Your best prospects are the ones who’ve already visited your site. They’ve explored your products, read your content, maybe even filled a cart — but haven’t converted.

Traditional retargeting was built to bring them back. A simple pixel and third-party cookie enabled you to follow visitors across the web with targeted ads. It worked because it was invisible, automatic, and easy to set up.

However, that invisibility is now disappearing. The old infrastructure is being replaced with cookieless retargeting, which is more transparent and privacy-focused. Retargeting without cookies brings with it new tools, tactics, and strategies that marketers need to embrace.

Key takeaways

• Traditional cookie-based retargeting relies on cross-site tracking that browsers and regulations are eliminating.
• Higher match rates, better privacy compliance, and stronger audience ownership make cookieless retargeting more effective than cookie-based methods.
• With cookieless retargeting, first-party data becomes your primary retargeting asset — email addresses, phone numbers, and on-site behavior that you collect directly.
• Server-side tracking helps preserve conversion data and audience signals when browsers block client-side cookies.
• Conversion APIs send data directly to platforms, bypassing browser restrictions.

How does traditional retargeting work?

Traditional retargeting relies on one core mechanism: placing a tracking pixel and third-party cookies.

You’d place a pixel on your website, usually from an ad platform like Meta or Google. When someone visited your site, that pixel would fire and drop a third-party cookie in their browser. 

This cookie acted as a marker, identifying that person as part of your audience while they browsed other sites. When that person visited another site within the ad network, the platform could read the cookie, recognize them as someone who’d visited your site, and serve them your ad. 

This system made it easy to build audiences at scale. You could segment visitors based on behavior. People who viewed specific products, abandoned carts, or spent time on pricing pages would be served ads tailored to where they were in the funnel.

The cookie served as the red thread that enabled advertisers to use their first-party data for targeting and retargeting the right audience. But it was the third-party nature of these cookies — set by external domains and readable across sites — that made cross-site tracking possible. And that’s precisely what’s under fire now.

The pitfalls of using third-party cookies for retargeting

The problems with cookie-based retargeting aren’t new, but they’ve reached a tipping point. 

For starters, cookie lifespans have shortened dramatically. Even when cookies aren’t blocked, they often expire within days instead of weeks. If you’re running campaigns with longer nurture cycles, this compression makes it challenging to stay in front of prospects over time.

In addition, browsers increasingly restrict third-party cookies. For example, Safari introduced Intelligent Tracking Prevention (ITP) in 2017, and Firefox rolled out Enhanced Tracking Protection (ETP) in 2019. 

These features block third-party cookies by default, meaning millions of users were already invisible to retargeting efforts before they even knew what cookies were.

Ad platforms feel this loss. When cookies are blocked, conversion events don’t reach them, and audience data degrades. Campaign optimization suffers because platforms can’t attribute conversions accurately or build reliable lookalike audiences. As a result, budgets are spent on campaigns that are harder to measure and optimize effectively.

Also, global privacy regulations such as the EU’s General Data Protection Regulation (GDPR) and the California Privacy Rights Act (CPRA) don’t just restrict how cookies work; they restrict how you can use them legally. And if companies don’t comply, they risk fines and GDPR penalties.

The result is a shrinking pool of trackable users and campaigns that no longer scale as they once did.

What is cookieless retargeting?

Cookieless retargeting flips the model. Instead of relying on third-party cookies to track users across the web, you build retargeting audiences from data that users give you directly. Using information like email addresses, phone numbers, or behavioral data from your site, you can match that data against ad platform audiences using privacy-preserving methods.

Therefore, retargeting without cookies means you’re not surreptitiously following people across the web. You’re activating data they’ve explicitly permitted you to use. This respects browser restrictions and user consent while maintaining your ability to reach people who’ve already interacted with your brand.

Benefits of cookieless retargeting

The advantages of cookieless retargeting go beyond simply staying privacy-compliant. This approach improves how you build and activate audiences, leading to better performance and stronger relationships with your customers.

Easier to achieve and maintain privacy compliance

When you build retargeting audiences from consented first-party data, privacy compliance becomes easier. You’re not tracking users across sites. You’re using data they’ve explicitly shared with you under clear terms. 

The GDPR, CCPA, and other privacy regulations are designed to restrict invisible, nonconsented tracking, not the legitimate use of data users willingly provide. This alignment helps reduce legal risk and builds trust with your audience.

More accurate audience data

First-party data is inherently more accurate than inferred behavior from cookies. You know exactly who someone is, what actions they’ve taken on your site, and whether they’ve given you permission to contact them (and for what purposes.) 

This precision leads to better segmentation and more relevant ads. Instead of guessing based on fragmented cookie data, you’re working from a complete picture of how someone has engaged with your brand.

Stronger audience ownership

Cookie-based retargeting meant renting access to audiences through ad networks. Cookieless retargeting means owning the relationship. Your CRM data, email lists, and customer records become the foundation for your campaigns. 

This gives you independence from third-party tracking infrastructure and helps ensure your audiences remain accessible regardless of how browser restrictions or platform policies evolve.

Improved signal reliability

Server-side tracking and conversion APIs capture events even when browsers block client-side tracking cookies. This helps optimize campaigns and ensures ad platforms receive the data they need for attribution and audience building. 

The result is more consistent performance and better ROI, even as browser restrictions continue to tighten.

How does cookieless retargeting work?

The mechanics of advertising without cookies become clear once you understand the data flow. 

Everything starts with first-party data collection, including purchase history, surveys, account settings, communication preferences, and much more. This data lives in your systems: your CRM, your CDP, your marketing platform. 

When you want to retarget someone, you hash their identifiers — such as email addresses, phone numbers, or user IDs — and upload them to an ad platform like Meta, Google, or TikTok. 

Hashing transforms the data into a privacy-preserving format that can’t be reverse-engineered to reveal personal information. The platform receives these hashed identifiers and matches them against its user database. Successful matches become your retargeting audience.

Server-side tracking adds another layer. Instead of relying on browser-based pixels that can be blocked, server-side setups record user behavior directly on your server. 

When someone completes a conversion or triggers an important event, your server sends that signal to the ad platform’s conversion API. This happens server to server, thus completely bypassing browser restrictions.

Consent-based identifiers like Unified ID 2.0 take this a step further. These technologies use hashed, consented email addresses as a privacy-preserving alternative to cookies. Users opt in explicitly, and their identifier can be used for audience matching across participating platforms without exposing their actual email or personal data.

The key to making this work is system integration. You collect and manage user permissions. Your CRM or CDP stores first-party data. Your server-side tagging setup captures behavioral data and sends it to an ad platform through conversion APIs. Each component reinforces the others, creating a system that functions reliably without third-party cookies.

Setting up retargeting without cookies

Building a cookieless retargeting strategy requires rethinking how you collect data, manage consent, and integrate with ad platforms. Here’s how to approach it.

Invest in consent-driven first-party data collection

Everything starts with permission. If users don’t consent to data collection, you can’t build audiences. Use a consent management platform (CMP) to present clear, legally-compliant information and consent requests, and respect user preferences. Only collect data from users who’ve opted in (where legally required.)

Focus on high-value touchpoints: email signups, account creation, purchases, and content downloads. These interactions give you explicit identifiers you can use for retargeting. When asking for this information, make the value exchange clear. 

People are more willing to share data when they understand what they’ll get in return — whether that’s a discount, early access, or personalized recommendations.

Progressive profiling also helps. Instead of asking for everything up front, collect data over time as users engage with your brand. This reduces friction and improves completion rates.

Use a CMP to align consent and data activation

A CMP does more than display cookie banners. It ties user preferences to data activation, helping to ensure you only use data in ways users have approved. When someone consents to the use of marketing cookies, your CMP signals that permission to your tagging setup, enabling retargeting pixels and audience matching.

This alignment is critical for privacy compliance. You can’t rely on assumed consent or outdated permissions. Your CMP creates an audit trail that shows exactly what users agreed to and when, along with changes to those preferences over time.

Deploy server-side tagging for reliable data flows

Server-side setups record user behavior without relying on cookies. The container you create sits between your website and ad platforms. It receives events from your site and forwards them to platforms like Meta, Google, and TikTok through secure server-to-server connections.

This approach offers several advantages. It bypasses browser restrictions, reduces data loss from ad blockers, and gives you more control over which data is sent to each platform. It also improves data accuracy by eliminating client-side variables like inconsistent cookie lifespans or blocked tracking pixels.

It’s true that setting up server-side tagging requires technical infrastructure — either a cloud server or a managed solution — but the payoff is reliable data flows regardless of browser restrictions.

Integrate conversion APIs for audience building

Conversion APIs connect your server directly to ad platforms, thus sending conversion events and audience data without depending on browser-based tracking. Facebook CAPI, Google Enhanced Conversions, and TikTok Events API all work this way.

These APIs accept hashed identifiers, for instance, email addresses, phone numbers, or user IDs, along with event data like purchases, signups, or page views. The platform matches these identifiers against its user base and attributes conversions or builds retargeting audiences based on the match.

However, for optimal implementation, map your data schema to the platform’s API format and set up secure authentication. But once configured, these APIs deliver more reliable attribution and audience building than client-side pixels ever could.

Test list quality and performance continuously

Cookieless retargeting depends on data quality. If your email list is outdated or your CRM data is incomplete, match rates suffer and campaigns won’t perform.

Therefore, it’s important to regularly audit data sources, clean invalid records, and test how well audiences match against ad platform databases. Monitor match rates, audience sizes, and campaign ROI. If match rates are low, look into why. Are you collecting the right identifiers? Are users providing accurate information?

Then, iterate based on what you learn. If email-based matching outperforms phone numbers, prioritize email collection. If certain segments perform well, invest more in building similar lists.

Server-side tracking and cookieless retargeting

Server-side tracking is the backbone of retargeting without cookies. When someone interacts with your site, your tagging setup sends event data to your server, rather than directly to ad platforms. Your server processes the data, enriches it with first-party identifiers from your CRM, and forwards it to ad platforms through conversion APIs.

This bypasses browser restrictions entirely. You decide what data gets sent, how it’s formatted, and which platforms receive it. You can include context like customer lifetime value or purchase history that wouldn’t be available through client-side tracking. And because data flows server to server, ad blockers and browser settings don’t interfere.

However, it’s worth noting that server-side tracking still requires user consent. Simply because data isn’t stored in a browser doesn’t mean it’s exempt from the requirements of privacy regulations. It’s important to respect user preferences and only activate tracking for users who’ve explicitly consented.

Retargeting in a cookieless world is possible

Retargeting isn’t ending; it’s transforming. The shift away from third-party cookies creates an opportunity to build more transparent, resilient strategies rooted in consent and first-party data. 

By investing in server-side tracking, conversion APIs, and strong data collection practices, you maintain the ability to re-engage your best audiences while respecting privacy and future-proofing your campaigns.

Reaching the right audience has always been about understanding intent and context. For years, third-party cookies simplified this by tracking users across websites. But as privacy becomes a priority for individuals and regulators, that shortcut is disappearing.

Cookieless targeting offers a more sustainable path forward. It enables you to connect with relevant audiences using methods that respect privacy boundaries. The good news is that the infrastructure is already here. The shift to audience targeting without cookies is less about losing capability and more about rebuilding it on a foundation that lasts.

Key takeaways

• Targeting cookies track users across websites to build advertising profiles, but privacy regulations and browser restrictions are phasing them out.
• Cookieless targeting replaces cross-site tracking with privacy-safe methods.
• First-party data activation provides a reliable foundation for audience targeting without cookies.
• Contextual targeting analyzes page content, keywords, and metadata to place ads in relevant environments.
• Server-side tagging improves data quality and creates cleaner signals for ad platforms while maintaining privacy controls.

What are targeting cookies?

Targeting cookies are small files placed on a user’s device to track their browsing behavior across different websites. These cookies collect information about pages visited, content viewed, searches performed, and purchases made. 

This data is then used to build detailed profiles that help marketers segment audiences and deliver personalized ads.

One common method for gathering this data is through the use of third-party cookies, which enable tracking across multiple websites. Third-party cookies are placed by ad networks or other external services when someone visits a participating site. They then track their activity across all sites in the network. 

This enables cross-site visibility for retargeting campaigns, lookalike audiences, and behavioral targeting.

But this same capability raises privacy concerns. Users often don’t know who is tracking them or how their data is being used. Regulators have responded with stricter consent requirements, and browsers have implemented tracking protections that block or limit these cookies by default.

What is cookieless targeting?

Cookieless targeting helps identify and reach audiences without relying on third-party cookies or cross-site tracking. Instead of following users across the web, it uses alternative methods that respect privacy boundaries while still enabling personalized ads.

The approach shifts the focus from individual tracking to signals that respect privacy boundaries. This includes information that users share directly with your brand, the context of where ads appear, aggregated audience groups, and consent-based identifiers.

However, cookieless targeting isn’t a single technology or method. Instead, it’s a collection of tools and strategies that work together to help brands keep their advertising impactful while respecting user privacy.

The common thread in all these methods is putting user privacy first while still connecting with the right audiences. You can reach specific people and track how campaigns perform using transparent, privacy-friendly practices instead of hidden tracking.

Why start targeting without cookies?

Cookies are still a fundamental tool in online advertising. However, traditional targeting alone no longer achieves the same results.  People are increasingly aware of tracking practices and skeptical of how brands use them. 

Therefore, by using transparent, privacy-respecting targeting methods, you’re showing that you value user privacy. This helps to build long-term relationships rather than just short-term conversions.

In addition, privacy regulations add legal pressure. The EU’s General Data Protection Regulation (GDPR) requires explicit consent for tracking and gives users the right to access and delete their data. 

In the U.S., the California Privacy Rights Act (CPRA) requires that people be able to opt out of certain types of data access and use, and multiple states are implementing similar privacy laws. 

Meeting these requirements with traditional cookie-based targeting has become challenging and risky. Cookieless methods align better with regulatory expectations by design.

Given regulatory requirements, browsers have also adapted. Safari blocked third-party cookies in 2020, Firefox followed, and Chrome continues to expand privacy controls. Your targeting infrastructure must function across all browsers, which means it can’t depend on third-party cookies.

Beyond privacy compliance, there are practical advantages to cookieless targeting. Ad blockers, browser restrictions, and user privacy settings create gaps in cookie-based tracking that undermine data quality. 

Audience targeting without cookies relies on more stable signals that aren’t blocked or hampered by privacy tools. This produces more accurate data and better campaign performance. Brands that adapt now will have refined strategies and infrastructure in place while others scramble to catch up.

