Conversion tracking is getting harder. Browser restrictions, ad blockers, and stricter privacy tools are all limiting the data that advertisers can rely on. For businesses, this means incomplete reporting, unstable campaign performance, and wasted ad spend.

Server-side conversion tracking offers a way to take back control. By moving tracking to your own infrastructure, you gain more reliable data, extended attribution, and stronger compliance with privacy laws. It’s not a plug-and-play solution, but the payoff for the effort it takes to implement is better optimization, more accurate insights, and a future-proof setup for your marketing.

Here’s what you need to know about what server-side conversion tracking is, who it benefits, and how you can implement it quickly.

What is server-side conversion tracking?

Server-side conversion tracking sends conversion data from your servers directly to advertising platforms via application programming interface (API) connections. Your server processes conversion events and forwards them to ad platforms, eliminating browser dependencies entirely.The core difference between server-side and client-side tracking is control. Browser-based tracking pixels depend on user environments you can’t influence, plus ad blockers, JavaScript settings, and privacy tools can interfere. Server-side conversion tracking handles everything on the infrastructure you manage, so you’re less impacted by those limitations.

Why use server-side conversion tracking?

Understanding what server-side tracking does is just the first step. Your next question is whether the benefits justify the additional setup complexity compared to traditional pixel implementations.

To help you decide, consider these benefits to server-side conversion tracking.

Improved campaign optimization

Ad platforms rely on conversion data to make bidding decisions. When Facebook’s algorithm receives incomplete signals, it struggles to identify which audiences and placements drive results. Server-side tracking provides the fuller picture these algorithms need.

With more accurate data, automated bidding strategies can be more effectively optimized. Cost per acquisition metrics stabilize, and campaign performance typically improves within two to four weeks of implementation.

Extended attribution windows

Browser restrictions are shortening attribution windows, making it difficult to track conversions that occur days after initial ad exposure. Server-side tracking maintains the attribution windows your business actually needs.

For e-commerce brands with longer consideration cycles, this change often reveals about 20 percent more conversions that were previously invisible. Business-to-business (B2B) campaigns also benefit since those sales cycles frequently extend beyond standard attribution windows.

Improved data quality and consistency

Client-side tracking produces inconsistent results across different browsers, devices, and user configurations. Some users generate perfect tracking data while others provide none at all.

Server-side implementation provides consistent measurement regardless of user setup. Every conversion gets captured and reported uniformly, giving you reliable data for analysis and optimization decisions.

Key platforms that support server-side conversion tracking

Given these clear advantages, a variety of platforms now offer server-side solutions. Each takes a slightly different approach, but all address the same core tracking reliability issues.

Google Ads server-side tracking

Google Ads server-side tracking uses the Google Ads API or enhanced conversions to send conversion data directly from your servers. The platform supports both real-time and batch conversion uploads.

Enhanced conversions can work alongside server-side implementation by using hashed customer data to improve conversion matching. This combination often provides the most comprehensive tracking setup for Google campaigns.

Facebook server-side tracking

Facebook’s Conversions API (CAPI) enables you to send conversion events directly to Facebook’s servers. That means you’re bypassing browser limitations entirely.

CAPI supports all standard Facebook conversion events plus custom events specific to your business. The API can handle real-time event streaming or batch uploads, depending on your needs and technical setup.

TikTok server-side tracking

TikTok server-side tracking operates through their Events API, which accepts conversion data from your servers. The platform supports standard e-commerce events and enables custom event definitions for specialized tracking needs.

TikTok’s implementation tends to be more straightforward than Facebook’s due to clearer documentation and fewer configuration options to manage.

Requirements before you get started

Before you get started, be aware that server-side conversion tracking requires some foundational elements to work properly. 

The following three requirements apply regardless of which advertising platforms you plan to use.

Server or container setup

To set up server-side conversion tracking, you need a server environment capable of receiving conversion events from your website and forwarding them to advertising platforms. Google Tag Manager (GTM) server-side offers the most accessible option for most businesses.

GTM server-side can deploy on Google Cloud Platform, AWS, Azure, and other cloud providers. Choose a region close to your primary audience to minimize latency, which can affect attribution accuracy.

Alternate approaches include custom server implementations or third-party tracking solutions like the Usercentrics Server-Side Tagging Solution. We offer pre-built templates and detailed documentation, so you can get started in minutes, without a single line of code. 

[H3] Consent management integration

Privacy regulations like the EU’s General Data Protection Regulation (GDPR) and California’s Privacy Rights Act (CPRA) require that server-side tracking respect user consent. Be sure to check that your consent management platform integrates with your server-side setup to enforce consent decisions at the server level.

This integration helps ensure that conversion data only flows to platforms where users have provided appropriate consent. Without this connection, your server-side implementation could violate privacy regulations.

API access and credentials

Each advertising platform requires specific API access and authentication credentials:

• Google Ads needs API access through your Google Ads account
• Facebook requires app creation and business verification for CAPI access
• TikTok needs Events API access through their advertising platform

Obtain these credentials before starting the implementation process. And be sure to plan ahead — approval processes can take several days, depending on the platform and your account history.

How to set up server-side conversion tracking (step-by-step guide)

With your requirements in place, you can move to the actual implementation. Rather than following a rigid step-by-step process, server-side tracking is usually set up in multiple parts at the same time, which are then connected into a larger system.

1. Establish your server infrastructure first

Deploy GTM server-side or build custom server endpoints that can receive conversion events from your website. Configure your chosen solution with appropriate resource allocation and set up a custom domain for better attribution accuracy.

2. Prepare your data collection simultaneously

Update your website to capture conversion events in a format suitable for server-side processing. You may need to modify existing tracking code or implement new event collection methods.

3. Configure platform connections as infrastructure becomes ready

Create the necessary API credentials and authenticate your server with each advertising platform. Then, set up conversion actions in each platform to properly accept server-side data.

4. Test everything before going live

Send test conversions through your completed setup and verify that data appears correctly on all platforms. Run parallel tracking to compare server-side data with existing measurement methods.

The key is to treat setup as system integration rather than sequential steps. Different parts can progress independently as long as they eventually connect.

Server-side tracking and compliance with global privacy laws

Server-side conversion tracking gives you more control over how data is collected and processed. But more control doesn’t mean less responsibility. It won’t replace the need to comply with global privacy regulations, but it does put compliance decisions directly in your hands.

Under the GDPR, you need a clear legal basis for processing personal data. That could be legitimate interest when measuring conversions, or explicit consent for marketing optimization. Your privacy policy should clearly reflect these purposes so users understand how their data is being handled.

In addition, consent choices must be reflected in your server-side setup. If someone opts out of advertising cookies, your server has to respect that decision by stopping data transmissions to platforms. This is only possible if your consent management solution is fully integrated with your server infrastructure, not just your website.

Data minimization practices become even more important in a server-side model. Because you choose exactly what information is processed, regulators expect you to limit collection to what’s necessary. Avoid sending extra customer details simply because the technology allows it.

