firefox blocks it; Brave randomizes fingerprints, etc.).
Google itself, while delaying the end of cookies, softened its stance on fingerprinting in 2025: it announced that, under conditions, companies using its ad products could employ fingerprinting techniques as of February 16, 2025. This surprised many, as Google had historically decried fingerprinting as a way to circumvent user consent. The signal is that as long as such techniques are not “abusively used for unlawful purposes” (per the UK ICO cited by Google), they will be tolerated.
In 2026, pure fingerprinting should be used with great caution: it may be a last resort to track minimal ad efficacy (exposure frequency, fraud prevention, frequency capping…), but it must be embedded in an ethical, legal approach (clear privacy-policy disclosures, limited usage, etc.).
Cohort- or topic-based targeting
Rather than tracking individuals like Peter or Paula, the browser groups users by shared interests and you target those groups anonymously. For example, Chrome’s Topics API (from the Privacy Sandbox) assigns each person a handful of primary interests based on recent browsing—without revealing their full history to advertisers.
These topics (e.g., “sports,” “travel”) then underlie ad targeting. Google designed the system without a persistent unique ID: user data remains locally in the browser and only emerges as aggregates (segment membership). Likewise, other Privacy Sandbox APIs aim to enable conversion measurement or remarketing without cookies via secure computation and strict limits (e.g., FLEDGE for on-device retargeting, or Attribution APIs that return numeric results without identifying who clicked).
In 2025 these technologies were still in testing, with real adoption delayed by Google’s change of plans. Nevertheless, they represent an intriguing direction: target without identifying via machine learning.
In 2026, if you buy programmatic media, check the status of these solutions: some SSPs/DSPs may already offer “cookieless” deals leveraging anonymous signals (cohorts, AI-enriched semantic contextual, etc.). Test them and compare performance to your traditional campaigns.
Machine learning and statistical modeling
Increasingly advanced, these offer powerful ways to reach and measure without cookies. More brands are adopting hybrid approaches that combine deterministic data (their CRM base, collected first-party IDs) with probabilistic methods to expand reach.
For example, you can use your deterministic customer data (e.g., email) to precisely retarget existing users and use those same profiles to train a lookalike model. AI can analyze shared characteristics of your best customers and find people online with a similar profile (the principle behind lookalike audiences, now supercharged by recent AI advances). These methods don’t require tracking each person: they operate on datasets and correlations.
Adrena’tips: Rather than tracking an anonymous prospect’s individual path, you can statistically predict that a given behavior (visiting certain product pages, coming three times in a week, etc.) has an X% chance of converting—and adjust bids or messages accordingly for all users showing that behavior.
For performance measurement without cookies, we’re seeing a resurgence of techniques like marketing mix modeling (MMM) and incrementality tests (e.g., expose one group to ads and keep a control group unexposed, then compare conversions). These aggregate, probabilistic methods compensate for the loss of individual tracking by providing reliable trends on campaign effectiveness—without personal tracking.
The downside is a loss of granularity (you can no longer attribute every sale to every click exactly) and a need for stronger analytical skills. But many solutions are emerging to support this transition: specialized platforms analyze your data to detect high-potential segments or attribution fraud. In 2026, investing in probabilistic capabilities (data science, marketing AI, experimentation tools) will be a key success factor for continued optimization in a less traceable world.
Leverage Web Push: a cookieless, direct opt-in lever
Web Push stands out as one of the most powerful strategic alternatives to third-party cookies, particularly for retargeting and loyalty, without invasive tracking. This format lets a website collect a user’s direct opt-in via the browser, without requiring an email or account creation. Once subscribed, users can receive personalized messages even when they are no longer on the site.
This channel offers many advantages in a privacy-first environment:
- 100% GDPR-compliant: every send targets a user who has given explicit consent.
- Cookieless: Web Push relies on no third-party identifier or cross-site tracking.
- High engagement rates: thanks to visibility on desktop and mobile, Web Push often sees CTRs between 5% and 15%, depending on the vertical.
- Ideal for retargeting: you can automate re-engagement scenarios after a visit, cart abandonment, or prolonged inactivity, based on on-site behavioral data.
