After years of working on the full depreciation of third-party cookies, Google decided to keep them up and running in 2024 after all—with a caveat.
Google is trying to balance advertiser needs and consumer privacy, so they’re planning to roll out a one-time prompt which allows users to set privacy preferences across the Google search/browsing experience.
What does this mean for marketers?
You can still technically use third-party cookies, but you won’t reach your full audience by relying on them.
The solution to future-proof your strategy is cookieless attribution. This guide covers everything you need to know about cookieless attribution, including what it is and how to achieve it.
Key Takeaways:
- Cookieless attribution may show fewer conversions, but those conversions are more trustworthy. What you lose in volume, you gain in integrity and compliance.
- Shifting to cookieless attribution isn’t just a tech swap—it’s a mindset and workflow shift. A phased rollout starting with first-party data, server-side tracking, and validation creates stability, accuracy, and team alignment.
What is Cookieless Attribution?
Cookieless attribution tracks and identifies traffic and customer leads sources without relying on browser cookies.
While they’re not banned on Chrome (yet), the depreciation of third-party cookies represents a shift in digital marketing. The overall sentiment on internet privacy shows that cookieless attribution is necessary for long-term strategy.
The Shift to Privacy-First Attribution
Privacy concerns about browser cookies came to attention in the late 1990s and 2000s. But they weren’t a legal issue until privacy regulations like the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) came into force in 2016 and 2020 respectively.
Privacy regulations help protect consumers from invasive tracking and give them control over how companies collect and use their data. But in Deloitte’s 2024 Connected Consumer report, respondents suggested these regulations alone aren’t enough:
“Ninety percent of respondents believe that device makers should do more to protect data privacy and security (up five points from 2023), and the same number feel that application and online service providers should do more.
Eighty-four percent want the government to do more to regulate the way companies collect and use consumer data (up seven points from 2023).”
As an additional factor to consider, 64% of the surveyed consumers using Generative AI (GenAI) technologies were concerned with data privacy and security.
For companies that don’t respect consumer privacy, the stakes are pretty high. Nearly two-thirds of respondents (64%) said they would be “very likely” or “somewhat likely” to switch tech providers if a privacy incident made them lose trust.
All of this is to say that the trend is moving towards cookieless attribution. This privacy-first approach is a positive reputational move, and you can gather accurate insights without invading consumers’ privacy with tools such as The Attribution Platform.
Advanced Cookieless Tracking Methods
There are several technology alternatives marketers can use to advertise and run campaigns that track leads without invading privacy. We’ll cover a few established methods to integrate cookieless attribution into your business.
First-Party Data and Server-Side Tracking
First-party data is what you collect directly from users, like login information, subscriptions, and surveys. If your website is a publisher, SaaS platform, or ecommerce store, you’ll likely have this data already. It’s fully compliant, user-consented, and persistent.
This data complements server-side tracking—which moves data collection from the browser to the server with tools like Google Tag Manager.
This method bypasses browser cookie restrictions, improves data accuracy, and offers more control over data sharing. Combining these approaches, you’ll track conversions, custom events, and user paths without third-party cookies.
Zero-Party Data
You can run zero-party data initiatives—where users intentionally and proactively share their data.
You can get this data by creating product-related quizzes, using preference centers, and communication feedback forms (e.g., their content preferences and preferred contact time/method).
Collecting data this way can help build trust and is fully compliant with data protection regulations.
Universal IDs
With a few extra steps after collecting zero or first-party data, you can replicate some third-party cookie functions while respecting privacy. To do that, you’ll need to create universal IDs.
When a user consents to being tracked (usually by email login), the email is hashed or encrypted to generate a universal ID. Publishers and advertisers use this ID instead of cookies.
A few adtech providers offer this service, including ID5 and LiveRamp.
CDPs with ID Resolution
Another privacy-compliant approach, arguably the most insightful, is using a Customer Data Platform with ID resolution.
This approach combines data from web, mobile, and CRM sources into unified profiles using deterministic or probabilistic matching. It allows for personalized experiences and analytics without cookies, as long as user identity can be inferred or matched.
The Attribution Platform offers a comprehensive solution for unifying cross-platform and cross-device attribution data. Our integration with Segment lets you build privacy-compliant customer profiles and track their journey with your brand.
With this approach, you access privacy-focused tracking and analytics, and a detailed view of marketing ROI, ROAS, and other crucial metrics.