How does cookieless targeting work?

Cookieless targeting often includes contextual targeting — placing ads based on a page’s content rather than personal data — and other privacy-friendly methods like first-party data and cohort-based targeting.

To target your audience without cookies, you need to identify audiences using signals that don’t rely on cross-site tracking. This approach combines three main methods, each addressing a different aspect of audience reach.

Step 1: Use your first-party data

When someone interacts with your brand, such as making a purchase, signing up for emails, or creating an account, you collect first-party data with their consent. 

This information lives in your Customer Relationship Management (CRM) platform, analytics platforms, or customer databases. You own it, users have shared it knowingly, and it provides accurate insights into their preferences and behavior. This becomes the foundation for building targetable audience segments.

Step 2: Target based on content instead of cookies

Cookieless contextual targeting focuses on the environment where ads appear rather than who is viewing them. Ad platforms analyze page content, keywords, topics, and metadata to determine relevance. 

For example, someone reading an article about hiking gear might see outdoor equipment ads based on the content they’re engaging with right now, rather than their browsing history. This method helps you reach new audiences while keeping ads relevant.

Step 3: Protect privacy while reaching the right audiences

Tools like browser APIs group users into categories based on shared interests without exposing individual identities. Hashed email addresses create privacy-safe identifiers that match users across platforms with their consent. These technologies enable you to maintain targeting capability while limiting exposure of personal data.

The technical infrastructure supporting these strategies also matters. For instance, server-side tagging helps you control data before it reaches ad platforms: filter, anonymize, or enrich information in line with privacy requirements and user consent. This produces cleaner signals that work better with ad platforms while respecting privacy boundaries.

Five strategies for cookieless targeting and advertising

Transitioning to cookieless targeting involves a mix of complementary strategies. Some focus on your existing customers, others expand reach, and a few strengthen the technical infrastructure.

Here’s how each strategy contributes to your overall approach.

First-party data activation

First-party data is information that users share directly with your brand. This includes email signups, loyalty programs, account registrations, purchase transactions, and website behavior. It’s privacy-compliant because users provide it knowingly and with consent.

The key is collecting this data transparently. Explain how you’ll use it to improve their experience, then integrate it with your CRM to turn customer information into targetable audiences. 

Next, use that information to export segments to advertising platforms as custom audiences or lookalike models. For example, someone who bought running shoes becomes part of an “active lifestyle” segment you can target with related products.

Progressive profiling helps, too. Ask for basic information at first, then gradually collect preferences through follow-up interactions. This approach makes your first-party data even more accurate and complete, providing stable, compliant insights that can power targeted campaigns.

Even so, first-party data only reaches people who already know your brand. To expand beyond that audience, contextual targeting fills the gap.

Contextual targeting

Contextual targeting places ads based on the page or app context at the moment of the ad request. This includes its topics, entities or keywords, taxonomy, and sometimes sentiment, suitability, or metadata rather than on a person’s identity or browsing history. It matches ads to the content context, not prior behavior.

Semantic analysis takes contextual targeting a step further by interpreting the meaning and intent behind content, not just the words on the page. 

For instance, an article about reducing debt and another about investment strategies both mention money, but they reflect different user intentions. Semantic analysis recognizes these distinctions, helping ad systems to match relevant ads to the most appropriate content environment.

You can also use category targeting to place ads across all content within topics like technology, health, or finance. This reaches audiences based on what they’re interested in right now.

Contextual targeting methods can also adapt in real time. So someone reading breaking industry news sees ads that align with that moment. At the same time, you retain control over where your ads appear by setting content guidelines and exclusions, thus protecting your brand.

Cohort-based targeting

Cohort-based targeting groups users with shared interests rather than tracking them individually, enabling advertisers to reach audience segments without exposing personal data.

A key example is Google’s Privacy Sandbox initiative, which includes the Topics API. Instead of assigning users to persistent cohorts, the browser identifies a few general interest categories, such as fitness or home improvement, based on recent browsing activity. 

These topics are generated and stored locally, allowing advertisers to tailor ads to relevant themes without seeing an individual’s browsing history or identity.

The size of each cohort is important for privacy. Groups need enough members to keep individuals anonymous, and the Privacy Sandbox enforces minimum cohort sizes to prevent re-identification. This approach balances privacy and targeting effectiveness, allowing advertisers to reach relevant audiences without persistent user profiles.

Identity and consent-based targeting

Consent-based identity solutions create identifiers that users explicitly agree to share. These function similarly to third-party cookies but are built on transparency and permission.

Hashed email addresses are one method. When someone shares their email with consent, it gets cryptographically hashed into a privacy-safe identifier. Platforms with the same hashed email can recognize the user across touchpoints without storing the actual address. This enables frequency capping, attribution, and audience matching.

Your consent management platform then validates these identifiers. It collects consent, passes that state to identity solutions, and stops the identifier if someone withdraws permission.

Server-side tagging and tracking

Server-side tagging strengthens cookieless targeting by giving you control over the data your website collects and shares, even without relying on third-party cookies. 

When someone visits your site, their interaction data goes to your server first. Here, you can filter sensitive information, enforce consent rules, add first-party context, and format events correctly for each platform. This produces cleaner, more reliable signals that can power targeting without cookies.

Ad platforms benefit as well. APIs like Facebook Conversions API and Google Ads API receive validated events that aren’t blocked by browser privacy settings, improving match rates and attribution accuracy.

Privacy controls also become more granular. You can strip personally identifiable information before sending data, apply rules based on consent status, or route data differently depending on user preferences.

Server-side processing offers performance advantages, too. Fewer client-side scripts mean faster page loads, and processing on your servers reduces ad blocker errors, making your targeting data more dependable.

Challenges and solutions for implementing cookieless advertising strategies

Cookieless targeting opens new opportunities, but it also comes with its own set of challenges. Knowing what to expect and how to address it makes the transition smoother and helps to ensure your marketing campaigns keep generating results.

Balancing reach and precision

Each cookieless method has trade-offs. 

First-party data is accurate and high quality, but only reaches people who’ve already interacted with your brand. Contextual targeting expands your reach, but is less precise than behavioral profiles. Cohort-based methods cover the open web, but at a broader level. 

The solution is to combine approaches: Use first-party data for retargeting, contextual targeting for broader reach, and cohorts for open-web campaigns.

Rethinking attribution

Without cross-site identifiers, tracking every touchpoint is harder. Traditional multi-touch attribution models need reworking. 

Move toward modeled attribution and marketing mix analysis, which uses aggregated data and statistical methods to estimate campaign impact. 

Server-side tracking can help here too, providing cleaner conversion signals to ad platforms.

Managing technical complexity

Implementing server-side tagging and privacy APIs requires new skills. So start small: Set up server-side tracking for key conversion events first, build first-party data collection gradually, and test contextual targeting on a few campaigns before scaling. Expanding incrementally keeps the process manageable.

Handling consent efficiently

Collecting and honoring user consent adds operational work. You need to store preferences, apply them consistently, and respect opt-outs. 

A consent management platform automates much of this, centralizing collection and integrating with your ad tools.

Be future-ready using cookieless targeting strategies

Browser restrictions are here to stay, and privacy regulations will continue to expand. Therefore, your targeting needs to work within these constraints long-term.

Start now, even if third-party cookies still function in some places. First-party data takes time to build. Contextual strategies need testing. Server-side infrastructure requires investment. But the good news is that early adopters will gain experience while others scramble later.

When privacy is done right, it becomes a powerful competitive advantage. Brands that prioritize user privacy earn lasting trust, the kind that strengthens relationships and drives growth. The best part? The tools already exist, and you don’t have to wait for what’s next. Start using what’s available today.

With all of the creative effort that goes into writing website copy, thinking about legal documents, which are anything but lead magnets, might be the last thing on your mind. 

In this guide, we’ll explain in detail the differences and similarities among Terms of Service,Terms of Use, and Terms and Conditions, how you can use them, and what the goals of each document are so you can design your own with confidence. 

Terms of Use definition

Terms of Use (ToU), also called Terms of Usage, generally refers to a legal agreement between a website owner and its end users that specifies the rules users must follow when using that site or service. 

A Terms of Use policy can include: 

• Acceptable behavior and responsibilities for website visitors
• Details on data management, storage, and sharing
• Website disclaimers
• Details on the site owner’s rights if the rules are violated

Usually, a standard Terms of Use includes information about legal liability limits, intellectual property rights, and copyright disclaimer notices.

What is a Terms of Service agreement?

A Terms of Service (ToS) agreement is generally a legal document that defines the relationship between the website user and the service provider. 

While both ToU and ToS documents define the rules under which visitors can interact with website content, the distinction is that a ToS agreement defines those rules in the context of services rather than how information is used.

Information you can include in a Terms of Service:

• Descriptions and limitations of the services provided 
• User eligibility and responsibilities
• Subscription and refund policy terms (such as a 30-day money-back guarantee) 
• Data privacy protection and compliance

By including a Terms of Service document on your website, you can manage user expectations, minimize customer disputes, and limit your liability in the event of legal issues.

What does Terms and Conditions mean?

Terms and Conditions for services usually refers to a legal agreement that governs the relationship between a service provider and its users. The difference between Terms and Conditions and Terms of Service is that the Terms and Conditions document typically will provide details on product sales and how to handle monetary transactions in addition to the subscription and refund policy terms that both documents will provide.

Aspects of a Terms and Conditions (TaC) document for e-commerce include:

• Terms of product sale
• Payment methods and terms
• Shipping policy and delivery conditions
• Rights and responsibilities of the service provider, including the limitation of liability and the ‘all sales are final’ policy  

Overall, the Terms and Conditions document often includes general payment rules, disclaimers, and limitations of liability. It may also contain elements of other legal agreements, making this document generally more detailed than a Terms of Service.

Terms of Service vs Terms of Use vs Terms and Conditions: How do they compare?

In practice, the lines among Terms of Service, Terms of Use, and Terms and Conditions are blurry, as these titles are often used interchangeably. Companies often merge elements from all these documents to form a detailed, comprehensive agreement.

Still, there are differences in what each document tends to emphasize. We outline those differences in the table below.

Why ToU, ToS, and TaC are equally important

While businesses may prefer one term over another when choosing among Terms of Service, Terms of Use, and Terms and Conditions, each type of document is legally enforceable among the parties involved, regardless of the document title. You can decide on the title of your document based on the nature of your business and what your document emphasizes. 

In this section, we will use the terms interchangeably while explaining why you need to include at least one of them on your website.

Legal protection

The main reason to have a Terms of Service agreement is to legally safeguard your website and business. Clearly outlining the rules and restrictions helps establish a legal foundation to defend against possible lawsuits or conflicts. For example, if a user misuses your content or breaches your guidelines, you can rely on those terms to support your actions.

Managing user expectations

A well-crafted Terms and Conditions agreement also sets clear boundaries for user behavior and outlines your services. This clarity fosters a better user experience by reducing misunderstandings. 

Your terms should explicitly state: 

• What services are provided 
• How users can interact with your site or platform 
• What falls under acceptable use 
• When and how services might change 
• The consequences for breaching the terms

Limiting your liability

One of the most important roles of a Terms of Use is to try to protect your business from potential legal problems. You can lower legal risks and lessen your liability by:

• Defining the scope of your company’s responsibility 
• Representing warranty disclaimers 
• Setting liability limitations 
• Stating intellectual property rights 
• Specifying applicable jurisdiction and governing law

Minimizing customer disputes

By clearly defining terms like refund policies and prohibited actions in your Terms of Service document, you can also prevent potential conflicts:

• Clearly explain service delivery 
• Set clear expectations about the availability of your service
• Describe refund and cancellation policies in detail
• Define the procedures for dispute resolution 
• Establish communication channels for complaints

Preventing copyright infringement

Your Terms and Conditions agreement can also help protect your intellectual property and set user interaction guidelines. Your agreement can:

• Clearly state content ownership
• Determine acceptable use of your materials
• Set up procedures for copyright complaints 
• Indicate consequences for violations 
• Outline user-generated content rights

Best practices for drafting Terms of Use/Terms of Service/Terms and Conditions

While looking at examples, you’ll see that companies may use any of the above terms. For instance:

• Apple and Instagram both use the name “Terms of Use”
• Google has a “Terms of Service” page
• New York Times uses a “Terms of Sale” document
• Amazon offers “Conditions of Use” for website users

Nevertheless, all these companies generally adopt the same approach to designing their agreement. For an equally effective agreement, consider the following:

1. Introduction and acceptance of terms: Start with a section that introduces the parties, explains the purpose of the document, and states that by using the website, users agree to be bound by these terms.
2. User eligibility: Outline any age restrictions or other eligibility criteria for using your website, like being at least 18 years old.
3. User accounts and registration: If your site includes registration, add details on account creation, password requirements, user security responsibilities, and conditions for terminating or suspending accounts.
4. User conduct and prohibited activities: Clearly state the expected user behaviors and any prohibited actions, such as hate speech, harassment, spamming, or engaging in other harmful activities.
5. Intellectual property rights: Explain the website’s content ownership and policies on user-generated content. 
6. Privacy policy: Add a section that explains how user data is used, collected, shared, and protected.

7. Disclaimer of warranties. If applicable, state that you cannot guarantee the reliability or accuracy of specific content or services on your website.
8. Limitation of liability: Define the extent of your company’s liability for damages resulting from the use of your website. This usually includes limits on monetary damages and exclusions for specific types of losses.
9. Dispute resolution: Outline how disputes between users and your website will be addressed, including the applicable law, jurisdiction for legal actions, and options such as arbitration.
10. Termination clause: Explain under what circumstances you may terminate a user’s access to your website and what happens to the user data or content upon termination.
11. Changes to terms: Include a provision as to whether you may modify the Terms of Use and explain how users would be informed of these changes.
12. Contact information: Provide users with information about where and how to send their questions or concerns regarding the agreement.

Practical tips for writing effective ToU, ToS, or TaC agreements

• Research industry standards: Learn common practices, but be sure to customize your document for your business needs.
• Evaluate website needs: Write the agreement text by considering your business type, website content, user interactions, and any special features or services you offer.
• Be clear and concise: Write in plain language, without legal jargon and unnecessary ambiguity.
• Make your terms easily accessible: Place a visible link to the agreement in a highly visible location, like your website footer.
• Adapt the agreement to your jurisdiction: Get legal consultation on whether your agreement complies with relevant laws, including data privacy regulations like the General Data Protection Regulation (GDPR).