Cross-border data transfers also require careful planning. For example, if EU customer data is processed on US-based servers, you may need additional safeguards. Choose your hosting locations wisely and apply the right protection measures to mitigate risks.

Finally, retention and deletion are now your responsibility. With pixel-based tracking, platforms handle much of the data lifecycle. Server-side tracking puts that in your hands. You must define how long data is stored and put processes in place to delete it when required.

Better conversion data starts with server-side tracking

Browser restrictions will continue tightening, making reliable conversion measurement increasingly difficult when using more traditional approaches. Server-side tracking offers a path forward that puts you back in control of your data collection.

The setup may require more technical work upfront, but the payoff is immediate: more complete conversion data, better campaign optimization, and measurement that works regardless of browser limitations. You’re setting your marketing efforts up for future success.

Google Analytics server-side tracking is quickly becoming a must-have for businesses that need accurate, privacy-compliant analytics. Server-side tagging offers a way to regain control over your data and future-proof your marketing strategy.

Instead of sending tracking information directly from a user’s browser to Google Analytics, server-side tracking routes the data through your own server first. This extra step gives you more control over data quality, supports compliance with privacy regulations, and helps reduce data loss from ad blockers and browser restrictions.

So, let’s talk about how Google Analytics server-side tracking works and how to set it up step-by-step using Google Tag Manager and GA4.

Google Analytics 4 and server-side tracking: what you need to know

The shift to server-side tracking represents more than just a technical change; it’s a fundamental rethinking of how web analytics works. With traditional client-side tracking, data collection happens in browsers, which can significantly restrict data access and flow. Server-side tracking puts you back in control.

When you implement Google Analytics 4 server-side, your website sends collected data to your servers instead of directly to Google. Your server then processes this data and forwards relevant information to GA4 using the Measurement Protocol API. This two-step process might seem more complex, but it solves several important problems associated with traditional tracking methods.

The Measurement Protocol API accepts the same event data that would normally come from browser scripts, but processes it through your infrastructure. You send HTTP requests containing event parameters, user identifiers, and measurement data. 

Your server then becomes the gatekeeper that validates, cleans, and forwards information based on your business rules and privacy requirements.

Differences from Universal Analytics setup

Universal Analytics was not made with server-side tracking in mind, which complicated the process. You could send data, but then companies would lose enhanced ecommerce features and audience capabilities.

GA4 fixed these limitations. Server-side and client-side events work the same way in reports. You can build audiences, set up conversions, and access all platform features regardless of how you collect the data.

Key benefits of using Google Analytics with server-side tagging

Server-side web analytics addresses several limitations that plague traditional tracking methods. The benefits extend beyond just data collection. Server-side analytics tracking impacts your entire analytics strategy.

Improved data accuracy and control

Ad blockers affect roughly 25 percent of web traffic, which can cause significant gaps in your analytics. When you compare server-side vs client-side analytics, there’s a clear winner when it comes to data completeness. Server-side web analytics bypass these restrictions entirely because the data flows directly from your servers to Google Analytics.

You also gain more control over data quality. Instead of accepting whatever the browser sends, you can validate events, clean up parameters, and ensure consistent formatting before forwarding to GA4.

Greater user privacy and data privacy compliance

Many privacy regulations, such as the EU’s General Data Protection Regulation (GDPR), require explicit consent before collecting personal data. Server-side tracking enables you to apply consent preferences at the server level. That means that data only flows to Google Analytics from users who have opted in.

This approach also supports data minimization and limits transmission of personally identifiable information (PII). You can strip out sensitive details, hash email addresses, or anonymize IP addresses before sending data to third parties.

Reduced data loss from ad blockers and browser restrictions

Apple’s Intelligent Tracking Prevention (ITP) and similar browser features limit how long tracking cookies persist. Server-side analytics tracking extends cookie lifetimes because the data processing happens on your domain rather than through third-party scripts.

Safari’s ITP limits client-side cookies to seven days for cross-site tracking. Server-side tracking can maintain user identification for much longer periods, which improves attribution accuracy for longer sales cycles.

Faster load times

Attribution modeling relies on your ability to connect user actions over time. When cookies expire prematurely, you’re no longer able to attribute conversions to earlier touchpoints in the customer journey.

Server-side tracking maintains first-party cookies for extended periods, often up to two years instead of the seven-day limit imposed by browser restrictions. This extended timeline provides more accurate attribution data for your marketing campaigns.

How to set up Google Analytics server-side tracking 

Setting up GA4 server-side tracking isn’t something you can flip on with a single switch. It requires some planning and technical configuration.

The process involves three main stages: preparing your infrastructure, sending data from the client to your server, and then forwarding that data to Google Analytics.

Prerequisites and tools

Before you dive into implementation, make sure you have the following in place:

• Google Tag Manager server container: This acts as the core infrastructure for processing and routing your analytics data. You can host it on Google Cloud Platform (the default), your own servers, or other cloud providers.

• Custom domain: For first-party cookie status, the server container should run on a subdomain of your website (e.g. analytics.yoursite.com.)
• GA4 property: Confirm that your GA4 property is configured with the events, parameters, and conversions you want to track.
• Development resources: Server-side tagging isn’t a plug-and-play setup. You’ll need developers familiar with web tracking, server management, and API integrations.

Once these foundations are in place, you can begin the actual implementation process.

Sending data from the client to your server endpoint

The first step is to redirect event data from the browser to your server container instead of sending it straight to Google Analytics. You’ll need to:

• Update your GA4 tracking code: Replace the standard GA4 script with a version that points to your server endpoint. Functionally, the client-side code still gathers events (page views, clicks, conversions, etc.) but it routes them through your custom domain.
• Leverage the data layer: Configure your website’s data layer so that all relevant events and parameters are included. This helps ensure that your server receives a complete, structured picture of user interactions.

In short, you’re inserting your own server as a “middleman” between the client and Google Analytics.

Forwarding hits from your server to Google Analytics

Once the data arrives at your server container, it needs to be processed and sent on to GA4 using the Measurement Protocol API. This is where most of the configuration happens:

• Set up a GA4 client in Google Tag Manager (GTM): This client listens for incoming requests from your site and interprets them in a way your server can handle.

• Create server-side tags: These tags format the data correctly and forward it to Google Analytics. They also give you the opportunity to apply transformations (e.g. anonymizing IPs, enriching data, or filtering out noise.)
• Implement consent logic: Respect user privacy by ensuring that only those who have opted in are tracked. This is especially important for compliance with the GDPR, CCPA, and other privacy regulations.
• Thoroughly test your setup: Use the GTM preview mode and GA4 debug tools to confirm that events are flowing as expected and reporting correctly.

When done properly, server-side tagging provides a more controlled, privacy-friendly, and reliable way to collect analytics data — while reducing your reliance on client-side scripts.

Use cases for Google Analytics server-side tagging

Server-side tracking comes with plenty of advantages, but that doesn’t mean it’s the right solution for every business. It tends to deliver the most value in specific scenarios. 