Maintaining ROI Visibility Without Cookies
Advertisers’ main concerns regarding cookieless digital ad strategies have been “reaching target audiences effectively at scale” (53%) and “ensuring/maximizing return on advertising spend” (51%).
Among other similar concerns, these suggest marketers and advertisers think cookieless attribution may reduce measurement capabilities—but the opposite can be true.
Cookieless attribution helps track customer journeys and pinpoint metrics like Customer Acquisition Cost (CAC), Return On Ad Spend (ROAS), and Lifetime Value (LTV) with precision. How?
Using the Attribution Platform, you can connect popular ad, marketing, and ecommerce platforms for a unified view of marketing efforts.
The Attribution Platform uses simplified server-side tracking and data aggregation to access the real ROAS by cohort across vendors, and a combined view of paid channels like PPC, retargeting, sponsored content, and affiliate/partner marketing.
Using multi-channel attribution modeling, you can identify the best marketing mix model for your brand and determine which channels to allocate more budget to for better ROI.
Comparing Cookieless Attribution Solutions
Since cookieless attribution solutions provide the data accuracy you need for ROI insights, you’re likely considering potential solutions. We touched on this a little in the earlier section on advanced tracking methods.
At a high level, the solutions include:
- Deterministic attribution using first-party identifiers (like logins, emails, or UTM parameters). The Attribution Platform is a tool that uses this approach.
- Server-side tracking shifts data collection from browser to backend. Again, The Attribution Platform uses this approach, but you can also use Google Tag Manager.
- Probabilistic and AI modeling that combines data from multiple platforms and builds user identity graphs. Segment is a tool that uses this approach.
- Cohort and click-based models that avoid user-level tracking. Tools like Google Ads, Email Service Providers, and Heap offer this type of attribution.
- Privacy-focused APIs like Google’s Topics and Attribution Reporting, offering aggregated insights.
These solutions aim to answer the same core question, “What’s working?”—but vary in data granularity, compliance approach, and technical requirements.
Tools like The Attribution Platform offer robust cookie-free multi-touch attribution, using deterministic logic and server-side integrations to connect ad spend to revenue. You can also use different attribution models like first-touch attribution or time-decay attribution depending on your funnel’s complexity.
Others rely more on aggregated or probabilistic insights, which can be less precise but quicker to deploy.
Implementation complexity also varies a lot. Some platforms are plug-and-play with native integrations, while others need developer support, custom tagging, or complex data modeling for meaningful results.
Choosing the right approach depends on your tech stack, compliance needs, and the level of attribution insight your business requires. The key is to balance data clarity with privacy-by-design principles—and choose a solution that fits your internal capabilities, not just your marketing ambitions.
Implementing Your Cookieless Attribution Strategy
Getting your cookieless attribution strategy running shouldn’t be an overnight switch. Even with a dedicated team of data engineers, you should still take a phased approach to test, refine, and optimize your strategy.
Here’s a step-by-step roadmap to help you transition to cookieless attribution:
Phase 1: Audit and Assess
In this phase, conduct a comprehensive audit of your current tracking methods:
- Which cookies do you use?
- Which tools/platforms depend on them?
Map your customer journey across touchpoints like ads, web, email, sales calls, etc. With this map, you can try identifying where attribution breaks down (like with iOS and Safari users).
With this information, you can review your data privacy compliance with GDPR, CCPA, and similar regulations in your country.
Challenges you may encounter
You may face two main challenges in this phase:
- Discovering hidden or legacy cookie scripts.
- Internal stakeholders not being aligned with changes you need to make.
To resolve these challenges, document your findings and create an internal report—involve marketing, sales, legal, and data teams early.
Phase 2: Strengthen First-Party and Zero-Party Data
After assessing your situation, it’s time to build more of what you own. Audit your current UTM strategy (if you have one, if not, build one) and make sure to keep consistent tag naming conventions.
From there, start collecting more first-party identifiers:
- Email addresses, user IDs, or login states (e.g., Google Sign In).
- Add consent banners and data preference center if you haven’t already.
If you’re planning to use content attribution, encourage users to create accounts, sign up for newsletters, and download content from lead magnets to grow your database.
Challenges you may encounter
You’ll likely face a few challenges during this phase, including:
- Seeing drop-offs from added friction in signups.
- Needing a clear value exchange for customers to volunteer their data.
To overcome these challenges, start with low-friction forms and make opt-ins transparent (for regulatory purposes) and valuable (for customers).