Usercentrics solutions help simplify complex legal compliance

Businesses that need to meet legal standards and future-proof their businesses for ever-evolving laws need robust tools to manage and automate regulatory requirements. Protecting your business requires specific legal documents to provide transparency and build trust in your operations. 

Usercentrics delivers solutions to seamlessly collect and manage user consent across your tech stack and maintain a comprehensive and up-to-date privacy policy. Save time and resources while you protect your business and build a future-proof Privacy-Led Marketing strategy. Comply with global regulatory requirements and ad platforms’ policies today and as the legal landscape changes.

Let’s state the obvious: Web tracking is evolving. As browsers phase out third-party cookies and implement privacy controls, and privacy regulations set new standards, the way you measure user behavior is changing.

Cookieless tracking offers a new way forward. It helps you gather meaningful insights while respecting user privacy and staying privacy-compliant. You get reliable data that works with the web’s privacy-first direction, not against it.

Key takeaways

• Third-party cookies are being phased out due to browser restrictions, privacy controls, and data privacy regulations
• Cookieless tracking shifts data collection toward first-party sources and server-side analytics instead of cross-site identifiers
• Server-side tracking offers the best balance of control, data quality, and privacy protection
• User consent is still required for most cookieless tracking methods under privacy regulations

What is cookieless tracking?

Cookies are small text files placed on a website to track website visits and optimize browsing behavior. They serve the function of storing and processing user information when visiting a website.

Cookieless tracking is an alternative form of tracking. Instead of placing tracking files in browsers that follow users across websites, cookieless web analytics measure behavior using alternative strategies.

Some methods use first-party cookies, which are set by your own domain, while others skip cookies entirely. The connecting thread is moving away from third-party cookies that track users across the web.

Why are cookies being phased out?

The move toward cookieless tracking reflects broader changes in regulation, browser policies, and user expectations.

Privacy laws such as the EU’s General Data Protection Regulation (GDPR) and the California Privacy Rights Act (CPRA) set stricter requirements for transparency and consent. 

Because third-party cookies track users across multiple sites and share data with other parties, they are difficult to reconcile with these standards. Many organizations have found traditional cookie-based tracking increasingly hard to make privacy-compliant.

Browsers have reinforced these requirements. Safari blocked third-party cookies by default in 2020, followed by Firefox. Google also gives users the option to opt out of third-party cookies. Even with shifting timelines, the direction is clear: Browsers are aligning with stricter privacy standards.

At the same time, users have changed their expectations. People are more aware of how their data is used and expect companies to handle it responsibly. Ad blockers are widely used, privacy settings are actively managed, and trust in data handling influences consumer behavior.

Together, these legal, technical, and behavioral factors are driving the decline of third-party cookies, making tracking without cookies increasingly necessary.

Benefits of cookieless tracking

Switching to cookieless measurement helps to address privacy compliance needs, and it also brings advantages that can strengthen your analytics foundation. 

Here’s what you gain from making the transition.

More accurate data collection

Third-party cookies have become increasingly unreliable. Cookieless methods help to ensure that meaningful behavioral data continues to be captured even as cookies disappear. Instead of relying on fragile third-party signals, your analytics are grounded in direct, verifiable interactions with users.

Better data quality and consistency

When data is no longer fragmented across multiple cookie sources, measurement becomes more consistent across devices and sessions. Cookieless analytics techniques help reduce duplication, attribution errors, and data loss. This results in a more accurate and unified view of the customer journey.

Faster site performance

Fewer third-party scripts lead to faster load times. Cookieless web tracking typically requires fewer browser-side calls, reducing page weight and improving overall site performance. These factors directly influence user experience, engagement, and search visibility.

Greater privacy and control

Cookieless approaches emphasize transparency and user choice. They give organizations greater control over what data is collected, how it is processed, and when it is shared with partners. This improves data governance and supports compliance with privacy standards while reinforcing user trust.

Future-proof measurement

More and more people are gravitating towards privacy-first experiences. Cookieless tracking helps to ensure your measurement framework remains resilient as browsers, devices, and regulations continue to limit traditional identifiers. Rather than adapting reactively to each new restriction, you operate within a model built for the privacy-centric future of the web.

How does cookieless tracking work?

The shift to cookieless tracking changes where and how you collect data. Instead of relying on cross-site identifiers, you focus on first-party data within your own domain and use server-side processing to handle analytics.

Here’s the crucial difference: When someone visits your website, their interactions are recorded using methods that respect browser privacy controls and give you direct data ownership. 

This might mean using first-party cookies (which are still allowed), processing data server-side before it reaches analytics platforms, or using privacy-preserving APIs that aggregate data without exposing individuals.

Server-side tracking sits at the heart of most cookieless approaches. Rather than tracking scripts running in the user’s browser and sending data directly to third parties, you route everything through your server first. 

Your server receives the data, processes it according to your requirements, and then forwards it to analytics tools. This layer of control is what makes cookieless tracking both more private and more reliable.

Cookieless tracking methods explained

Cookieless tracking works based on identifying and tracking users without relying on cookies, which are traditionally used to store user data on their devices. Instead, it uses alternative cookieless analytics methods, such as device fingerprints, server-side tracking, and other technologies, to gather and process data.

First-party data collection

First-party data collection refers to gathering information directly from users through your brand-owned channels, such as websites, apps, or CRM systems. This includes contact details, purchase history, preference settings, and on-site behavior.

Unlike third-party data, first-party information is collected with a direct relationship and usually under clear consent, making it both privacy-friendly and highly valuable. 

Even if first-party cookies are used, they operate within your domain and do not raise the same cross-site tracking concerns. This method forms the foundation of most sustainable cookieless strategies.

Privacy-preserving APIs

Privacy-preserving APIs are browser-based technologies designed to enable essential measurement functions, such as attribution or conversion tracking, without revealing personal identifiers. One example of this is Apple’s Private Click Measurement (PCM).

This kind of API aggregates and anonymizes user data to ensure that individual users cannot be identified, thus providing a middle ground between measurement accuracy and privacy compliance. 

While they currently have limitations compared to traditional cookie-based tracking, they represent the direction in which browsers are steering the future of web measurement.

Cookieless analytics platforms

Cookieless analytics platforms offer website insights without storing cookies or personal identifiers. Instead, they provide aggregated metrics like page views, referrers, device types, and geographic regions.

These tools are designed with privacy and legal compliance in mind, making them a good fit for organizations that value transparency or have limited data processing needs. However, because they do not track users across sessions or devices, they deliver less granular data than traditional analytics solutions like Google Analytics or Adobe Analytics.

Server-side tracking 

Server-side tracking routes user interaction data through your own servers before sending it to analytics or marketing platforms. This method provides full control over how data is collected, transformed, and shared. You can filter or anonymize information before it leaves your environment.

While technically more complex and resource-intensive to implement, server-side tracking offers significant advantages in data quality, accuracy, and compliance flexibility. It can also serve as a bridge between traditional analytics and a fully cookieless ecosystem.

How to start using server-side tracking

Server-side tracking offers a strong balance of data quality, control, and privacy compliance. While it involves some technical work up front, the long-term benefits make it a worthwhile investment for marketers who want more reliable data without compromising user trust.

1. Choose a server-side tagging solution: Google Tag Manager (GTM) Server-Side is the most common option. But you can also run server-side tracking directly through Usercentrics’ server-side solution, which provides built-in consent handling and streamlined configuration.
2. Set up server infrastructure: For GTM, you’ll host a tagging server on your own domain or subdomain (e.g., via Google Cloud Run) to keep the setup in a first-party context. Alternatively, Usercentrics offers a managed server-side tagging option — with prebuilt templates for self-hosting — that streamlines hosting, consent-state validation, and routing of approved data. This removes much of the manual server setup work.
3. Configure your client-side tracking: Update your website tags to send data to your new server endpoint rather than directly to Google Analytics.
4. Implement server-side processing: Process incoming data on the server, apply Usercentrics consent signals, filter or enrich as needed, and forward only approved data to analytics platforms.
5. Test and validate: Check that consent choices are correctly applied and that no data flows without a valid legal basis.
6. Monitor and maintain: Set up alerts and review regularly to keep your server-side setup reliable and compliant as privacy rules evolve.

The initial setup takes effort, but once running, server-side tracking provides more stable measurement than client-side alternatives.

Best practices to implement cookieless tracking

Implementing cookieless measurement effectively requires more than simply replacing old technologies. It’s about rethinking how data is collected, governed, and interpreted in a privacy-first environment.

The following best practices help ensure your implementation remains privacy-compliant, resilient, and capable of generating accurate, actionable insights.

Start with consent management

Even in a cookieless world, user consent remains central to privacy compliance. Most tracking methods, including first-party data collection or server-side processing, still involve personal data under definitions in privacy laws like the GDPR or CCPA.

A consent management platform (CMP) helps you collect, manage, and honor user choices consistently across all your tracking touchpoints. It enables transparency while providing the flexibility to adjust consent flows as regulations evolve.

Prioritize first-party data

Base your analytics and personalization strategies on data collected directly from users on your own properties. First-party data — such as purchase history, behavior, or preferences — is both privacy-safe and sustainable because it’s gathered with a direct user relationship. 

Investing in first-party infrastructure strengthens trust, enables accurate insights, and reduces reliance on external identifiers that are being phased out by browsers.

Document your data flows

Transparency starts with understanding your own systems. Map out how data moves from user interactions through your servers, APIs, and analytics platforms. 

Documenting data flows is essential for demonstrating compliance, identifying potential risks, and troubleshooting inconsistencies. It also helps align internal teams around a shared understanding of how and where user data is processed.

Test across browsers and devices

Privacy protections vary by browser and device. Safari’s Intelligent Tracking Prevention (ITP) and Firefox’s Enhanced Tracking Protection (ETP) behave differently. Testing across these environments helps to ensure your tracking setup continues to perform reliably and that your analytics remain consistent, regardless of user context.

Focus on meaningful metrics

Cookieless measurement doesn’t require tracking everything. Identify which metrics truly drive business outcomes and limit data collection to what’s necessary to measure them accurately. This data minimization principle improves privacy compliance, reduces complexity, and helps to ensure your teams focus on insights that actually matter.

How will a cookieless future affect marketers?

The shift to a cookieless web is transforming how marketers understand audiences, measure performance, and optimize campaigns. As third-party identifiers disappear, attribution becomes more modeled and aggregated, focusing on trends and probabilities rather than detailed individual journeys. 

While this may reduce precision, it also encourages a healthier, more privacy-aligned approach to measurement.

From a technology perspective, new tools and frameworks are becoming essential. These require investment and technical capabilities, but they enable marketers to maintain insight and performance in a privacy-compliant way.

Ultimately, the cookieless future is not a loss of capacity or precision, but a recalibration of digital marketing. It shifts the focus from invasive tracking to transparent, trust-based engagement. 

Marketers who adapt early can not only stay privacy-compliant, but also build a more resilient and future-proof data strategy to thrive in a privacy-first world.

For marketers, disclaimers may seem like dry and pointless — but necessary — text that legal teams insist on including. Often, teams copy and paste the disclaimer text from their competitors and don’t give much thought to the content. That is, until the first legal notice arrives.

In this guide, we provide you with disclaimer examples you can adapt for your business. More importantly, we’ll show you what a disclaimer statement is, who they are geared toward, and how to use and adapt a disclaimer sample to your business needs.  

Key takeaways 

• Understanding disclaimers: Learn what disclaimers are and why they are essential for businesses.
• Key differences: Distinguish among disclaimers, privacy policies, and terms of service.
• Importance of disclaimers: Discover how disclaimers build trust, can help limit liability, and clarify responsibilities.
• Common disclaimer types: Explore various disclaimer examples, including fair use, copyright, email, medical, YouTube, views expressed, affiliate, no responsibility, music copyright, and AI disclaimers.
• “Do Not Sell Or Share My Personal Information” Notice: Understand the importance of this disclaimer for CCPA/CPRA compliance.
• Crafting effective disclaimers: Get tips on how to write clear, specific, and legally sound disclaimer statements.
• Strategic placement: Learn where to place disclaimers for maximum visibility and impact.
• Best practices for disclaimers: Ensure long-term effectiveness with regular updates and comprehensive compliance strategies.

What’s a disclaimer and why does it matter?

A disclaimer statement can explain the limits of a company’s responsibility for information, products, or services it provides. It’s a notice designed to protect a company from potential third-party claims.

For instance, if you shop for health or wellness products, you’re very likely to see a product disclaimer like: “This statement has not been evaluated by the Food and Drug Administration. This product is not intended to diagnose, treat, cure, or prevent any disease.” 

This message can be strengthened by a website disclaimer warning, which informs you that “[Entity’s website] is intended for informational purposes only and should not be considered a substitute for the advice of a qualified medical practitioner.” 

In this example, the company is openly communicating what areas of responsibility belong to the business in a medical context and which belong to website visitors. This varies depending on the products or services offered by the entity.

A legal disclaimer can be your first line of legal protection. It helps readers set their expectations of your services, making it clear what you offer and can minimize potential liabilities that may arise from disputes.

Key differences among disclaimers, privacy policies, and terms of service

A disclaimer message is part of a company’s overall legal and compliance framework that also includes a privacy policy and a terms of service agreement. Each serves a distinct purpose.

Why are disclaimers important?

Disclaimers aren’t always legally required, but are valuable as a disclaimer message notifies users of potential risks and limitations and can help protect companies from lawsuits or other actions. Providing a full disclaimer also supports a business by:

• Building trust and transparency by telling users clearly what to expect
• Defining boundaries of responsibility and warranty
• Clarifying roles (e.g., user responsibilities vs. provider responsibilities)
• Supporting compliance in regulated sectors (e.g., healthcare, finance)

Building trust and transparency with users

In addition to being legal protection, a clear and accessible disclaimer message is also a concrete demonstration of respect for your customers, which can foster trust.

• Inform users of any limitations, potential risks, or legal boundaries related to the content covered by the disclaimer
• Demonstrate the company’s transparency and accountability
• Contribute to the provider’s credibility (in case of copyright notices)
• Clearly separate information intended to be useful, opinions, or estimates from guarantees or legally binding statements
• Demonstrate the business’s dedication to regulatory compliance as well as best practices for customer experience

Serving as a warning, disclaimer text clearly communicates to users what to expect and how much responsibility the business assumes. It can decrease misunderstandings and the risk of legal disputes. 