Here are some of the situations in which server-side tagging makes the most sense.

E-commerce tracking with enhanced security

Online retailers handle sensitive customer information throughout the purchase process. Server-side tracking enables you to collect detailed ecommerce data while maintaining strict security controls.

You can track product views, cart additions, and purchases without exposing sensitive data to client-side scripts. Payment information, customer details, and order data remain secure on your servers while providing rich analytics insights.

This approach is also valuable for businesses in regulated industries like healthcare or finance, where data security requirements are especially strict.

Ad campaign attribution without relying on third-party cookies

Third-party cookie restrictions make it difficult to attribute conversions to your advertising campaigns. Server-side tracking helps maintain attribution accuracy by using first-party data and server-side identifiers.

When a user clicks on your ad, you can store campaign parameters in your database and associate them with subsequent conversions through server-side events. This method provides more reliable attribution data than browser-based tracking alone.

Personalization with first-party data

Personalization engines need detailed behavioral data to deliver relevant experiences. Server-side tracking enables you to combine Google Analytics data with your customer database, Customer Relationship Management (CRM), and other first-party sources.

This unified view supports more sophisticated personalization while helping to maintain privacy compliance. You can segment users based on their complete interaction history rather than just browser-based behavior.

Taking control with Google Analytics server-side tracking

Server-side tracking is more than a technical tweak; it’s a strategic shift in how you manage your analytics. By routing data through your own infrastructure, you gain more accurate reporting, stronger privacy compliance, and the ability to protect against data loss caused by ad blockers and browser restrictions.

Whether you’re running an e-commerce store, managing ad campaigns, or building personalized customer experiences, Google Analytics server-side tracking gives you the tools you need to stay ahead in a privacy-first world.

If you’re ready to take control of your data and future-proof your measurement strategy, server-side tagging is the next step.

Your Google Ads campaign drove 1,000 clicks yesterday, but only 12 conversions showed up in your reports. Yet your sales team says it was their best day in months.

If that sounds familiar, you’re not alone. The gap between actual conversions and reported conversions is growing wider every month. Browser restrictions, iOS updates, and ad blockers are quietly undermining your tracking. What you see in Google Ads is often just the tip of the iceberg.

Server-side tracking flips the script. You don’t have to hope that browsers cooperate with your tracking tags, because your server takes control of the conversation with Google Ads. No more crossed fingers, no more mysterious attribution gaps, and no more campaign optimization with incomplete data.

What is server-side tracking in Google Ads?

Google Ads server-side tracking moves conversion measurement from the user’s browser to your own servers. Instead of relying on JavaScript tags that can be blocked or fail to load, your server sends conversion data directly to Google Ads through secure APIs.

The process involves three main steps: 

1. First, your website captures conversion events through server-side code or enhanced tracking setups. 
2. Next, your server processes this data and formats it according to Google’s requirements. 
3. Finally, the conversion information is sent to Google Ads through the Conversions API.

This method provides more consistent data flow compared to client-side tracking, because it doesn’t depend on browser behavior and user settings that you don’t control.

Server-side tracking vs. enhanced conversions vs. Consent Mode

Server-side tracking can easily get confused with enhanced conversions or Google Consent Mode, but they each serve different purposes and can actually work together to improve your tracking setup.

Server-side Google Ads tracking happens entirely on your servers. Your website sends conversion data through secure server-to-server connections, bypassing browser limitations completely. It provides the most reliable data delivery, but requires more technical setup.

Enhanced conversions still use client-side tracking, but add hashed customer data to improve matching accuracy. When someone converts, Google receives additional signals, like email addresses or phone numbers (in hashed form), to better connect conversions to ad clicks. This method helps recover some conversions that might otherwise be lost, but still relies on browser-based tracking.

Google Consent Mode manages how tracking tags behave based on user consent choices. When users decline cookies, Consent Mode switches to privacy-preserving measurement while still providing conversion insights. It works with both client-side and server-side setups to respect user preferences.

Since each has its own benefits and drawbacks, you can combine all three approaches. Server-side tracking provides the foundation for reliable data collection. Enhanced conversions improve matching accuracy for the data you collect. Consent Mode supports respecting user privacy choices.

Benefits of Google Ads server-side conversion tracking

The benefits of shifting to server-side tracking extend beyond just recovering lost conversions.

Data accuracy that matters

Client-side tracking has become increasingly unreliable, as more businesses lose conversion data to browser restrictions. Using server-side for Google Ads tracking can help eliminate these gaps by handling measurement on your servers, where external factors can’t interfere.

It’s not just about seeing bigger numbers in your reports. More complete data means Google’s automated bidding strategies can make better decisions about when and how much to bid. Smart Bidding algorithms work exponentially better with clean, consistent signals rather than patchy or incomplete data.

Attribution windows that reflect reality

Browser restrictions are forcing attribution windows to be shorter and shorter, making it difficult to track conversions that happen days or weeks after ad exposure. Server-side tracking maintains the attribution windows you actually need for your business model.

For businesses with longer consideration phases, this change alone can reveal valuable insights about conversions that were previously invisible. Suddenly, campaigns that looked like they were not profitable start showing their true contribution to your revenue.

Improvements to your website performance

Traditional tracking setups can slow down your site with multiple JavaScript tags that need to load and execute. Google Ads server-side tracking moves this processing burden to your servers, reducing the scripts that bog down your pages.

The result is faster loading times that translate to better user experience and higher conversion rates. You’re not just improving your tracking accuracy; you’re potentially improving the conversions themselves.

How to set up server-side conversion tracking for Google Ads (step-by-step breakdown)

The implementation process might look daunting, but it doesn’t have to be. We’ve broken it down into manageable phases to make server-side tracking achievable for teams without requiring extensive development resources.

Success depends more on careful planning than complex coding. Most businesses can implement basic server-side tracking within two to four weeks using existing tools and platforms.

Preparation phase: Audit your current setup

Start by documenting every conversion action currently tracked in your Google Ads account. Note which conversions drive the most value for your business, as these should be at the top of your list of server-side tracking priorities.

Then, export your historical conversion data to establish baseline metrics. You’ll use these benchmarks later to measure the impact of your server-side implementation.

Next, identify the customer touchpoints where conversions happen. Online purchases, form submissions, phone calls, and app installs each require different server-side tracking approaches.

Implementation phase: Choose your technical approach

Google Tag Manager (GTM) server-side offers the most straightforward path for most businesses. This approach leverages Google’s infrastructure while providing control of server-side tracking.

To implement, deploy your GTM server-side container on a cloud platform. Google Cloud Platform provides seamless integration, but AWS, Azure, or other providers work just as well. The key is selecting a region close to your primary audience to minimize latency.

Configure your website to send conversion events to your server container instead of directly to Google Ads. This typically involves updating existing GTM tags or implementing new event tracking code.

Custom API integration gives you maximum control, but does require more development resources. Still, if you have specific data processing requirements or want to integrate with existing server infrastructure, direct API implementation might be worth the additional complexity.