Phase 3: Implement Cookieless Tracking Infrastructure
Before scaling cookieless tracking, you need to lay its foundations. Start deploying server-side tracking with Google Tag Manager or native platforms.
As you deploy server-side tracking, migrate conversion tracking from third-party to first-party endpoints—like Meta’s Conversion API or Google Enhanced Conversions.
You’ll also need to choose a cookieless attribution solution that fits your needs—then set up custom event tracking and test the tool’s cohort logic.
Challenges you may encounter
Depending on the complexity of your business needs, you may need developer resources or third-party support. During this switchover phase, your data may also look a little messy or incomplete at first.
To help you overcome these issues, you can run these solutions in parallel with your existing tools and use a “test and learn” period before decommissioning older systems.
Phase 4: Validate and Calibrate
After building your infrastructure, you’ll want to make sure your new systems capture data accurately. During this phase, you’ll need to take the following actions:
- Compare data from your new attribution setup vs your old cookie-based reports.
- Focus on directional accuracy over an identical match. In other words, the conversion numbers won’t be exactly the same, but your channel trends should match (e.g., similar drops or boosts in performance).
- Start analyzing:
- ROAS, CAC, and LTV by cohort.
- Drop-off points.
- Influential marketing touchpoints.
Your cookieless attribution tool should start providing these insights, and remember to keep key stakeholders in the loop by reporting on your initial findings.
Challenges you may encounter
If you previously used cookie-based solutions, you likely used different performance metrics—especially if you’re moving from last-touch to multi-touch attribution. Since the data looks different, stakeholders might not trust it at first.
To overcome these issues, show trends instead of raw numbers and explain the “why” behind shifts in attribution logic (e.g., previous reports may have duplicate or missing data).
Phase 5: Phase Out Cookies and Optimize
The final phase makes your cookieless attribution strategy official, but keep iterating. During this phase, you’ll need to:
- Decommission third-party pixel dependencies like Meta or LinkedIn in favor of APIs or first-party methods.
- Optimize marketing channels using the new attribution insights.
- Train your team on interpreting cohort-based and multi-touch reports.
- Implement privacy dashboards and reinforce compliant practices (tools like Segment can help with this). In your privacy dashboard, monitor and manage:
- What data do you collect (and how)?
- Consent status (who opted in/out).
- Data retention periods.
- Third-party data sharing and access.
- Requests for access, correction, or deletions (DSARs).
These actions will establish transparent and compliant data practices, future-proof your data, and respect customer/user privacy.
Challenges you may encounter
If your team is used to last-click or Google Ad defaults, they will need to embrace a mindset shift to privacy-focused multi-touch approaches. With these changes, you’ll also likely find some short-term confusion around optimization decisions.
To overcome these issues, create an internal “Cookieless Attribution Playbook” and highlight wins from this approach (e.g., uncovering hidden, high-performing channels).
Getting Started With The Attribution Platform
Moving to a cookieless attribution system and sunsetting third-party cookies offers your business several benefits, including:
- A more positive reputation for high privacy compliance and practices.
- A much smaller probability of breaking privacy regulation rules.
- More meaningful data for a holistic view of your marketing efforts.
The Attribution Platform lets you unify your cookieless tracking results into an easy-to-use dashboard. Use the aggregated attribution data to track and monitor key metrics like channel-specific ROAS, ROI, and LTV, and document customer journeys.
Alongside integrations with key digital marketing and sales tools like HubSpot, Salesforce, Segment, and Google Ads, you can take a plug-and-play approach or use the Attribution Platform to build a customized machine-learning attribution model for your business.
If you’re curious about the Attribution Platform’s data tracking capabilities, book a demo today.
Cookieless Attribution FAQs
How accurate is cookieless attribution compared to cookie-based tracking?
Cookie-based tracking can be more accurate for anonymous, first-time visitors, while cookieless attribution can be more accurate for cross-device journeys, long sales cycles, Safari and iOS traffic, and when consent is required.
How will cookieless attribution affect my advertising performance?
Cookieless attribution doesn’t hurt your ad performance—it just gives you a clearer view of it. What may seem like a dip is often just the removal of inaccurate data.
Can cookieless attribution work across multiple devices and platforms?
Short answer: Yes. With a solid data infrastructure, cookieless attribution works cross-device and platform using server-side tracking and deterministic attribution modeling.