Adrena’tips: In 2026, integrating Web Push into your marketing journeys compensates for reach lost to third-party cookies. Start by enabling a GDPR-compliant solution on your site, prompt subscription at strategic moments (e.g., end of article, cart add), and use behavioral segments to personalize campaigns.
A successful privacy-first marketing playbook in 8 steps:
To summarize this transition, here are practical tips for marketers and publishers beginning their journey toward cookie-free advertising:
- Audit your third-party cookie dependencies: identify which channels, tools, or partners use third-party tracking (DSP, DMP, retargeting, analytics…) and evaluate the impact if that data disappears. Prioritize alternative solutions where the risk is highest.
- Strengthen consent-based data collection: emphasize signups, account creation, and voluntary surveys. Enrich your CRM with declarative data (preferences, intents) that users provide in exchange for real value (personalized advice, rewards, exclusive content). The richer your first-party data, the less you’ll feel the absence of third-party cookies.
- Communicate transparently and educationally: explain the changes underway, your privacy commitments, and how they improve the experience. An informed, reassured user is more likely to share data directly (newsletter opt-ins, etc.) than a wary one.
- Test alternatives progressively: don’t wait for perfection to experiment. Launch pilot contextual campaigns, try a privacy-safe data-sharing partnership with a complementary player, deploy your web push solution, enable advanced conversion APIs from Google or Facebook (sending hashed conversions) to fill attribution gaps. Each test reduces uncertainty and accelerates learning.
- Combine approaches in a hybrid way: there won’t be a single silver bullet. Leverage multiple alternatives in parallel to offset each one’s limits. For instance, use first-party data to retarget loyal customers, contextual to prospect new audiences, and probabilistic lookalikes to expand reach. Mixing deterministic and probabilistic maximizes coverage while preserving precision where it matters most.
- Measure differently—and smartly: adopt new KPIs and analytical methods. Track global indicators (total sales, customer LTV) rather than micro multi-touch events. Use statistical approaches (MMM, regional analyses) to assign credit without individual tracking. And accept some uncertainty: in 2026 we’ll steer more by “compass” than ultra-precise GPS—but with the right tools, it’s manageable.
- Train teams and partners: the cookieless transition requires new skills. Educate marketing, data, and legal teams on privacy issues. Align partners (agencies, ad networks) with your requirements. The more the ecosystem is aligned, the smoother the transition.
- Monitor legal and technical evolution: stay on top of upcoming regulations (e.g., the future EU ePrivacy Regulation) and browser developments. 2026 is unlikely to be the end of the story: more changes will come (new fingerprinting limits? standardized ad APIs?). Active monitoring lets you anticipate rather than endure these shifts.
Comparison table of third-party-cookie alternatives
To help you see clearly, here’s a summary table comparing the main alternatives discussed, with their pros, cons, and performance impact.
Toward effective and ethical advertising
The era of increasingly cookieless advertising is not the end of digital marketing, but the beginning of a new chapter built on innovation and trust. The year 2026 marks the starting point of an ecosystem where personal data is used more sparingly and more intelligently. Marketers and publishers already have a range of solutions to keep hitting objectives: leverage owned data and direct audience relationships, put context back at the heart of targeting, experiment with alternative approaches (shared IDs, anonymized cohorts, predictive AI…), and rethink measurement methods.
Yes, the transition requires effort and a mindset shift. We must accept the loss of conveniences offered by mass tracking and replace it with deeper customer understanding and renewed creativity in acquisition. Far from handicapping marketing, this transformation can make it more sustainable and more virtuous.
Less intrusive, better-accepted advertising ultimately delivers better performance: your messages reach people in the right mindset, on channels that respect their choices. And by demonstrating respect for privacy, you build a trust capital that lifts your brand and engagement rates.
In 2026, it’s time to “take the leap” toward a future that may soon be free of third-party cookies. Start now, step by step, applying practical advice and leveraging available alternatives. You will unite technical expertise with user experience, strengthen your brand’s authority in data protection, and prove the reliability of your practices. The cookie era is behind us; a more responsible and equally effective digital marketing era is within reach—begin writing it today.