Testing and validation 

Send test conversions through your new server-side setup before switching any live campaigns. Verify that conversion data appears correctly in Google Ads and includes all the parameters your campaigns need for optimization.

Run parallel tracking for one to two weeks to compare server-side conversion data with your existing client-side tracking. Doing so will help you identify any gaps or discrepancies before making the full transition.

During the testing phase, monitor server performance and response times. Slow server responses can impact attribution accuracy, so address performance issues before going live with production traffic.

Tips for tag configuration

Server-side conversion tracking delivers the best results when your tags are set up thoughtfully. A few technical considerations can make the difference between clean, reliable data and frustrating attribution gaps.

One of the first decisions is container placement. If you host your GTM server-side container in the same region as your primary audience, it helps reduce latency, which in turn improves conversion attribution for time-sensitive campaigns. 

It’s also worth considering server resources early on. Start with moderate specifications that match your traffic, and scale as demand grows to keep data flowing smoothly.

Accuracy is also important when it comes to trigger setups. Conversion tags should fire only when real conversions occur, so it’s important to build in deduplication logic to prevent inflated numbers. 

At the same time, server-side setups enable you to enrich the data you send to Google Ads. Passing parameters like order value, product category, or customer segment can give the bidding algorithm more context and ultimately improve campaign optimization.

API integrations also deserve careful attention. Network hiccups and temporary service interruptions are inevitable, but they don’t have to cost you conversion data. With proper error handling and retry logic, failed calls can be recovered automatically. Logging is just as valuable for troubleshooting, as long as you do not store sensitive customer details.

Finally, don’t overlook data quality. Before you send anything to Google Ads, make sure the required fields are present, values are properly formatted, and currency codes are correct. Data freshness also matters. Outdated conversions are less useful, and Google Ads has strict rules about how recent data needs to be for optimal performance.

Troubleshooting common setup issues

Even with careful implementation, server-side tracking setups can encounter issues that affect data quality or campaign performance.

Here are a few common issues and how to solve them.

Conversion attribution problems

If conversions aren’t attributing correctly, first verify that your server is sending the Google Click ID (GCLID) or other click identifiers properly. These parameters link conversions to specific ad clicks and are essential for accurate tracking. 

Next, review your conversion timing settings. Sending conversions too long after the original click may fall outside of Google Ads’ attribution window.

Data validation errors

API rejections often come from incorrectly formatted data, like invalid currency codes, missing fields, or values that exceed Google’s limits. Follow Google’s Conversions API documentation for current formatting rules. 

If you’re using enhanced conversions, make sure customer information like emails and phone numbers is normalized and hashed with SHA256 before sending.

Performance and latency issues

Slow server responses can affect conversion accuracy. Monitor server performance, optimize database queries, and review any external API calls that might introduce delays. 

For high traffic periods, consider implementing queuing systems to prevent conversion data loss during spikes.

Debugging data flow

Comprehensive logging is important at every stage of your pipeline. Track when conversions are received, processed, and sent to Google Ads. This visibility makes it easier to pinpoint issues. Use Google Ads’ conversion tracking and debugging tools to confirm that your server-side conversions are being received and processed correctly.

Measuring the impact: what to expect

After you implement Google Ads conversion tracking server-side, it’s normal to see improvements in data quality within a few weeks. While an exact timeline and changes can vary by business, here’s what you can most likely expect.

Immediate improvements

In the first week after implementing server-side tracking, organizations often notice more consistent conversion reporting. Daily conversion counts stabilize, with fewer gaps or unusual spikes caused by tracking failures. 

Conversion data also becomes more complete, especially if ad blockers or browser restrictions were previously causing losses.

Medium-term campaign optimization

Over the next two to four weeks, Google’s automated bidding strategies will start leveraging the improved conversion data. Cost-per-acquisition metrics typically become more stable, and overall campaign performance improves as algorithms receive higher-quality signals. 

Attribution reporting also becomes more comprehensive. You’ll have a clearer picture of how different touchpoints drive conversions, which can inform smarter budget and strategy decisions.

Long-term strategic benefits

After one to two months, the combination of better data quality and improved algorithmic optimization often leads to measurable gains in return on ad spend. The impact depends on how much conversion data was previously lost when you were using client-side tracking. 

More complete customer data also boosts lookalike audiences and segmentation, which supports both acquisition and retention campaigns.

Elevate your marketing results using Google Ads server-side tracking

Google Ads campaigns are based on the quality of the data they run on. When conversions slip through the cracks because of browser restrictions or ad blockers, you’re left with incomplete insights and campaigns that can’t reach their full potential. 

Google Ads server-side tracking shifts measurement to your own servers, helping ensure conversions are captured consistently and sent directly to Google Ads.

The payoff goes beyond better reporting. With steadier data, Smart Bidding can optimize more effectively, attribution windows reflect real customer journeys, and your campaigns get the signals they need to scale and drive profits. It’s the difference between campaigns that are guessing at performance and those optimizing with confidence.

You can hide a $10 bill from unauthorized access. But when you need to store and manage $100,000, controlling each $10 bill becomes harder. 

In data privacy best practices terms, you will need to choose among several types of measures to keep the whole sum safe. 

First, you may decide to keep all those $10 bills together in one place. In this case, you increase their visibility and, thus, the risk of unauthorized access. To protect your money, you’ll need to hire a guard, get security cameras, build high fences, and invest in other protective measures while dealing with privacy and security issues. 

Alternatively, you can design a data privacy security system with diversified denominations and different storage places for your $100,000 sum. Here, you’ll face the challenge of managing data protection in all these separate sources, but getting the complete $100,000 from you will become much harder.

Managing your personal data is just like choosing how to manage that big sum of money. You need to understand what the sensitivity levels of your personal information are. Then, you can diversify the risks and launch accurate data privacy practices to protect it from unauthorized access. 
This guide will show how to choose and apply the most relevant data privacy best practices for your personal information.

What are data privacy and data security practices?

User data protection is achieved through data privacy and data security practices. While data security focuses on maintaining measures that safeguard sensitive information from unauthorized attacks, data privacy is a more complex term that governs how data is collected, shared, and used.

In simpler words, data security asks, ‘How to protect data?’, while data privacy asks, ‘Why do we have this data, and is how we protect it appropriate?’.
Together, data privacy and data security practices are guidelines and measures that ensure managing sensitive data as a strategic business asset and protect personal identifiable information (PII) with the best tactics. 

Data privacy best practices: Why protecting user data matters in 2025

Each time we go online, we leave a growing digital trace. Be it the greater number of personal photos on your cloud storage or more detailed corporate data in your scaling business, the biggest sensitive information challenge is that it constantly increases in volume. 

Due to its size, it’s getting harder to protect data privacy from corruption, data breaches, and other types of unauthorized access. It’s just too much data, and it increases every day.

That’s why you need to be clear about what information you store and how you protect it. Then, depending on your circumstances and tech abilities, you can apply different data privacy best practices to secure all your sensitive data. 