Straightforward, accessible disclaimers enable businesses to protect themselves legally while being transparent with customers, which is important to build long-term engagement and loyalty.

Limiting liability

Disclaimers can also limit a company’s liability by clearly defining the scope and boundaries of its responsibility for specific actions, information, or outcomes, including: 

• Clarifying your company’s responsibilities to minimize misunderstandings about liability
• Informing users about risks or limitations associated with using a product, service, or content, which can help you avoid legal claims resulting from unexpected issues
• Disclaim responsibility for issues beyond your company’s control, like third-party content or product misuse
• Limit your company’s commitment or warranty in clear, specific terms to help manage error-related risks, e.g., inaccuracies or unforeseen events

Although a disclaimer warning alone does not excuse a business from legal obligations and responsibilities, it can help to minimize its risk of legal problems for occurrences outside of its control. 

Clarifying the scope of responsibility

Disclaimers clearly define what falls under the business or website owner’s responsibility and the cases and areas in which the business has no liability. These can include mistakes in content, damages from misusing products or services, or errors in third-party information.

A well-crafted disclaimer defines the limits of responsibility and clarifies what uses — and resulting potential risks — are beyond the provider’s control. It emphasizes that users bear responsibility for their use of the products, services, or information, and often notes that the business isn’t responsible for user-generated content, third-party links, or specific damages.

To be considered an effective warning, a disclaimer message should use simple language, clearly define the areas of responsibility, and be easily visible or accessible. Otherwise, it may not be legally enforceable.

Complying with regulatory requirements 

Disclaimers help businesses comply with regulatory requirements by communicating information, warnings, and limitations that protect both visitors and businesses. There are several specific areas where a comprehensive disclaimer helps protect a company: 

• Legal disclosures: Many industries — especially highly regulated ones like finance, healthcare, and pharmaceuticals — require that companies inform their users about potential risks and side effects, where applicable.
• Product or service scope: The disclaimer warning defines responsibilities and helps to prevent misinterpretation.
• Updates: Businesses must update their disclaimers regularly to maintain ongoing compliance as laws, business operations, technologies, and other factors change.

Common disclaimer types (with examples)

Below are disclaimer examples and templates to help you get started. Always tailor template content to legal requirements, business operations, and other relevant context.

Fair use disclaimer

Potential users of this disclaimer example: Educational platforms, critique and commentary sites, news outlets, nonprofit or advocacy websites, and research-based portals.

Fair use disclaimers can clarify when copyrighted material — text, visual, audio, or video — may be legally used without extra permission for criticism, commentary, news, teaching, research, or other purposes. 

What factors to consider before applying a disclaimer sample: 

1. Purpose: Is it likely considered fair use?
2. Type: Original creations like novels, movies, and other works of art have stronger protection compared to news reports and technical documents, for example.
3. Amount used: How much of the original material is to be used?
4. Market value: Your use should not harm the creator’s ability to profit from their work.

What to include in a fair use disclaimer statement:

1. Acknowledge that you use copyrighted material on your website and clarify that your company has no ownership over that material.
2. State the company’s intent for using the copyrighted material, which must be for commentary, education, or critique purposes. 
3. State that the fair use disclaimer does not provide absolute protection from copyright claims.

Place the disclaimer in a location that is easily accessible, such as in or linked from the website footer, or on a dedicated page.

Copyright disclaimer

Potential users of this disclaimer example: Creators who want to protect their original work.

Copyright disclaimers are legal notices that inform visitors about who owns the site’s or other platform’s content and what rights they have to use it. They claim ownership of original material and aim to deter unauthorized use, copying, and distribution.

Why you may need a copyright disclaimer:

1. Clearly communicate which person or entity owns the content.
2. Specify how users can interact with the content, e.g., prohibit usage entirely or permit sharing with attribution only.
3. State your intention to protect your content and deter infringement or plagiarism.
4. Help protect content from unauthorized copying, scraping, and plagiarism, e.g., resulting from AI access. The disclaimer can serve as a legal basis for requesting takedown from search engines and hosting platforms.

What to include in a copyright disclaimer statement:

1. A copyright symbol (©)
2. Creation or release date
3. Content creator’s or owner’s name
4. A statement of rights (e.g., “All rights reserved”)
5. Website’s domain name

Email disclaimers

Potential users of these disclaimer examples: Businesses meeting privacy compliance standards.

Email disclaimers are brief statements typically located at the end of emails, which aim to reduce an organization’s legal and financial liability. They clarify the sender’s position and address issues related to compliance, legal standards, and confidentiality.

Why you may need an email disclaimer:

1. Reinforce confidentiality and compliance obligations for the sender and recipient
2. Clearly outline who’s responsible for advice shared or for technical risks like viruses
3. Confirm that emails are of a noncontractual nature
4. Support compliance with regulations like the EU’s General Data Protection Regulation (GDPR), US privacy laws, HIPAA, and anti-spam laws.

Email disclaimer statement types:

1. Privileged and confidential disclaimers: Limit access to authorized recipients. Commonly used in legal, finance, and healthcare communications.
2. Liability disclaimers: Limit responsibility for errors, omissions, or damages resulting from reliance on the information in the email.
3. Newsletter disclaimers: Identify the sender and purpose of the message, and provide opt-out instructions to comply with anti-spam laws.
4. Security disclaimers: Alert users to potential risks like viruses or unauthorized access, and remind them to verify email authenticity and scan attachments.
5. GDPR disclaimers (for EU communications): Explain how personal data is processed, outline recipients’ rights, and reference your organization’s privacy policy.
6. HIPAA disclaimers (for US healthcare and insurance firms): Flag protected health information (PHI) and restrict access to authorized parties.

Medical / health disclaimers

Potential users of these content and product disclaimer examples: Anyone providing information related to health or wellness, including medical and wellness companies, health coaches, bloggers, app developers, influencers, fitness trainers, nutritionists, and others.

Medical disclaimers can clarify that the provided information isn’t a substitute for professional medical advice, treatment, or diagnosis. They generally state that reliance on the information is at the user’s own risk and encourage consultation with qualified healthcare providers. 

While health disclaimers apply to a broader scope of health and wellness providers, medical disclaimers are specific to clinical advice, diagnosis, or treatment.

Why you may need a medical disclaimer:

1. Protect health providers against liabilities
2. Reinforce that the services or content cannot replace professional healthcare advice
3. Clarify that content is meant to be informational 
4. Mitigate risks associated with spreading misinformation
5. Demonstrate ethical behavior

Medical disclaimer statement types:

1. Medical advice legal disclaimer: The content provided doesn’t include professional medical advice or treatment.
2. “Please consult your doctor” disclaimer: Recommends consulting healthcare professionals instead of relying on content.
3. “Educational purposes only” disclaimer: The purpose of the provided content is shared only for learning and not self-diagnosis or treatment.
4. Mental health disclaimer: Mental health-related content is informational in nature and recommends that users seek the help of professionals.
5. “I am not a doctor” disclaimer: Explains that shared personal health advice is based on experience only and is not advice from a licensed medical expert.
6. Drug disclaimer: Clarifies the limits of drug-related content and states that content is not an endorsement or recommendation of specific medications or other products.
7. Health and wellness disclaimer: The health-related content is for information purposes only and does not replace professional medical guidance.
8. Supplement product disclaimer: Statements about supplements have not been reviewed by authorities and advertised products aren’t meant to treat health conditions.

YouTube copyright disclaimer

Potential users of these disclaimer examples: Video creators who want to protect their original content from liability or from being used unlawfully by other creators.

Video creators use YouTube copyright disclaimers to clarify the use of copyrighted material, assert intellectual property rights, or limit liability when uploading videos. 

Why you may need a YouTube copyright disclaimer:

1. Mitigate the risks of video takedowns, channel strikes, and associated monetary losses
2. Clearly communicate the use of copyrighted material
3. Demonstrate compliance with copyright law

YouTube disclaimer statement types:

1. Fair use disclaimer: States that copyrighted content is used for commentary and educational purposes in accordance with fair use laws.
2. Parody or satire disclaimer: Highlights that copyrighted content is used in a transformative manner.
3. YouTube music copyright disclaimer: States the ownership status of music used in videos and how that music is allowed to be used.
4. Other related types: No copyright infringement intended, Creative Commons attribution disclaimer, and Non-commercial use disclaimer.

Views expressed disclaimer

Potential users of these disclaimer examples: Professionals with public profiles, freelancers, contractors, content creators, academics, and those addressing controversial topics outside their professional boundaries.

A views expressed disclaimer, also known as the “opinions expressed disclaimer,” clarifies that an opinion belongs to the author personally and does not represent or cannot be applied to an organization, employer, or entity to which they are professionally connected. 

Why you may need a views expressed disclaimer statement:

1. Prevent misinterpretation and manage audience expectations 
2. Set personal responsibility to protect an organization
3. Reduce legal risks

Affiliate/advertising disclaimers

Potential users of these paid advertisement disclaimer examples: Any business or individual using affiliate marketing, including Business-to-Consumer (B2C) companies, Business-to-Business (B2B) companies, bloggers, and review sites.

Affiliate disclaimers inform visitors that site owners may earn commissions from affiliate links. They can support legal compliance and credibility for affiliate marketers. It’s important to add this disclaimer to a highly visible location on the page where the affiliate links are placed. 

Laws that require using an affiliate legal disclaimer:

Various global data privacy laws include requirements for disclosing affiliate relationships:

• General Data Protection Regulation (GDPR): Mandates businesses in the EU be transparent about collecting personal data via affiliate links and requires explicit consent. 
• Data Protection Act: Mandates that UK businesses be transparent about collecting personal data via affiliate links and requires explicit consent.
• Federal Trade Commission: The FTC’s updated Endorsement Guidelines require US affiliates and influencers to disclose any financial relationships with promoted businesses.
• California Consumer Privacy Act (CCPA): Mandates sites targeting California consumers to disclose purposes of data collection, including if they sell personal data or use it for profiling or targeted advertising.
• Personal Information Protection and Electronic Documents Act (PIPEDA): Businesses in Canada should notify users when their data is used through affiliate marketing practices.
• Lei Geral de Proteção de Dados/General Data Protection Law (LGPD): Requires websites in Brazil to clearly inform users about data collection, including affiliate marketing efforts.
• The Privacy Act: Businesses in Australia are required to notify individuals about the collection and use of their personal data.

No responsibility / limitation of liability

Potential users of these disclaimer examples: Service providers, e-commerce platforms, content creators, educational platforms, technology companies, and any business or individual at risk of user misunderstandings.

No responsibility disclaimers can make it clear that your business isn’t responsible for specific results, damages, or risks related to its website, content, services, or products. They typically cover areas outside the business’s control, such as third-party links, user actions, or unforeseen circumstances.

Why you may need a no responsibility disclaimer statement:

1. Practical protection by reducing the risk of legal issues
2. Foster clarity and set boundaries in relationships with users and customers
3. Prevent misunderstandings while serving international audiences with varying legal requirements

What to include in a no responsibility disclaimer sample:

1. Clearly define the general scope of liability
2. Specify circumstances and areas excluded from your responsibility
3. Define areas of user responsibility
4. Specify applicable legal jurisdiction(s)
5. Provide illustrative examples and details where relevant

Music copyright

Potential users of these disclaimer examples: Professional composers, independent artists, businesses that incorporate music for branding or marketing strategies, anyone involved in creating, using, and distributing music.

A music copyright gives creators the exclusive right to control and profit from their original music. This protection supports creators in reproducing, distributing, performing, and displaying their work publicly without it being used unlawfully. Music copyrights also protect the creation of derivative works like remixes and adaptations. 

Why you may need music copyright disclaimers:

1. Generate income by reproducing works, distributing copies, publicly performing, and creating derivative works like remixes and adaptations.
2. Legally protect original music works. This protection is even stronger once supported by a music copyright notice that proactively communicates the ownership to listeners.
3. Grant creators exclusive rights over use of their work.

AI disclaimer 

Potential users of these disclaimer examples for: Anyone using AI-generated content to provide information.

An AI disclaimer notice informs that a business uses artificial intelligence to generate content, recommendations, or customer interactions. Inclusion of one can fall within the requirements of regulations, including the EU AI Act, pro-innovation UK framework, dozens of US state laws, Australia’s AI Ethics Principles, and others.

From a privacy perspective, laws like the California Invasion of Privacy Act (CIPA) also have requirements for the use of AI tools like chatbots where recorded communications are concerned.

Why you may need an AI disclaimer statement:

• Comply with fast-evolving regulations and minimize the risk of fines for nondisclosure

• Increase transparency and build consumer trust
• Promote responsible and ethical marketing practices

“Do Not Sell Or Share My Personal Information” notice

Potential users of this disclaimer example: Anyone who is obligated to follow the requirements of the CCPA and California Privacy Rights Act (CPRA).

Many websites need a “Do Not Sell Or Share My Personal Information” disclaimer while operating in California to enable users to control how their personal data is used. It limits the sale or sharing of that data with third parties, such as via the hidden tracking that happens through cookies, tracking pixels, and other tools that monitor user behavior.

According to the CCPA/CPRA, these disclaimers need to provide information on automated decision-making, including opt-out options, and limit the use of sensitive data. They also address how to delete or access this data, obtain consent for collecting information from minors, and transfer this information.

How to write an effective disclaimer

You can start with one of the ready-made disclaimer examples shared here, but you will need to customize it to your regulatory jurisdiction(s) and business operations. 

Customize the basic disclaimer templates by: 

• Consulting with a legal professional: Get qualified legal counsel as early as possible to better ensure compliance and identify the full scope of risks to cover, and check back over time as laws and operations change.
• Keeping language simple and clear: Legal or technical jargon can be difficult to understand, potentially violating requirements for clear notifications or informed consent. Simplify the disclaimer language to make it clearer for your users.
• Customizing the disclaimer’s language to your business operations: Avoid copying generic templates without tailoring them to the actual context in which they will be used. Customize the content with accurate details about responsibilities and limitations. 

Where to place disclaimers

Your disclaimers need to have maximum accessibility and visibility, so you should place them in prominent locations and where users take actions. These include:

• Your website’s footer
• A dedicated legal page
• Within the content or workflows that affect users

The table below contains more examples on where to put each legal disclaimer.

What to do after adding disclaimers: best practices

A well-crafted and prominently published disclaimer warning supports legal compliance, can protect your business, and supports building trust with your users.