Important compliance laws and regulations for data privacy best practices

For the data privacy guidance, several key compliance laws and regulations establish the legal basis for modern data protection architecture. Here are some of them:

• General Data Protection Regulation (GDPR) applies to any organization processing EU residents’ data, 
• California Privacy Rights Act (CCPA) and California Consumer Privacy Act (CCPA) protect the consumer rights of California residents,
• EU Data Act protects the Internet of Things (IoT) data privacy of EU residents,
• Brazil’s LGPD serves as a Brazilian analog of GDPR with local elements, and
• Canada’s PIPEDA is the act for personal information protection in Canada.

These compliance regulations establish the foundation for transparency, data minimization, and storage limitation, and serve as the basis for data privacy best practices described below.

Data security and privacy best practices: Active tech measures

Among the data privacy best practices you can implement on the technology level, you can rely on minimizing data collection, improving storage security, and getting privacy-first security software.

Minimize data collection for managing data protection

Data minimization is the practice of collecting, processing, and storing the minimal amount of personal information for any specific purpose. Among all the data privacy best practices, it is one of the quickest fixes a company can do to reduce risks and improve compliance.

Data anonymization, or erasing identifiers on personal information, is one of the ways to achieve data minimization. Also, as the key security and privacy policy recommendations, consider:

• Being vigilant regarding sensitive data
• Avoiding the practice of keeping extra data “just to check our future hypotheses”
• Embedding storage limitations into the design of systems and processes in a company  

In data-driven companies, it’s always tempting to collect as much information about users as possible. Some believe it’s better to have strong data to experiment and iterate. 

But this practice increases the occurrence of data privacy problems. So, a more sustainable approach is to stabilize the risk by collecting only the necessary and compliant information.

How to ensure data security and storage protection

In addition to limiting the amount of data collected, improving the storage limitation, or the way it’s managed, is also among data privacy best practices. You should build a system that collects just enough data, stores it for a minimal period, and then deletes, destroys, or anonymizes it.

The most common data security and storage protection practices include:

• Encrypting data both at rest and in transit
• Letting only authorized users access the data
• Linking deleting personal data with the action of changing an account status to ‘inactive’

Cleansing the data after it’s no longer necessary is among the key GDPR and CCPA requirements. 

Ensure compliance with data privacy-first technology

Data privacy management software is a data privacy practice that helps with keeping regulatory responsibilities for managing sensitive data. The decision to get privacy-first software facilitates automating compliance, building trust, and reducing legal risks. 

Among the range of privacy-first technology types, consider these tools to stay compliant and efficient:

• Consent management platform for automated consent collection and blocking.
• Server-side tagging for moving data processing from the user’s browser to a secure server that ensures better data accuracy, control, and compliance.
• Advanced Privacy Enhancing Technologies (PETs) for data anonymization, encryption, and access control privacy management tools.

You can get the tech solution that assists with each separate data privacy function — or invest in data privacy-first technologies like Usercentrics to comply with compliance regulations on all levels of protecting sensitive information.

Security and privacy policy recommendations: Strategic improvements

Perceiving data privacy strategically is seeing it as a trust-building and compliance-ensuring measure that prevents your business from making costly mistakes. These data privacy best practices will help you integrate data protection in your business operations.

Protecting data privacy by design

With a privacy by design approach, you build the system that considers personal data protection from the development stages, not while reactively dealing with the data privacy problems. 

In practice, data privacy by design includes these regular practices:

• Assessing data privacy risks before launching any initiatives
• Conducting regular training for data privacy and security
• Having an incident response plan developed and available 
• Setting default settings to privacy-friendly options
• Getting consent management at the core of business

With data privacy by design measures, you embed privacy protections proactively and cover all the vulnerabilities that may lead to the data privacy problems.

Managing data protection by building a privacy-aware corporate culture

Transparency and purpose limitation are the foundation of ethical data practices. Thus, a key proactive user data protection practice is to ensure that each business unit understands why collecting only absolutely necessary data for legitimate purposes only is the only way. 

Making data privacy awareness part of a corporate culture means that each employee understands how data privacy works and what their role is in protecting user data privacy. Here is how you can do it:

• Conduct regular training on data privacy and data compliance standards
• Add a data privacy slide to the onboarding flow
• Conduct regular privacy and security audits and react to the possible problems
• Launch regular discussions and open talks on data privacy to keep the topic up-to-date and shared
• Optional: for extra motivation, you can nominate privacy champions in each team to undermine its importance. 

With these measures, you’re building data privacy as a strategic function within an organization. Ideally, it will mean that all the teams think as user advocates and protect building sustainable relationships with them.

How to ensure data protection by giving users control

Making consent and policy clear before collecting the data is about empowering users. They can make informed decisions and actively participate in protecting their sensitive data. 

However, simply letting people manage their own data privacy is not enough for tis measure. You need to work on your communication and processes to make it work:

• Make it easy for them to see their privacy settings and understand what they can do with them
• Simplify the legal language of a privacy policy so users can fully embrace their data control
• Add granular consent options with clear types of consent described and understandable permissions given

Allowing people manage their data is a good practice. Even though these measures require extra effort and thought leadership, they contribute to building transparency and trust between service providers and their users.

Implementing data protection best practices: What’s next?

Introducing data privacy and data security practices may seem costly, but the potential business losses from severe violations can reach up to EU 20 million in GDPR penalties only. 

Getting a data privacy-first technology from Usercentrics is more cost-effective in comparison. It can help you build the privacy by design that fixes current data security problems, maintains data privacy compliance, and contributes to building trust with your audience.

You can choose one tech solution among several data privacy best practices at a time. Alternatively, you can make a strategic decision to start investing in privacy by design to protect all your sensitive information. 

Each of these measures will contribute to creating a conducive environment where each piece of data, be that a bill in your $100,000 sum or a detail of your personal information, is safely protected.  

Few tools are as powerful as Google Tag Manager (GTM) when it comes to website analytics and marketing automation. GTM is currently used by 48.1 percent of websites, and still holds a dominant market share (around 95 percent) in the tag management industry.

A properly executed Google Tag Manager setup is like adding a mission control centre to your website. You can manage all your tracking codes, analytics scripts, and marketing pixels in one centralized location without constantly editing site code.

This Google Tag Manager guide is not just about getting you up and running with a basic tag manager setup. It will also give you a comprehensive understanding of how GTM works, why it’s valuable, and how to structure it so your tracking remains accurate and scalable over the long term.

Whether you’re tackling your first GTM implementation or refining a more mature GTM setup, this guide will help you approach it with confidence.

We’ll cover Google Tag Manager basics like tags, triggers, and variables, but also look into advanced topics like Google Tag Manager custom event trigger setup, cross-domain tracking, and server-side GTM implementation.

How to use Google Tag Manager

To understand how to use Google Tag Manager, you first need to grasp its role in the broader ecosystem of website analytics, advertising and conversion tracking. 

At its core, Google Tag Manager is a container-based system. That container — created during your Google Tag Manager account setup — is a hub for tracking tags, triggers, and variables you’ll need for your site or app. 

Instead of opening up your website’s source code every time you want to make a change, you place all your tracking logic inside GTM and publish it from one centralized interface. 

For those completely new to the platform, think of Google Tag Manager for beginners as a middleman between your website and all the marketing tools you use. 

Instead of manually embedding different tracking codes for Google Analytics, Facebook Pixel, LinkedIn Ads, and more, you only need to install the Google Tag Manager code. From then on, using Google Tag Manager means adding, editing, or removing any number of tags without touching your site’s core code. 

There’s a straightforward workflow to follow after your GTM setup. 

1. Creating tags

These are the scripts or pixels that send data to third-party platforms. They can be pre-developed templates like Google Analytics 4 (GA4), Google Ads, or custom HTML snippets. 

2. Configuring triggers

Triggers decide when the tags fire. This is where Google Tag Manager custom event trigger setup comes into play, enabling you to target specific user actions. 

3. Defining variables

Variables capture and pass information to tags, such as URLs, the ID of a clicked button, or the value of a transaction. 

4. Previewing and debugging

This is the process of simulating user activity and checking that tags are firing properly. 

5. Publishing changes

After testing, new tags go live to your audience. 

There is some flexibility around GTM implementation. You can use it for more than analytics, for example, deploying A/B testing scripts, adding heatmap tracking tools, or triggering custom marketing automation workflows. 

It’s important not to overload your first container with tags. Overcomplicating your initial setup of Google Tag Manager can lead to firing conflicts, slow page speed, and complex reporting. 

Having a clear roadmap and measurement plan is really important, especially when it comes to knowing which events, conversions, and behaviors you want to track. 

Key components of GTM: tags, triggers, and variables

Before diving deeper into Google Tag Manager implementation, you need a solid grasp of GTM’s three core components: tags, triggers and variables. 

These components are the building blocks of every Google Tag Manager setup, whether you’re conducting a basic tag manager setup for a small blog or a complex GTM implementation for an enterprise e-commerce platform.

Tags

A tag is a snippet of tracking code that communicates with third-party tools. You’ll often encounter pre-built tag templates for GA4, Facebook Pixel, and Google Ads. If you don’t want to use a templated tag, you can implement a Google Tag Manager code example into a custom HTML tag. 

Triggers

Triggers are essential in any Google Tag implementation as they provide instructions on when to run. Common trigger types include page views, clicks, and form submissions, but you can create custom event triggers. 

For example, if you only want your GA4 purchase event to fire after a successful checkout. In this instance, you’ll need to use a custom event trigger linked to an e-commerce transactionComplete event, if this is how your website’s Data Layer is structured. 

Variables

Variables collect and store the data that triggers and tags fire. These are also really important for a successful GTM setup. Google Tag Manager comes with built-in variables, like page URLs, click texts, referrers and form IDs. For more advanced GTM implementation, user-defined variables like lookup tables and JavaScript variables can be used. 

When setting up Google Tag Manager, it’s tempting to rush through creating tags without fully thinking through triggers and variables. But without the right trigger logic, tags may fire too often (causing data inflation) or not at all (causing missing data.) We recommend experimenting with a single tag, one trigger, and one variable first. Once you’ve confirmed in preview mode that your Google Tag implementation works, you can start layering in more complexity.

Step-by-step guide to setting up Google Tag Manager

Here, you’ll learn exactly how to set up Google Tag Manager from scratch. Whether you’re performing your very first Google Tag Manager account setup or reworking an older GTM setup, the steps below will walk you through the process.

1. Create your GTM account

When creating your GTM account, you’ll need to provide information about your location, business name, website URL or app name, and target platforms, e.g. web, iOS, Android, etc. 

For most GTM beginners, select web, unless you’re tracking a mobile app or implementing a server-side GTM setup.

2. Install GTM container snippet

Once your account is created, GTM will give you a Google Tag Manager code example. One snippet goes inside the <head> tag of every page. Another snippet goes after the opening <body> tag.

If you’re working with a CMS like WordPress or Shopify, there are often built-in GTM fields or plugins that handle this for you. If you’re hardcoding, give your developer these snippets to embed sitewide. 

This installation is the foundational step of Google Tag implementation, which enables GTM to load and manage tags on your site. Without this, none of your future GTM implementation work will take effect.

3. Add first tag (basic tracking)

This is the first step in the basic tag manager setup. From here, you can build event tracking, conversions, and more. To add your first tag, follow these steps: 

1. Select Add a New Tag 
2. Choose Google Analytics: GA4 Configuration from the tag templates
3. Enter your GA4 Measurement ID (found in the GA4 property settings)
4. Set the trigger to All Pages to track every page view

4. Configure first trigger

Without a trigger, your tag won’t know when to run. For targeted tracking, like a form submission or button click, you’ll need to:

1. Select Triggers in GTM
2. Choose a trigger type (Click, Form Submission, Page View, or Custom Event)
3. Set conditions, e.g. fire only when Click Text equals Sign Up

5. Enable built-in variables

GTM comes with built-in variables that save you from having to code data points manually. To enable these built-in variables: 

1. Go to Variables
2. Select Configure under Built-In Variables
3. Check variables like Page URL, Page Path, Click URL, or Click Text

6. Test in Preview mode

Preview mode is the best way to see whether your GTM implementation is working properly without publishing changes. To enter Preview mode, click Preview in the dashboard, enter your site URL and start the debug session, navigate to your site and see which tags successfully fire in the debug panel.

7. Publish container

Once you’re happy with how things work in Preview mode, select Submit to publish your container. You can add a Version Name and Description to help you identify changes later. Batching related changes together so your version history remains organized is recommended.

8. Verify tracking

Even after publishing, verify in GA4, or whichever platform your tag sends data to, that events and page views are being recorded correctly. This ensures your Google Tag Manager implementation is producing accurate results.

Structuring your GTM container for scalability

One of the most overlooked parts of Google Tag Manager setup is planning for growth. Many marketers rush through setting up Google Tag Manager to get tracking live as fast as possible, only to find their container becomes unmanageable after a few months. 

Without a clear structure, tags fire when they shouldn’t, and triggers become hard to track. 

A scalable GTM setup is more than just adding tags. It’s about maintaining order so that your GTM implementation can handle future campaigns, team changes, privacy-compliant data management, and analytics updates. 

This is especially important if you’re working in a team, because GTM is often a shared workspace among marketers, developers, and analysts. 

Here are some GTM best practices to keep in mind:

• Use clear naming conventions: Your GTM container may contain dozens of tags, so naming them is really important. We recommend platform (GA4, FB, etc.) > tag type or purpose (Event, Conversion, etc.) > action or description (Sign-up, Purchase, etc.)
• Organize folders: If you’re using GTM for multiple campaigns, file them separately to save time searching for specific tags. 
• Reuse triggers and variables: Creating new triggers or variables can lead to duplicates and inconsistencies. The best approach is to create general purpose triggers and variables that can be applied across multiple tags.