Once created and published, make sure to keep them relevant long-term:

• Update disclaimers regularly: Review your disclaimer statements at regular intervals to keep up with changing laws, tech, and business operations.
• Optimize disclaimer visibility: Review how users search for and interact with the disclaimer and make improvements as needed.
• Build in privacy by design: A disclaimer is just a surface-level legal protection. Combine it with a Terms of Service agreement and a Privacy Policy. Invest in the best marketing compliance practices for fuller coverage.

Managing multiple domains doesn’t have to mean losing sight of the customer journey. In this guide we’ll show you how to track visitors seamlessly across domains while building a privacy-first analytics setup.

Learn how cross-domain tracking works to make your data more accurate, how to set up cross-domain tracking in Google Analytics 4 (GA4), and some common pitfalls to look out for. 

Key takeaways

• Cross-domain tracking in GA4 stitches user activity across multiple domains into a single session, preventing inflated user counts, broken attribution, and fragmented customer journeys.
• Google Tag Manager (GTM) is the most efficient way to configure GA4 cross-domain tracking, ensuring identifiers are passed reliably between domains for accurate reporting.
• Setup requires alignment: domains must be listed consistently in both GA4 and GTM, with allowLinker enabled, and tested through DebugView or Tag Assistant to avoid data gaps.
• Common pitfalls include missing domains, adding unnecessary subdomains, misconfigured linker parameters, and failing to integrate with consent management for privacy compliance.
• Alternatives like Segment, Adobe Analytics, and Matomo also support multi-domain tracking, but GA4 + GTM remains the most widely adopted, especially when paired with server-side tagging.
• Server-side tagging is the future, offering improved accuracy, privacy compliance, and resilience against browser restrictions: helping businesses prepare for the cookieless future with reliable, privacy-first analytics.
• What is cross-domain tracking? 

Cross-domain tracking is used by Google Analytics and other tools to recognize the same user as they move among different domains. Instead of treating each domain visit as a separate session, cross-domain tracking stitches those interactions together to create a single, accurate view of the user journey.

For example, if a user starts on your marketing site, clicks through to your product site, and then completes a purchase on your checkout site, cross-domain tracking will tie all of those interactions to one visitor. 

Without cross-domain tracking, analytics tools pick up these transitions as three new sessions. This results in broken attribution, inflated user counts, and misleading performance data.

Implementing GA4 cross-domain tracking solves the problem of multiple domains disrupting your analytics. It gives you smoother attribution, more reliable metrics, and a complete understanding of how customers are interacting with your digital ecosystem.

Why cross-domain tracking is important for user journeys 

If your customer journey spans more than one domain, cross-domain tracking is essential for gathering data you can trust.

These days, customer journeys rarely take place on a single domain. A visitor might discover your brand on a campaign microsite, browse your main website for details, and then complete their purchase on a separate checkout domain. 

While this is one continuous experience, analytics platforms without cross-domain tracking in place would interpret it as multiple unrelated sessions from different users.

This disconnect creates several problems:

• Lost attribution: Conversions appear to come from “direct traffic” instead of the real source
• Inflated numbers: The same person is counted as multiple unique users
• Fragmented journeys: It’s harder to understand how channels and touchpoints are truly influencing customer behavior

That’s why cross domain visitor identification is crucial. This tracking code means analytics tools recognize the same person across all domains, and ties together their interactions into one single, accurate user profile. 

With multi-domain tracking in place, you can:

• See the customer’s full path, from first click to conversion
• Make smarter decisions about budget allocation and campaign performance
• Build trust in your data for both marketing and business stakeholders

Essentially, you get cleaner attribution and a fuller view of how users move among your websites.

Cross-domain tracking with Google Tag Manager

One of the best ways to implement cross-domain tracking in GA4 is through Google Tag Manager (GTM). By configuring your GA4 tags correctly, GTM passes client identifiers among domains, helping to ensure that the same visitor is recognized across all sites. 

This process is often referred to as Google Tag Manager cross domain tracking or simply GTM cross-domain tracking.

When you configure GTM correctly, people moving among your websites will be tracked across one continuous user journey. Just make sure the list of domains in GA4 matches the list in GTM. Mismatches are one of the most common reasons cross-domain tracking fails.

What is cross-domain tracking in Google Analytics 4?

In GA4, cross-domain tracking works by carrying a visitor’s unique identifier from one domain to another. When someone clicks a link that directs them between your sites, GA4 adds a small piece of tracking code (_gl) to the URL. The second domain reads that and recognizes the visitor as the same person, rather than creating a new session ID.

GA4 makes this process much simpler than it was in Universal Analytics. Instead of editing code manually, you just enter the list of domains you want to connect in your GA4 settings. GA4 then takes care of passing the identifier and stitching session information together automatically.

This means you get consistent, accurate data across all of your domains, and a full view of the real customer journey from start to finish.

When do you need to use cross-domain tracking in Google Analytics 4?

Not every website setup requires cross-domain tracking. But if your business relies on multiple domains, it’s the best way to get accurate reporting in GA4.

When you need GA4 cross-domain tracking

• Your checkout is hosted separately
  • e.g. your main site is brand.com, but the payment process runs on checkout.com
• You run marketing or campaign microsites
  • visitors start on campaign.com and then move to brand.com to convert
• Your product or blog is on a different domain
  • e.g. blog.brand.com or productsite.com that links back to your primary site
• You have different product sites
  • e.g. software-brand.com and hardware-brand.com
• You use regional or language-specific domains
  • e.g. brand.co.uk and brand.de

When you don’t need GA4 cross-domain tracking

• You use subdomains
  • e.g. blog.brand.com and shop.brand.com count as the same domain in GA4 by default
• You use subdirectories
  • e.g. brand.com/blog or brand.com/shop always count as the same domain

In these cases, GA4 automatically tracks the journey as a single session, so no special setup is required.

How does cross-domain tracking work in Google Analytics 4? 

In GA4, cross-domain tracking works by transferring a visitor’s unique user identity among domains so their activity is stitched into one session ID. The key to this process is the linker parameter.

Here’s what happens in the background:

• A visitor clicks a link from one of your domains (e.g. brand.com) to another (e.g. checkout.com).
• GA4 automatically appends the _gl linker parameter to the URL. This URL parameter contains the visitor’s client ID (and, if enabled, user ID.)
• The second domain reads the parameter and applies the same client ID to that visitor.
• Google Analytics recognizes them as the same user and continues the original session ID, instead of starting a new one.
• This automatic stitching means you don’t need custom coding. As long as the correct domains are listed in your GA4 property settings, GA4 will handle the passing of identifiers in the background.

How to set up cross-domain tracking in Google Analytics 4 

Here we’ll walk you through the steps to set up cross-domain tracking in GA4. Everyone will have some variance in web properties, but the steps are clear enough to adapt to your needs.

1. Open your GA4 configuration tag in GTM

• Navigate to your GA4 configuration tag.
• Under Fields to Set, check that allowLinker is enabled. This enables GTM to append tracking parameters to URLs.

2. Enable cross-domain tracking in GA4

• In your GA4 property settings, go to Admin → Data Streams → More Tagging Settings → Configure your domains.
• Add all relevant domains you want to track, e.g. example.com, checkout.com, blog.example.com.

3. Configure the linker in GTM

• While still in your GA4 configuration tag, expand Cross Domain Tracking.
• Add the same domains you listed in GA4.
• GTM will automatically append the _gl linker parameter to URLs when users click among these domains.

4. Publish your container

• Save your changes.
• Preview to test.
• Publish your container.

5. Test your implementation

• Use GA4 DebugView or Tag Assistant to confirm that sessions persist when you navigate among domains.
• Check that no new session is created when crossing from one domain to another.

Common mistakes and how to fix them 

Cross-domain tracking can easily break down due to small oversights. Here are some common issues and how to resolve them.

Forgetting to configure all domains

Mistake: Only adding domains in GA4 or only in GTM.

Fix: Make sure the same list of domains is present in both the GA4 property settings and your GA4 configuration tag in GTM. A mismatch means sessions won’t stitch correctly.

Adding unnecessary subdomains

Mistake: Including subdomains, e.g. blog.brand.com, in the cross-domain list.

Fix: GA4 already tracks subdomains under the same property. Only add separate root domains, e.g. brand.com and checkout.com.

Ignoring consent and privacy requirements

Mistake: Deploying cross-domain tracking without integrating it with your consent management platform (CMP).

Fix: Always ensure that GA4 tags only fire once valid user consent is given where required by relevant data privacy laws.

Broken linker parameters

Mistake: The _gl parameter isn’t being added to URLs. This usually happens if allowLinker is disabled or if links are hard-coded without GTM’s tracking logic.

Fix: Double-check your GA4 configuration tag. In GTM, ensure allowLinker is enabled and the cross-domain list is correctly set.

Not testing properly

Mistake: Publishing changes without validation. Errors often go unnoticed until reports show inflated users or unexplained “direct” traffic.
Fix: Use the Google Analytics Debugger (GA4 DebugView) and Tag Assistant to test across all domains before publishing. Simulate real user journeys, like moving from blog to website to checkout, to confirm sessions persist.

Alternative tools: Segment and other solutions 

While most businesses rely on GA4 and GTM for cross-domain tracking, they’re not the only options available. Other analytics and tag management tools offer similar functionality, though the setup and flexibility can vary.

Segment cross-domain tracking

Segment, a popular customer data platform, provides its own way of stitching together user activity across domains. Instead of relying on linker parameters, Segment uses a centralized tracking script that captures events and user IDs. 

These are then passed into downstream tools, like Google Analytics 4 , Mixpanel, or CRM systems. This makes it easy to manage cross-domain visitor identification across your entire analytics and marketing stack.

Other multi-domain tracking tools

Adobe Analytics: Uses its Experience Cloud ID Service to unify visitors across domains

Matomo: Supports cross-domain tracking through URL parameters and configuration settings

Other CDPs: Platforms like RudderStack and Tealium provide similar capabilities to Segment

Why Google Analytics 4 and Google Tag Manager are popular

Even with alternatives available, Google Analytics 4 with Google Tag Manager remains the most common setup. It’s free, widely supported, and integrates directly with Google Ads and other Google products. 

The main limitation is complexity. As your tracking needs grow, GTM setups can become difficult to maintain, especially across multiple domains and compliance requirements.

That’s why many teams look to server-side tagging (SST) as a way to simplify management, improve data accuracy, and stay privacy-first.

Server-side tagging: the future of cross-domain tracking

Cross-domain tracking with GA4 and GTM works really well, but it comes with some challenges. For example the setup can be complex, ongoing maintenance is often overlooked, and data privacy regulations add extra layers of risk. 

As regulations tighten and browser restrictions expand, client-side cross-domain tracking will only get harder to maintain. Server-side tagging offers a way to simplify setups, provide data integrity, and stay privacy-compliant while keeping a high level of confidence in the analytics your teams rely on.

How server-side tagging works

Instead of sending data directly from the browser to every analytics or ad platform, SST routes requests through a secure server you control:

• Data is collected and processed centrally
• You control how information is processed, e.g. enriched or anonymized, and what information is forwarded, and to which platforms
• Consent choices are applied before any data leaves your environment

Benefits for cross-domain tracking

The value of server-side tagging extends well beyond simpler cross-domain setups. There are five major benefits that make the shift especially useful for marketers.

• Improved data accuracy with fewer gaps caused by ad blockers or browser restrictions
• Faster site performance, since tracking scripts move off the browser and onto your server
• Streamlined privacy compliance, thanks to centralized control over what data is collected and shared
• Simpler management: one central setup instead of juggling multiple GTM containers

Future-proof: More resilient to browser restrictions, ad blockers, and third-party cookie deprecation than Google Analytics and other off-prem tools.

Preparing for the cookieless future

Cross-domain tracking is only part of the bigger shift shaping digital measurement. As browsers phase out third-party cookies and privacy regulations tighten, marketers need strategies that preserve measurement accuracy while keeping data privacy-first.

Tools like server-side tagging help bridge the gap, but they work best as part of a broader strategy. Google is already rolling out several cookieless solutions and privacy tools, including Consent Mode, Enhanced Conversions, and the Privacy Sandbox. These tools are designed to maintain reliable insights even as traditional tracking methods disappear.

For a broader perspective on what the cookieless future means for your business, and the solutions available to prepare for it, don’t miss our guide on how to prepare your marketing strategies for a cookieless future. This practical resource can help you to adapt before these changes hit your reporting.

Looking ahead: the future of data in marketing

Cross-domain tracking and server-side tagging are essential steps toward building a resilient, privacy-first analytics setup, but they’re just part of a much bigger shift.

As data privacy regulations tighten, tracking technology continues to advance, and consumer expectations around privacy increase, it’s important that marketers adapt with smarter data strategies that balance compliance, measurement, and growth.

For more information about these predicted changes, our guide The Future of Data in Marketing offers a deeper dive into how first-party data, innovative tools like Google Topics and Protected Audience APIs, and privacy-led frameworks are reshaping the way marketers connect with audiences without compromising trust.

Google Tag Manager (GTM) simplifies how you deploy and manage tracking codes. But working with GTM gets even easier when you also have the right extensions and tools.

If you’re a frequent user of Google Tag Manager, you’re likely always looking for ways to improve your performance, catch bugs faster, and simplify your process. We’ve collected a variety of tools to help you do just that.

Key takeaways

• Why Google Tag Manager (GTM) tools are essential for scalability, accuracy, and privacy compliance
• Organizational Chrome extensions: GTM Sonar, Variable Inspector, GTM Copy Paste
• Debugging and QA tools: Google Tag Assistant, Data Layer Inspector+, Ecommerce Validator
• Documentation and collaboration solutions: GTM Tools by Simo Ahava, Scribe, GTMFixer
• Privacy and compliance integrations: Consent Management Platforms (CMPs), Google Consent Mode
• Server-side tagging advancements: Usercentrics server-side solution, server container managers, performance dashboards
• Best practices: consistent testing routines, audits, layered debugging, and process standardization

Google Tag Manager extensions for setup and organization

A well-organized GTM container is like a clean codebase — it saves you time, prevents mistakes, and better enables collaboration. However, as your GTM implementation expands, maintaining that structure can be a real challenge, especially when an increasing number of teams or team members are involved.

The following extensions help you maintain structure as your GTM implementation evolves. They’re particularly valuable when multiple people work on the same container or when you need to scale your setup across multiple properties.