Best practices for tag firing and trigger configuration

Even the most carefully planned Google Tag Manager setup can fall apart if tags are firing at the wrong times or under the wrong conditions. 

Poor trigger logic is one of the most common problems in GTM implementation, and it’s often the reason analytics data looks suspicious or inflated. In this section, we’ll cover the best practices for tag firing and trigger configuration.

Be specific with triggers

Use click triggers for specific buttons or links, filtered by Click Text, Click URL or Element ID. Use Form Submission triggers that only fire on unique Form IDs and use Page View Triggers for specific page URLs or paths.

Use trigger exceptions

This enables you to define conditions when a tag does not fire and ensures you avoid double counting.

Sequence tags

If you want tags to fire in a specific order, you need to enable this in Advanced Settings. Enable Tag Sequencing and choose whether another tag fires before or after the main tag. This is especially useful during a Google Tag Manager custom event trigger setup.

Use Lookup Tables

Best practice is to have the same tag fire under different conditions with different values. Instead of creating several duplicate tags, you can use Lookup Table variables and implement them during the configuration.

Use Data Layer for triggering

While click and form triggers can work fine for simple tracking, the Data Layer is the most reliable method in advanced GTM implementation. Developers can push structured data to the Data Layer, and you can set custom event triggers to listen for those values, reducing the risk of tracking issues.

Managing environments: preview, debug, and publish

Unlike hardcoding tracking scripts directly into HTML, using Google Tag Manager gives you a safe, contained way to work in preview, debug, and publish stages.

Preview mode is the single most important testing tool when setting up Google Tag Manager. When you select Preview, your website opens in a special debug session, enabling you to see which tags fired and what exact variables and Data Layer values reached each tag.

While Preview mode gives you a real-time panel, Debug mode (also known as Tag Assistant Companion in Chrome) adds another layer, which enables you to replay tracking activity, isolate events in a timeline view, and identify variable values at the moment of firing.

This is especially useful when your Google Tag implementation involves multiple steps or dynamic page content. Finally, once your tags work perfectly in Preview and Debug modes, you can publish your GTM container.

GTM also supports multiple environments, including:

• Live (Production): the version seen by real users
• Staging: for testing in a pre-launch environment
• Development: for QA and experimentation

If you’re running a complex Google Tag Manager implementation across multiple domains or subdomains, environment-specific containers help you test changes in staging without affecting live users. 

Proper use of GTM’s preview, debug, and publish tools is the difference between guessing your tags are working and knowing they are. In the next section, we’ll build on this by covering implementing GTM across multiple domains or subdomains, where testing across environments becomes even more important.

Implementing GTM across multiple domains or subdomains

When your business spans more than one domain or operates across multiple subdomains, Google Tag Manager setup becomes more complex. A standard single-site basic Tag Manager setup works fine for many small sites, but if you’re tracking users across pages or entirely different domains, things can get tricky. 

In these scenarios, special attention to cross-domain tracking, cookie settings, and container deployment is needed to ensure you capture accurate, unified user journeys. 

When setting up Google Tag Manager for multiple domains, you have two main approaches: a single GTM container, which offers centralized control over tags, triggers and variables, and separate containers, which offer cleaner separation between sites. 

For a Google Tag Manager for beginners scenario, starting with a single container is the best option unless you’re working with very different business units. 

If you’re working with subdomains, GA4 automatically handles them as part of the same property if the cookie domain is set correctly. In GTM, this means your GA4 configuration tag can remain the same across all subdomains. This is key for using Google Tag Manager in multisite setups without mixing irrelevant data.

GTM for server-side tagging: configuration essentials

While most people start with a basic tag manager setup that runs entirely in the browser, advanced teams are increasingly moving to server-side tagging for better performance, security, and control over data.

In a traditional GTM implementation, every tag runs in the user’s browser. In server-side mode, the browser sends event data to your GTM server endpoint, which then processes the data and sends it to relevant marketing tools.

Setting up GTM for server-side tagging involves more steps than a standard web container.

1. Create a server container in your GTM account. 
2. Deploy the server container so it sends data to your server container instead of directly to Google or Meta. 
3. Reconfigure tags inside the server container to forward the data to analytics and ad platforms.

The shift to server-side Google Tag Manager implementation delivers several key advantages over traditional client-side setups.

Site performance improves because fewer scripts need to run in the visitor’s browser, leading to faster page loads and smoother user experiences. Server-side GTM gives you greater control over the data you collect and send, rather than letting every tag gather raw user information directly, which naturally supports better privacy compliance.

Another key benefit is that server-side requests are harder for ad blockers and browser privacy features to intercept, meaning you retain more accurate tracking, even as third-party cookie use declines.

While you can self-host your server-side GTM container, many marketers prefer integrated solutions that combine server hosting with built-in consent management. This approach removes the need for a development team while ensuring data quality and compliance.

Solutions like Usercentrics’ Server-Side Tagging make it possible to run a first-party GTM container on a secure server, simplifying setup while improving performance and privacy.

Common pitfalls and how to avoid them

Even the most experienced marketers and developers can run into issues during their Google Tag Manager setup. The good news is that nearly every problem can be avoided with proper planning, careful testing and structured workflows. Let’s break down the most common pitfalls and how to avoid them.

1. Publishing without testing

Skipping Preview and Debug modes opens the window for broken tracking, duplicate conversions, or missing events. Always test new tags in GTM’s Preview mode, use Debug mode to examine variable values, and click through real user flows before publishing.

2. Overloading the container with tags

A bloated GTM container can slow down your site and make management chaotic. Make sure to audit your container quarterly and remove legacy tags and triggers that no longer serve a purpose.

3. Misconfigured triggers causing over-firing

Improper trigger configuration is one of the biggest problems in Google Tag implementation. For example, if your Google Tag Manager custom event trigger setup isn’t specific enough, a conversion tag might fire multiple times.

4. Ignoring version control and documentation

Name each version descriptively, e.g. GA4 Event Tracking – Newsletter Signup, and keep a simple changelog as part of your best practices.

5. Setting up cross-domain or subdomain tracking incorrectly

When using Google Tag Manager across multiple domains or subdomains, forgetting to configure cross-domain tracking causes analytics platforms to count the same user multiple times. Plan your domain strategy during the initial account setup and confirm in testing that your GA4 client ID persists across site boundaries.

6. Relying solely on web containers instead of server-side

Consider a setup Google Tag Manager process that includes a server-side container to protect against data loss and improve performance.

7. Forgetting to update consent settings for privacy laws

In today’s compliance-focused environment, firing tags without user consent can lead to legal risks. Many teams forget to update GTM triggers to respect user choices from cookie consent banners, so ensure you build consent triggers into your GTM implementation.

8. Hardcoding tracking scripts

Mixing GTM-managed tags with hardcoded scripts makes tracking harder to manage and troubleshoot. Move all possible tags into GTM.