GTM Sonar Chrome extension

This Google Tag Manager Chrome extension provides a quick visual overview of all tags, triggers, and variables active on any page. The interface displays firing status for each element, shows blocked tags, and identifies potential conflicts between or among different tracking implementations. 

It works by scanning the GTM data layer and displaying results in a compact sidebar that doesn’t interfere with normal browsing. This makes it a useful GTM tool for getting to the point and understanding your tag ecosystem quickly. It’s free to use and can be downloaded via the Chrome Web Store.

Variable Inspector for GTM

On dynamic websites, data layer variables can be hard to keep track of. This tag manager extension monitors your data layer variables in real-time, showing current values and tracking changes as they occur. 

It offers a straightforward way to troubleshoot issues with dynamic content or personalization rules, simplifying what can otherwise feel like a complex process. Keeping the focus clear and avoiding unnecessary jargon makes data layer management more accessible, and it’s free to use.

GTM Copy Paste

Scaling GTM setups across multiple containers has traditionally meant a lot of manual work. This tool enables the copying and pasting of complete configurations, including all relationships among tags, triggers, and variables. It exports complete tag setups, including dependencies, then allows selective import of specific elements or entire configurations.

This GTM extension simplifies a process that could otherwise be a nightmare and helps you maintain consistency across multiple properties. The tool itself is free, but as with any third-party solution, it’s a good practice to be aware of how GTM updates might affect its performance.

Google Tag debugger and quality assurance tools

Even with perfect organization, tags can break. They often break silently, and in ways that won’t show up in your reports until weeks later, when you notice missing data. The key to maintaining reliable tracking is catching problems before they compound.

Quality assurance tools work best when used proactively rather than reactively. Instead of troubleshooting after discovering broken tracking, these tools help you validate implementations during development and catch edge cases before they reach production.

Google Tag Assistant

The Google Tag Assistant Chrome extension is Google’s official extension, and it’s a go-to for checking your Google tags, like those for Analytics and Tag Manager.

It helps ensure everything is installed correctly and that essential data is present. It’s also useful for flagging common issues, like duplicate tags. Furthermore, it works on any website, is free to use, and doesn’t require access to your GTM container.

The session recording feature, which used to be in a separate Tag Assistant Companion extension, is now part of this main tool. This enables you to record complete user journeys — from page transitions to form submissions — to easily check tag firing sequences.

Data Layer Inspector+

This Google Tag Manager tool gives you a detailed, real-time look at your website’s data layer. It displays the current state of the data and tracks pushes and updates as they happen. 

It’s ideal for seeing the complete object hierarchy and making sense of the information being sent to your tags. Many companies find that it makes debugging complex data structures more manageable. Data Layer Inspector+ is also free to use.

E-commerce Validator

When it comes to e-commerce, ensuring your data is structured correctly is critical. While there isn’t one official Google tool for this, an e-commerce validator — which can be a dedicated tool or a function within a broader debugger — checks your enhanced e-commerce implementation against Google Analytics requirements. 

It helps you verify that all the required fields are present — like item_id, item_name, and price — which is essential for accurate conversion and revenue reporting.

Documentation and collaboration GTM tools

GTM projects can quickly become complex, especially when multiple teams are involved. One person implements a workaround, someone else modifies it without context, and six months later, nobody remembers why certain triggers exist or what they’re supposed to do.

The solution isn’t just better communication; it’s systematic documentation and change management. The following Google Tag Manager tools create accountability and knowledge sharing that scales with your team and prevents knowledge problems.

GTM Tools by Simo Ahava

This documentation generator analyzes your GTM container and creates detailed reports covering tags, triggers, and variables. It also provides a visualization of how these elements are connected, making it easier to understand the container structure. 

This GTM tool includes auditing features that help identify unused elements and areas for cleanup, supporting both documentation and optimization. It’s also free to use.

Scribe

Scribe is a tool that documents complete processes by recording user actions and automatically generating step-by-step guides with annotated screenshots. 

It’s useful for creating SOPs, onboarding materials, and training documentation for GTM workflows. The output can be shared with team members to standardize complex processes.

The company offers a free plan, and pricing plans start at USD 12/month.

GTMFixer

This GTM Chrome extension elevates the GTM interface with additional functionality. It adds search and filtering options, highlights tag errors, and introduces workflow improvements that simplify collaboration. 

These additions help teams navigate large containers more efficiently and reduce time spent troubleshooting. This extension is free and can be downloaded from the Chrome Web Store.

GTM Copy Paste

This tool enables importing and exporting of entire GTM configurations, including dependencies between elements. It simplifies the process of replicating setups across containers, saving time when scaling or migrating environments. 

By automating what is typically a manual process it helps reduce errors and enable consistency across projects. This GTM extension is free and can be downloaded from the Chrome Web Store.

Privacy and compliance tools for Google Tag Manager

Privacy regulations have fundamentally changed how tag management works. You can’t just deploy tracking codes and assume compliance. You need consent management and ongoing monitoring to meet legal requirements.

The challenge isn’t just technical compliance, but balancing legal requirements with business needs. These tools help you implement privacy controls that can help with compliance without undermining your ability to understand user behavior and optimize experiences.

Consent Management Platform

Consent Management Platforms (CMPs) are the user-facing part of the privacy solution, providing the cookie banner and managing the entire consent collection process. Many popular CMPs, like Usercentrics CMPs and Cookiebot CMP, are Gold Tier Google CMPs partners and offer pre-built templates available in the GTM Community Template Gallery.

The CMP connects to GTM by deploying a special tag that sets the default consent status for all other tags on the page. When a user makes a choice, our CMP updates the consent status, which then triggers a GTM event that tells your tags what to do. This allows you to centralize your consent logic and ensure that tags for analytics, advertising, and other purposes only fire when you have a user’s explicit permission.

Google Consent Mode

Google Consent Mode is a framework that helps to communicate a user’s cookie consent status to Google’s tags. It’s integrated with the CMP and with GTM.

Consent Mode enables Google tags to automatically adjust their behavior based on consent signals received by the CMP. For example, when a user denies consent, you can configure tags to send anonymous, cookieless pings to support conversion modeling without storing personal data. 

It’s a critical component for maintaining some data collection while respecting user privacy.

Server-side tagging tools

Server-side GTM represents a significant shift in how tracking works. Instead of loading tags directly in users’ browsers, you process tracking data on your own servers before sending it to analytics platforms. This approach offers better performance, increased privacy control, and more reliable data collection.

The transition to server-side tracking requires new infrastructure and different debugging approaches. These tools help bridge the gap between familiar client-side workflows and the more complex server-side environment.

Usercentrics server-side tagging solution

Usercentrics’ server-side integration helps ensure that consent signals from the browser are consistently passed to the server container and maintained throughout the entire data processing chain. 

It synchronizes consent states across multiple endpoints, provides APIs for custom implementations, and includes monitoring to track reliability. With built-in failsafes, it helps to ensure that only privacy-compliant, consented data reaches final tracking destinations.

There is a free option, and paid tiers start from EUR 16/month.

Server container manager

This type of Google Tag Manager tool automates server-side GTM container deployment on cloud platforms like Google Cloud Platform and AWS. It does so by handling server provisioning, container deployment, SSL certificate management, and load balancing configuration. 

Such tools often include monitoring dashboards that track server performance, request volume, error rates, and costs. They often also support multiple deployment environments (staging, production) and include rollback capabilities for failed deployments.

Performance monitoring dashboard

These types of Google Tag Manager solutions track key performance metrics specific to server-side GTM implementations, including request processing time, server response times, data transformation latency, and endpoint availability. 

They provide alerts for performance degradation, track resource utilization across server instances, and include cost monitoring for cloud-based implementations. The dashboard display can often correlate performance issues with specific tags or client events to help identify optimization opportunities.

Best practices when using Google Tag Manager tools and extensions

Having great tools doesn’t automatically prevent or solve problems. You need to use them systematically to get real value from your Google Tag Manager extensions. Without process, even the best debugging tools can lead to inconsistent results and missed issues.

Set up a consistent testing routine

Use debugging extensions during development, not just when things break. Create a simple checklist: validate tags, inspect the data layer, and check privacy compliance. Run through it every time you make changes, so testing becomes part of the workflow, not an afterthought.

Keep your team aligned on tools

Document which Google Tag Manager extensions your team uses and why. New team members need to know which tools to install and how you use them. This prevents the chaos of everyone relying on different debugging methods and helps to ensure consistent results across the team.

Schedule regular GTM audits

Set monthly reminders to review your setup with your tag manager assistant tools. Look for unused tags, confirm that privacy compliance is maintained, and spot configuration drift before it grows into a larger problem.

Layer your debugging approach

Don’t rely on a single extension for complex issues. Use multiple tools together — combine Tag Assistant validation with data layer inspection and performance monitoring for a more complete analysis.

Turn tools into process

The value of GTM tools comes when they’re baked into your team’s routines. With consistent testing, shared practices, and layered debugging, these tools move from being quick fixes to being part of a reliable system that scales with your projects.

Get more from your GTM setup with the right tools

Google Tag Manager tools can help solve a variety of challenges you may be facing. Whether you’re debugging a broken implementation, keeping your team organized, or staying compliant with privacy laws, the right extensions make it more manageable.

The key is choosing GTM tools that address your specific challenges. Don’t install every available Google Tag Manager extension. Pick the ones that solve problems you face regularly and use them consistently.

You’re running ads on Google, posting on social media, sending email campaigns, and maybe even doing some billboard advertising. Your customers interact with your brand across multiple touchpoints before making a purchase. However, most businesses only see the last click before conversion.

Multi-channel tracking and multi-channel attribution address this blind spot. They reveal the complete customer journey and show how each marketing channel contributes to conversions. Instead of guessing which efforts work, you gain data-driven insights to make smarter budget decisions.

Key takeaways

• Multi-channel tracking shows the full customer journey, not just the last click.
• Multi-channel attribution assigns credit to each touchpoint, helping identify which channels drive conversions.
• Learn how other brands are using multi-channel tracking.
• Tools like Google Tag Manager (GTM) and Google Analytics 4 (GA4) make cross-channel tracking and attribution scalable.
• Server-side tagging fills data gaps caused by blockers, privacy limits, or cross-device journeys.
• Metrics such as conversion paths and ROI help evaluate multi-channel tracking effectiveness.

What is multi-channel tracking?

Multi-channel tracking monitors how customers interact with your brand across platforms and touchpoints. Think of it as following the breadcrumbs customers leave as they move from one channel to another on their way to purchase.

For example, someone discovers your brand through a Facebook ad, visits your website directly a few days later, and finally makes a purchase after clicking your email newsletter. Multi-channel tracking records all of these interactions, building a timeline of engagement.

Your website analytics, social media insights, email marketing metrics, and advertising platforms all collect pieces of this puzzle. Multi-channel tracking brings these pieces together to show you the full story.

Multi-channel tracking vs. multi-touch attribution

Although multi-channel tracking provides a clear picture of all customer interactions, it doesn’t tell you which touchpoints actually drive conversions. That’s the role of multi-touch attribution. 

While multi-channel tracking focuses on data collection from different sources and channels, attribution analyzes that data and assigns value to each touchpoint.

Tracking is the foundation. Attribution models then assign value to each interaction:

• First-touch attribution credits the initial interaction
• Last-touch attribution credits the final interaction before conversion
• Linear attribution distributes credit evenly across all touchpoints
• Data-driven attribution uses machine learning to assign credit based on actual impact

What are the benefits of using multi-channel tracking and attribution?

Multi-channel tracking enables your company to eliminate guesswork and optimize your marketing strategies. Here are the specific benefits of using multi-channel attribution in your analytics.

Better decision-making

Attribution provides a complete view of campaign performance. You can prioritize what works rather than relying on last-click assumptions. You’ll see which campaigns are moving the needle and which are only riding the momentum of other efforts.

Clearer channel contributions 

Every marketing activity has a role, even if it doesn’t produce immediate sales. Social content may not close deals directly, but it can boost search conversions or increase email engagement. Understanding these interactions helps you create campaigns that work together, not in isolation.

Smarter budget allocation

Insights from attribution models guide budget distribution. Instead of cutting channels that seem underperforming, you can invest in combinations of channels and tactics that move customers through the funnel.

More accurate ROI

With all touchpoints accounted for, ROI reflects the true value of campaigns. This strengthens internal reporting, justifies spend, and supports scaling effective initiatives that drive results.

Deeper customer insights

Attribution reveals not just where conversions happen, but how customers interact along the way. These insights enable more refined messaging, tailored offers to different segments, and craft more resonant experiences throughout the journey.

Examples of multi-channel tracking

Tracking the customer journey sounds simple in theory: follow the path from first touch to conversion. In reality, people move across devices, platforms, and channels in ways that make the picture messy. And depending on the industry, those paths can look very different.

Software companies: The journey can stretch over weeks. A prospect discovers a project management tool through a LinkedIn ad, downloads a free template, signs up for a newsletter, attends a webinar promoted on Facebook, and reads blog posts found on Google. But only after a retargeting ad on an industry site do they start a free trial. One decision, seven interactions, two months.

Healthcare: The complexity isn’t just time, but people. A hospital administrator first hears about a solution at a conference, then repeatedly returns to the website to download whitepapers and join demos. Colleagues get pulled into the evaluation before requesting a proposal. Tracking has to connect all of those actions across multiple stakeholders and devices.

Travel: This industry adds another layer of shared decisions. A family planning a vacation might see Instagram ads for destinations, compare hotels and prices via Google search and booking sites, and check reviews on TripAdvisor. They finally book after receiving a promotional email from a hotel. Several people, several devices, all influencing one outcome.

These examples show why understanding the complete customer journey matters more than focusing on single-channel performance.

The challenges of tracking across multiple channels

It’s worth noting that implementing multi-channel tracking isn’t as simple as flipping a switch. Each platform creates another layer of complexity, and recent changes in privacy and technology can make things even trickier.

Data silos complicate reporting

A major challenge with multi-channel tracking is the presence of data silos. Facebook Ads Manager, Google Analytics, and your email platform each operate in their own “language.” Integrating their data can feel like trying to reconcile multiple, conflicting systems.

Privacy changes limit tracking capabilities

Then there’s the privacy revolution. iOS now blocks tracking by default, Chrome is making third-party cookies optional, and the EU’s General Data Protection Regulation (GDPR) requires you to ask permission before collecting any data. In addition, ad blockers have become mainstream, and customers are increasingly protective of their personal information.

Technical limitations create gaps

Cross-device tracking poses another hurdle for marketers. Your customer sees your ad on their phone during lunch, researches on their work laptop, and buys on their tablet at home. It can be a challenge to connect these dots, leaving gaps in your attribution data.

Different platforms also use varying attribution windows. Some credit conversions happen 30 days after an ad click; others only give you seven days. When you’re trying to get a unified view across platforms, these inconsistencies can complicate reporting.

Building the foundation for multi-channel attribution and tracking

To get cross-channel attribution right, you need a solid technical setup. That means tools that collect data consistently across platforms, help you understand customer journeys, and respect the privacy requirements that come with tracking users across multiple touchpoints.

Google Tag Manager as the backbone of tracking

Google Tag Manager (GTM) centralizes tracking across platforms, linking your website to different tools without requiring constant developer support.

Instead of juggling separate tracking codes for Facebook, Google Ads, email platforms, and analytics, GTM centralizes everything in one place. Updates or new integrations happen in its interface, not in your website’s code.

This solves common attribution problems. Data stays consistent across platforms, reducing discrepancies among reports. GTM also handles technical hurdles like cross-domain tracking, ensuring a customer moving from your blog to checkout is still recognized as the same journey.

GTM also enables you to track more than page views or purchases. Events like video plays, downloads, form submissions, or scroll depth enrich your data and give you a fuller view of the customer journey.

Making sense of the data using Google Analytics 4

GTM handles collection, while Google Analytics 4 (GA4) interprets it. GA4 tracks users across platforms and supports multiple attribution models, including data-driven attribution.

GA4 also comes with multiple multi-channel attribution models — from first-click to data-driven. The data-driven model is especially powerful, using machine learning to identify which touchpoints actually drive conversions based on your real customer behavior.

Key GA4 features for attribution include:

• Conversion paths report: reveals the sequence of touchpoints leading to conversions
• Model comparison tool: shows how results shift depending on the attribution model you choose

To maximize multi-channel attribution using Google Analytics, track meaningful events throughout the journey, not just final conversions. Use enhanced conversions with hashed first-party data for better accuracy, and integrate with Google Ads for smarter bidding strategies.

The role of server-side tagging in multi-channel tracking

Browser-based tracking often falls short: ad blockers, connectivity issues, and privacy restrictions can prevent data from being captured. This leaves gaps in your multi-channel attribution models. 

But without those touchpoints, you risk underestimating the impact of early-stage campaigns or misallocating budget.

Part of the problem comes from the way data is typically collected. Sending information directly from your website to platforms like Google or Facebook relies on browser-based scripts running perfectly in the user’s session. 

If a script is blocked, a page loads slowly, or a user navigates away too quickly, those interactions are lost. You also give external platforms control over your data, which can complicate privacy compliance and limit your flexibility in handling consent.

Server-side tagging can help solve these problems. Instead of your website sending data directly to platforms like Google or Facebook, the data flows through your server first. Your server decides what to send and where, giving you full control over which interactions are tracked and how.

This approach tackles three critical challenges:

• Ad blockers and script limitations: Tracking doesn’t rely on browser-based scripts, so data gets captured even when users block ads or tracking scripts.
• Fewer data gaps: Server-side processing ensures that interactions are recorded even if users leave quickly or experience slow connections.
• Privacy compliance: Handle data according to each user’s consent choices before sending it to external platforms, automatically respecting opt-outs.

By ensuring more complete, accurate, and privacy-compliant data, server-side tagging strengthens multi-channel tracking. With fewer blind spots, marketers can see the real contribution of each touchpoint, make better budget decisions, and optimize campaigns based on the full customer journey.

How to evaluate the success of a multi-channel marketing model

Multi-channel attribution isn’t about perfect tracking, it’s about understanding enough to make better marketing decisions.

Here’s how to evaluate your multi-channel attribution model:

• Establish baseline metrics before implementation: Document customer acquisition costs by channel, overall marketing ROI, conversion rates, and campaign performance for comparison.
• Monitor behavioral changes in your marketing strategy: Track how budget allocation shifts based on attribution insights. If social media boosts email performance rather than driving direct conversions, are you adjusting spend accordingly?
• Identify patterns in customer journeys: Customers starting with organic search might convert faster, while social media leads take longer but spend more, informing campaign timing and budget distribution.
• Track cross-channel engagement impact: Customers who interact with multiple channels often have higher lifetime value, so create campaigns designed to encourage multi-touchpoint engagement.
• Audit data quality regularly: Major discrepancies between platforms or large gaps in customer journey data signal problems that undermine attribution reliability.
• Measure efficiency gains in overall marketing ROI: The ultimate test is achieving better ROI with multi-channel attribution, even if individual channel metrics look different.

Use multi-channel attribution to boost your ROI

Your customers already move across multiple channels before they convert. Multi-channel tracking reveals these journeys so you can act strategically. 

Start with GTM to centralize tracking, then use GA4 attribution models to evaluate impact. Server-side tagging fills in the gaps.

The goal isn’t perfect tracking — it’s better decisions.  Focus on the insights that change how you allocate budget, design, campaigns, and create customer experiences. When you can see the complete journey, you can optimize for what actually drives results rather than what gets the last click.

Collecting reliable data from a website isn’t always straightforward. Different platforms often track the same interactions in different ways. This can lead to gaps, mismatched numbers, and incomplete insights.

The Google Tag Manager (GTM) data layer provides a structured foundation to solve these challenges. It helps ensure consistent capture of events like purchases, form submissions, and content engagement, and that they’re made available to all your tags.

Beyond consistent tracking, the data layer also makes managing analytics easier. Adding new tools, adjusting existing tracking, or changing how events are measured can be done without touching your site’s core code, keeping development simpler and your website focused on user experience.

The Google Tag Manager data layer is a structured system that organizes tracking information on your site. Instead of each marketing tool pulling data in its own way, the data layer creates a standardized format that all platforms can use.

Without it, tools like Google Analytics, Facebook pixels, and email platforms often collect information from different places, interpret it differently, and produce inconsistent reports.

With a data layer, website events, such as purchases, form submissions, and content engagement metrics, are captured once and shared consistently across all platforms. This means that analytics, ad pixels, and automation tools all work from the same source of truth.

This setup also separates data collection from your site’s design and functionality. You can adjust tracking or add new tools without touching core code. This keeps your website focused on user experience while the data layer manages information flow.

How the data layer differs from direct tag implementation

Traditional tag implementation requires embedding tracking codes directly into your website’s HTML. This approach creates several problems:

• Tags load inconsistently across pages
• Data collection depends on page elements that might change
• Multiple tags can conflict with each other
• Updates require developer involvement

The GTM data layer eliminates these issues by standardizing how data flows from your website to your tags. Instead of each tag grabbing information differently, they all reference the same structured data source.

Examples of GTM data layer

The Google Tag Manager data layer is most powerful when it tracks meaningful business events, not just page views. In practice, this often means capturing purchases, lead submissions, and engagement with content.

E-commerce purchase tracking

When a customer completes a purchase, the data layer records details like order ID, total value, individual products, and customer information. Google Analytics uses this for conversion tracking, Facebook applies it to build lookalike audiences, and your email platform uses it to trigger personalized campaigns.

Because every platform receives the same purchase data, your attribution models stay consistent and help prevent mismatched numbers in the tools you’re using.

Lead generation and form submissions

For B2B websites, the data layer can capture form completions and qualification events. For instance, when someone downloads a whitepaper or requests a demo, it logs details like form type, content topic, user segment, and lead score.

That context flows into your Customer Relationship Management (CRM) system, powers ad platforms to optimize for quality leads, and triggers tailored follow-ups in your email tools. Each system is aligned on the same lead information.

Content engagement measurement

Publishers and content-heavy sites use the data layer to measure how audiences interact with articles, videos, and resources. It can capture article titles, categories, scroll depth, time spent reading, and even social shares.

This richer engagement data gives content teams a clearer view of what resonates with readers, while also helping advertising platforms build audiences based on consumption patterns.

How does the GTM data layer work?

The GTM data layer acts as a bridge, collecting information from your site and making it accessible for GTM to use in tags and triggers. The process is best understood in two stages.

Stage 1: Pushing data from your website

Your website’s code explicitly pushes data to a JavaScript array called the data layer whenever a significant event occurs. This happens on page loads, form submissions, button clicks, or when a user completes a purchase.

Each push adds an object to the data layer with key-value pairs that describe the event. One of the most critical keys is ‘event’, which GTM uses to fire triggers. The timing of this data push is crucial — the information must be present in the data layer before a GTM tag attempts to read it.

Stage 2: The GTM reaction and data access

GTM constantly listens for new data pushes to the data layer. When an event is pushed, the GTM event listener is activated. It doesn’t permanently store the data; instead, it reads from the data layer and immediately uses the information to evaluate triggers.

GTM tags access the data layer’s information through GTM variables that you define in the GTM interface. These variables read specific key-value pairs from the data layer and make that data available to tags.

This process ensures that a tag only fires when a specific event occurs and has access to the correct data, helping you manage data collection consistently and efficiently.

Why does the data layer matter for accurate tracking?

Accurate marketing data doesn’t just happen. It depends on how information is collected and shared across your tools. That’s where the tag manager data layer comes in. It feeds every platform the same structured information. 

Once that foundation is in place, the advantages become clear.

Consistent data across all platforms

When a customer makes a purchase, your Google Analytics might capture the transaction but miss the product category. Meanwhile, your Facebook pixel records the product details but loses the customer type information. These gaps create incomplete user journeys and unreliable attribution reports.

The Google data layer solves this by creating one structured information source. When a purchase happens, the data layer captures the transaction ID, product details, customer information, and timing data. Every tracking tool pulls from this same source, giving you consistent numbers across all platforms.

Better decision-making with complete information

Incomplete tracking leads to poor marketing decisions. You might think a campaign isn’t working, when it’s actually your tracking that’s broken. Or you could be overspending on channels that seem effective but aren’t properly attributed.

The data layer provides the complete picture. You see the full customer journey from first click to final purchase, with all the context needed to optimize your marketing spend and strategy.

Simplified tag management

Without a data layer, adding new tracking tools means custom development work. Each new platform needs its own implementation, creating complexity and potential conflicts between different tracking codes.

The GTM data layer changes this. Once your data layer is set up, adding new tracking tools becomes a configuration task in Google Tag Manager rather than a development project. You can test new platforms, adjust tracking parameters, and optimize data collection without touching your website’s code.

A step-by-step guide to create a data layer in GTM

While the advantages are clear, realizing them depends on proper implementation. Setting up a data layer requires coordination between developers and marketing teams, combining technical setup with strategic planning to ensure it captures the information that supports your business goals.

Part 1: Plan your data structure

Start by identifying the key events and information that drive your marketing decisions. Common data points include:

User identification

• Customer ID (for logged-in users)
• User type or segment
• Account status
• Geographic location

Content and product information

• Page type and category
• Product IDs and names
• Content topics and authors
• Inventory status

Interaction events

• Button clicks and form submissions
• Video plays and downloads
• Search queries and filter usage
• Cart additions and removals

Document these requirements before beginning the technical implementation process. This planning prevents the need to restructure your data layer after tags are already configured.

Part 2: Technical implementation steps

Setting up the data layer involves a few key steps. Each one builds on the last, moving from basic initialization to capturing more complex interactions.

Step 1: Initialize the data layer

Start by adding the data layer initialization code to your website’s header, before the GTM container snippet:

<script>
dataLayer = [];
</script>
<!-- Google Tag Manager -->
<script>(function(w,d,s,l,i){...})(window,document,'script','dataLayer','GTM-XXXXXX');</script>

Step 2: Push static page data

Next, include page-specific details right after initialization. This ensures that every page load provides structured context for your tags.

<script>
dataLayer.push({
  'pageType': 'product',
  'pageCategory': 'electronics',
  'userType': 'returning_customer'
});
</script>

Step 3: Add event-based pushes

Finally, capture dynamic user interactions — such as clicks, form submissions, or video views — by pushing event data into the layer when they occur.

function trackFormSubmission() {
  dataLayer.push({
    'event': 'form_submit',
    'formName': 'newsletter_signup',
    'formLocation': 'sidebar'
  });
}

Development considerations

Beyond the setup, there are a few technical details your developers should keep in mind:

• Load order dependencies: Data must be available before tags try to use it. Coordinate data pushes with tag firing rules to avoid gaps.
  
• Data formatting consistency: Use clear naming conventions and standardized data types across the site. Inconsistent formats can create tracking errors.
  
• Performance impact: Data layer operations are lightweight, but excessive pushes can slow down busy pages. Monitor performance and streamline where necessary.

How GTM uses the information from the data layer

Google Tag Manager transforms data layer information into actionable tracking through its variable and trigger system. This process determines when tags fire and what information they receive.

Variables: Accessing data layer information

GTM variables extract specific pieces of information from the data layer. When you create a data layer variable in GTM, you specify which data layer key you want to access.

For example, if your data layer contains the following code:

{
  'event': 'purchase',
  'transactionID': 'TX123',
  'transactionValue': 99.99
}

You would create GTM variables to access transactionID and transactionValue. These variables become available for use in tags and triggers throughout your GTM setup.

Triggers: Determining when tags fire

Data layer events serve as triggers that determine when specific tags should fire. The event parameter in your data layer pushes creates trigger opportunities in GTM.

Custom event triggers in GTM listen for specific event names. When your website pushes an event to the data layer, GTM checks if any triggers are configured to respond to that event name.

Tag configuration and data mapping

Tags use the variables and triggers to determine their behavior. A Google Analytics tag might:

• Fire when the purchase event occurs (trigger)
• Send the transaction ID as a custom dimension (variable)
• Include the transaction value in the event value (variable)

This configuration process happens entirely within GTM, without requiring changes to your website’s code. You modify tracking behavior by adjusting GTM settings rather than updating your data layer implementation.

Troubleshooting GTM data layer issues

Data layer problems typically fall into a few categories: timing issues, data format problems, configuration mismatches, or event trigger failures. Recognizing these patterns makes diagnosing and fixing tracking issues much faster.

Timing and load order issues

One of the most common challenges is that tags fire before the data layer has the information they need. In GTM Preview mode, this often appears as variables showing “undefined,” or in reports where transaction details are missing. Tags may also trigger on page load, while the data arrives a moment later.

To fix this, make sure data pushes happen before tags are called. Adjust JavaScript execution order if necessary, or set triggers to wait for specific data layer events instead of relying on page load. The built-in GTM variables or custom JavaScript variables can also help bridge gaps in timing.

Data format inconsistencies

Another frequent issue is inconsistent data formatting across pages. Variables may work on some pages but fail on others, numbers might appear as strings, or arrays could collapse into single values.

The solution is to enforce a standardized structure across your site. Document conventions for naming and data types, and build validation into your push functions to catch errors before they reach GTM.

Variable configuration errors

Sometimes the data layer is set up correctly, but GTM can’t extract the right values. This usually comes down to misconfigured variables, such as case-sensitive name mismatches, the wrong data layer version, or missing scope settings.

Preview mode is your best tool here. Check the data layer tab to verify what’s being pushed, then compare those key names to your GTM setup. Pay close attention to nested objects, which require dot notation.

Event firing problems

Finally, event triggers may not fire even when the data layer is pushing them. This can happen if event names don’t match exactly, if trigger conditions filter them out, or if required variables aren’t available at the right moment.

To troubleshoot, simplify your trigger setup during testing so you can isolate the issue. Use the real-time GTM debugging tools to see which events are being pushed and how your triggers are responding.

How server-side tagging improves your Google Tag Manager data collection

The data layer is the backbone of any clean tagging setup. It ensures that user interactions are collected in a structured way, so analytics and marketing platforms all operate from the same source of truth. 

But sending events directly from the browser to third-party vendors has limitations: ad blockers, browser restrictions, and global privacy regulations can all interfere with data accuracy and compliance.

Server-side tagging addresses these challenges by routing events through a GTM server container you control. This introduces a checkpoint where you decide what data to keep, what to anonymize, and how to enrich it before it leaves your environment. 

Regulations like the EU’s General Data Protection Regulation (GDPR) and the California Privacy Rights Act (CPRA) make this level of control increasingly important.

How server-side tagging works with the data layer

When a visitor triggers an event, it enters the browser’s data layer as usual. The web container then forwards this event to the server container, where it can be processed and mapped to multiple platforms. 

Key context, like user identifiers, session information, and e-commerce details, remains intact, while your team retains the ability to apply privacy or consent logic centrally.

The advantage of this flow is subtle but significant. By introducing a server-side layer, you gain more control over how data is shared externally. Events are no longer fully exposed to the client environment, reducing the impact of ad blockers and browser-level restrictions while maintaining consistent, reliable measurement.

Setting up server-side tagging

Implementing server-side tagging involves several steps, but the process is straightforward for teams familiar with GTM:

• Create a server container in GTM and deploy it to a cloud platform, such as Google Cloud App Engine.
• Update your web container to route data to the server container endpoint instead of sending it directly to third-party platforms.
• Configure server-side tags to forward processed events to analytics and marketing platforms, applying any necessary filters or transformations.

Test the setup using GTM preview mode or browser developer tools to ensure events arrive correctly and carry the intended context.

Use server-side tracking to strengthen measurement and privacy

Server-side tagging paired with Google Tag Manager data layers offers multiple benefits. 

• By processing requests on your own server, data collection becomes more resilient to ad blockers and browser-level interference, improving reliability and data accuracy. 
• Fewer scripts run in the user’s browser, which increases your page speed performance and the user experience. This is also better for your SEO efforts as Google takes into account page speed.
• Centralizing privacy logic on your servers helps to simplify compliance with global regulations while preserving the quality and richness of the data you collect.

For organizations operating internationally, server-side tagging enables regional rules to be implemented in a single place rather than duplicated across multiple client-side containers. 

It’s not a replacement for the data layer, but rather an extension. The data layer continues to capture and structure events on the client side, feeding a controlled process that your team fully governs.

Global privacy regulations are becoming stricter every year, and keeping up can be exhausting for marketers. What was considered safe last year may not be compliant today, and falling behind risks customer trust and costly fines.

Delegating some of these concerns to privacy-preserving technologies can help. While many tools support global compliance requirements, privacy-enhancing technologies (PETs) stand out. They enable responsible data processing that places user trust at the center of compliance.

In this guide, you’ll learn what privacy-enhancing technologies are, how they work, and how to determine their value for your business in 2025.

Data privacy-enhancing technologies are becoming critical tools in organizations’ comprehensive data security systems. They help companies keep pace with the compliance requirements of fast-changing regulations and rising consumer expectations.

In 2025, PETs play a central role in building consistent, comprehensive data protection systems. They apply principles such as data minimization, which is increasingly critical as marketing compliance requirements grow stricter.

Regulations like the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), the Digital Markets Act (DMA), and the EU AI Act now apply across different jurisdictions and address different areas of business and technology. Each has unique requirements.

For marketers, complying with all relevant laws, frameworks, and policies can be daunting. When businesses fall behind, they face increased risks of noncompliant data handling or data breaches that erode trust.

Generative AI adoption further complicates the landscape as AI and data privacy concerns rise. An IBM report found that 63 percent of companies lack proper governance for AI-based security systems, exposing both customer and employee data to risk.

PETs help mitigate risk by enabling data to be transmitted, stored, and shared securely, in line with global privacy regulations.

What are privacy-enhancing technologies?

Before examining categories and use cases, it is important to understand what PETs actually are. Privacy-enhancing technologies are tools and methods designed to protect data across its lifecycle — from collection to storage to processing and transmission.

These data privacy technology tools reduce the risks of data breaches, strengthen customer trust, and support business sustainability by aligning with regulatory requirements and user expectations.

Categories of PETs

PETs can be classified into distinct categories, each targeting a specific aspect of data protection. According to the Organization for Economic Cooperation and Development (OECD), PETs can be grouped into four main categories:

1. Data obfuscation
2. Encrypted data processing tools
3. Federated and distributed analytics
4. Data accountability

Each category contributes to compliance and secure data use across industries, from research and healthcare to marketing analytics.

Types of privacy-enhancing technologies

The UK Information Commissioner’s Office (ICO) has identified four key types of PETs that address different privacy needs — including compliance and user experience — and contribute to a privacy by design ecosystem.

Privacy-enhancing technologies for data minimization and security

This data privacy technology type makes personal data less identifiable, helping to limit the risks of unauthorized access. These PETs use mechanisms like data minimization, anonymization, encryption, and access controls.

Privacy-enhancing technologies for data derivation

Data derivation PETs weaken the connection between data from a person’s input and their identity. This makes them effective for helping to handle data exposure risks, though added noise can impact data utility in certain scenarios.

Privacy-enhancing technologies for data splitting and access control

Data splitting and access control PETs assist in personal data management within systems. These technologies help to preserve data integrity and confidentiality by splitting datasets for storage or analysis and using specialized hardware to limit data access.

Privacy-enhancing technologies for data hiding and shielding

Data hiding and shielding PET techniques include homomorphic encryption and zero-knowledge proofs. Homomorphic encryption enables encrypted data to be analyzed without revealing the underlying plaintext. Zero-knowledge proofs help verify the truths without disclosing the underlying data or extra information.

Regulatory perspectives on PETs

Data privacy technology is closely tied to achieving and maintaining regulatory compliance, and helps organizations align with legal requirements across multiple jurisdictions.

The GDPR and privacy-enhancing technologies

GDPR principles emphasize privacy by design, which includes limits on data collected and protecting it at every stage of processing, among other principles. PETs help businesses address:

• Data minimization (Art. 5 GDPR)
• Integrity and confidentiality (Art. 5 GDPR)
• Technical and organizational measures (Art. 25 GDPR)

CCPA and privacy-enhancing technologies

The CCPA emphasizes consumer rights, including disclosure, removal, and restrictions on data sharing. PETs such as consent management platforms (CMPs) support granular opt-in vs. opt-out choices, helping businesses meet these requirements.

Privacy-enhancing technologies examples in 2025: Company experiences

The need for PET integration continues to grow. Over 60 percent of large businesses worldwide are expected to have integrated at least one PET solution in their data security systems by the end of 2025. Their data privacy technology sets will include tools used in business intelligence, analytics, and cloud computing. 

Roche and PETs: Fully Homomorphic Encryption (FHE)

Roche uses fully homomorphic encryption to analyze encrypted patient data from laboratories without decryption. This shielding helps secure data sharing and analysis and supports GDPR compliance and protects patient privacy. 

Upon implementation, Roche’s operations data is encrypted so that laboratories cannot access its proprietary algorithms. PETs enabled Roche to support compliant research collaborations with simplified security procedures. This approach also helped reduce the risk of data breaches, which had an average cost of USD 4.88 million in 2024. 

Google and PETs: Federated Learning and Differential Privacy

Google uses two privacy-enhancing technologies — federated learning and differential privacy — to analyze data across devices without centralizing users’ raw data. 

Google uses federated learning in its Gboard keyboard to improve predictive text. This enables user data to stay on on individual devices, and only model updates are sent to Google’s servers, not specific keystrokes.

Differential privacy is a tool that adds statistical noise to aggregated data, limiting the risk of identifying individual users. This way, data can be shared with less risk of exposure or consent violations. A critical improvement when regulatory fines under the GDPR can reach up to four percent of global annual revenue or EUR 20 million per infraction.

For Google and its global reach, these privacy-enhancing techniques help safeguard user privacy while still supporting key revenue drivers, including search, Google Assistant, and personalized advertising.

Microsoft and PETs: Confidential Computing

Microsoft migrated Windows licensing to Azure Confidential Computing in 2025, so businesses can run analytics or AI workloads without revealing sensitive data to the cloud provider or unauthorized users. 

This update helped to boost data security and support regulatory compliance, which in turn builds trust with customers demanding secure, scalable cloud services.

Benefits of privacy-enhancing technologies (PETs) for organizations

By supporting regulatory compliance and helping to maintain customer trust, adopting data privacy technology  has several tangible benefits.

• User data protection: Privacy-enhancing technologies support data minimization principles, which reduces risks related to personal data processing and storage and supports privacy compliance.
• Secular, granular data sharing: Privacy-preserving technologies enable implementation of granular access controls, limiting third-party access to authorized users.
• Cost effectiveness: By minimizing the risk of data breaches and other privacy violations, privacy-enhancing technologies help companies save money and resource allocation in responding to issues and maintaining complex tech ecosystems.

Stronger of consumer trust: A majority of Americans believe there should be more governmental regulation over how businesses can handle user data. To earn and maintain trust, businesses must demonstrate respect for data and user privacy and provide clear choices, as with data privacy technologies.

Challenges and limitations of PETs

PETs should not be the only tool in companies’ data privacy compliance strategy. A more sustainable approach is to make privacy-enhancing technologies part of a comprehensive system that supports data privacy every stage handling.

“When leveraging PETs, businesses should keep regulatory compliance and business requirements in mind, as well as internal data strategies and security policies. They should consider the future, short and long-term, and what flexibility and scalability needs the company will have, including costs and integrations with existing systems.”

Adelina Peltea

— CMO of Usercentrics

PETs are not infallible

Privacy-preserving technologies should complement other security approaches, not replace them. Organizations should integrate multiple security layers into business processes for more comprehensive protection that scales as companies grow.

PETs can affect data utility

Privacy-enhancing technologies can reduce the utility of the collected data, which can affect marketing and other business processes. Companies need to balance data security with business objectives that rely on high-quality data. The right balance requires a data minimization approach across operations.

PETs may conflict with user privacy rights

PETs can conflict with user privacy rights. For instance, anonymization techniques can protect data from misuse, but they shouldn’t prevent individuals from exercising rights, like access or deletion. Business leaders should invest in data privacy technologies that uphold privacy principles and balance operational requirements and user expectations.

PETs may be resource-intensive

Depending on the technology used, investing in PETs can be costly in time, money, and human resources. Some data-preserving technologies, like consent management platforms, can be seamlessly integrated within your tech stack. Others, like federated learning and homomorphic encryption, may require new infrastructure, specialized expertise, or even refactoring existing systems.

Best practices for adopting privacy-enhancing technologies

PETs enable you to achieve data-driven results without compromising privacy. Adopting them effectively requires a privacy by design approach.

• Make privacy by design a core value: Create and implement a holistic privacy strategy and integrate it into all stages of planning and development.
• Choose relevant PETs for your privacy needs: Options include consent management platforms, data anonymization tools, data encryption technologies, and more. Aim to implement a combination of PETs for layered privacy.
• Design for better user experience: Prioritize usability and transparency as you implement technologies and clearly communicate the changes with your users.
• Ensure PETs align with your business goals: Establish clear, measurable objectives like improved consent rates, secure AI model training, or reduced data exposure.
• Invest in cross-functional training: Equip data-using teams across the company to collaborate on PET initiatives so everyone understands and works to make data privacy a competitive advantage.

Key factors in selecting PETs 

To minimize risk of issues with PET implementation, businesses need to choose a data privacy technology that works for their industry, regulatory requirements, business operations and goals, and user expectations. 

Here are a few important questions to ask to help you choose a PET for your privacy compliance needs:

• Does it help you comply with current relevant regulatory requirements and partners’ policies, and adapt to legal changes?
• Does it align with your current tech infrastructure (analytics, AI/ML, cloud storage etc.)?
• Does it contribute to improved user experience?
• Does it have robust documentation and timely support for when you need them?

Privacy-enhancing technologies: AI and future trends

Tools like federated learning and automated consent management already use AI-based systems and machine learning (ML) models to support streamlined privacy compliance. In the future, privacy-enhancing technologies with these innovations will continue to become more integrated into digital ecosystems and enable greater protections at scale. 

Some potential trends for AI-driven privacy-enhancing technologies include:

• AI-powered privacy automation: AI-driven PETs will increasingly automate consent management and privacy compliance, adapting in real-time to evolving regulations, policies, and user preferences.
• Enhanced risk detection: AI models integrated with PETs can help detect anomalies and mitigate potential privacy risks early, especially in complex, distributed data environments.
• Multi-layered privacy protection: Combining AI with PET methods like differential privacy and encryption supports strong, flexible safeguards without sacrificing data utility.
• Better privacy and preference management: Transparent, AI-enabled privacy controls can better use consent and preference signals from customers for enhanced user experience and demonstration of your privacy commitment.

How Usercentrics supports privacy-enhancing strategies

The Usercentrics Consent Management Platform (CMP) is one data privacy technology that helps businesses achieve privacy compliance and show your customers that you respect their data and privacy.

The Usercentrics CMP prioritizes privacy compliance while balancing business needs for high-quality data and consumers demands for control.