Avoiding these pitfalls isn’t about memorizing every Google Tag Manager basics rule; it’s about building a habit of careful planning, thorough testing and clean documentation.

Tools and extensions to enhance GTM workflows

While the Google Tag Manager setup can be done entirely within GTM’s built-in interface, using the right tools and extensions can make implementation faster and more accurate.

Here are some tools and extensions you can use:

• GTM’s built-in Preview and Debug mode: Shows which tags fired and which variables they used
• Tag Assistant Companion: Required for enabling GTM’s Preview mode on specific sites
• dataLayer Inspector+: A Chrome extension that lets you review and debug the Data Layer in real time
• GA Debugger: A Chrome extension that logs GA4 hits in the console for verification
• ObservePoint: Enterprise-level automated testing for analytics and tag deployment
• Workspace and version control: GTM’s workspaces allow different team members to work without overwriting each other’s changes, and version control lets you retain historical data

By combining these tools with disciplined testing and consistent workflows, you can turn a standard basic tag manager setup into a high-performance, error-resistant and scalable tracking environment.

Future-proof your tracking with privacy-first server-side tagging

As privacy regulations tighten and browser restrictions like Apple’s Intelligent Tracking Prevention (ITP) limit traditional tracking, the future of Google Tag Manager implementation is moving firmly toward server-side tagging.

This approach shifts data collection from the visitor’s browser to a secure server, giving you more control over what’s collected, how it’s processed, and where it’s sent.

With server-side GTM setup, your tags run in a protected environment, meaning fewer scripts are loading in the browser, faster site performance, and less interference from ad blockers.

Even better, server-side tracking lets you anonymize or filter data before passing it to third-party tools, supporting compliance with data protection laws like the GDPR and CCPA.

For marketers who want the benefits of server-side tagging without needing to hire a team of developers, Usercentrics’ Server-Side Tagging solution offers an all-in-one path forward. It combines integrated server-side GTM hosting with industry-leading consent management, helping to ensure your data collection is marketing-effective and privacy-compliant.

By hosting your Google Tag Manager container on a secure server, Usercentrics helps you:

• Improve campaign performance by sending cleaner, more accurate, and consented data to your ad tools
• Reduce costs by eliminating wasted ad spend caused by poor tracking accuracy
• Gain full control of your tracking with a first-party system
• Simplify your workflow with a solution built for marketers

If you’re serious about future-proofing your Google Tag implementation and staying compliant with privacy laws while maximizing data quality, consider server-side tagging with consent built in.

ChatGPT has quickly become a household name, with the platform’s weekly active users surging past 400 million in February 2025. 

While individuals use the large language model (LLM) for everything from drafting emails to planning dinner menus, businesses are also integrating the technology into their workflows. 

Many companies use ChatGPT Team or ChatGPT Enterprise plans, which connect them to business data to help teams work more efficiently. Others use the OpenAI API (application programming interface) to build AI-powered features like search or chatbots directly into their own products. 

In August 2025, OpenAI, the company behind ChatGPT, announced it had more than 5 million paying business users. 

If your business uses these services, you could be sharing employees’ or customers’ personal data with the platform. In those cases, ChatGPT’s privacy policy would not apply; that document applies only to personal data collected by ChatGPT from individual users. 

Instead, any personal data shared by a business is covered by the OpenAI Services Agreement and its Data Processing Addendum (DPA). 

In this guide, we look at what personal data OpenAI may collect from your business, how this data may be used, and your potential obligations under various data protection regulations.

What personal data does OpenAI collect?

OpenAI’s services agreement and DPA don’t provide a definitive list of what personal data is collected. Exhibit A of the DPA — which is used to describe categories of data that may be transferred internationally — gives the clearest indication of what OpenAI might collect.

These categories include:

• Name
• Contact information
• Demographic information
• Any other information a user provides in unstructured form

There are two types of data that may contain this information:

• Customer data refers to personal data that your business provides to OpenAI, and that OpenAI processes on your behalf to deliver services.
• Business data includes the inputs and outputs from ChatGPT Team, ChatGPT Enterprise, and the API Platform (as well as ChatGPT Edu).

This data is collected from several sources.

Account setup for Team and Enterprise users

If your business uses ChatGPT Team or Enterprise, OpenAI may collect employee information necessary to register and manage their accounts under your organization’s workspace. For example, when your company purchases Enterprise licenses, each employee is provided with their own account. OpenAI collects data such as employees’ names and email addresses.

Chats and integrations

Employees using ChatGPT Team or Enterprise might share personal data with OpenAI. This data can come directly from messages they write or from third-party software integrations. 

For example, if you connect your account to customer relationship management (CRM) software and it sends customer data into a chat, OpenAI will receive and temporarily collect that information.

API calls

Whether OpenAI collects personal data through the API depends entirely on what your product sends and receives. If users’ API inputs or the resulting outputs include personal data, OpenAI will receive and temporarily process that information. If neither the API inputs nor outputs contain personal data, OpenAI will not receive any.

How does OpenAI use personal data?

OpenAI acts as a data processor under its DPA, which means it processes customer data under your instructions and on your behalf. The DPA outlines that this processing must be handled:

• Only for the purpose of delivering and supporting its services, including analytics, reporting, trust and safety monitoring, and abuse detection
• In compliance with your documented instructions
• In a manner that provides at least the level of privacy protection required by applicable data protection laws
• If legally required beyond these purposes, after OpenAI notifies you of this requirement, unless prohibited by law

Importantly, OpenAI states that it does not use business data for model training or improvement unless you explicitly opt in.

OpenAI may process de-identified or aggregated data to improve service functionality, provided that this data cannot be linked back to individuals or used to reidentify customers. Businesses may permit or instruct OpenAI to process customer data in de-identified, anonymized, or aggregated form, subject to US privacy laws.

Organizational data, company name, industry type, or internal policies are not by themselves ordinarily considered personal data under many global data protection regulations. 

However, business data, which is defined as inputs and outputs, may include employees’ or customers’ personal data, in which case it is protected.

OpenAI may run business data through automated content classifiers and safety tools. These tools generate metadata about the content but do not contain the original business data itself.

Business data is subject to human review only under certain conditions. Access to business data is limited and depends on the service being used:

• For ChatGPT Enterprise, authorized OpenAI employees may access conversations only to resolve incidents, help recover user conversations with your explicit permission, or where required by law
• For ChatGPT Team and OpenAI API, access is restricted to specific scenarios:
  • OpenAI employees may access stored data for engineering support, to investigate potential abuse, or for legal compliance
  • In some cases, third-party contractors — who are subject to confidentiality and security obligations — may review conversations to identify misuse or abuse

Does ChatGPT save user data?

Yes, OpenAI saves user data, but for how long and under what conditions depends on the specific service being used and whether it is customer data or business data.

OpenAI API

Business data is retained for a maximum of 30 days for abuse monitoring before being deleted, unless legal obligations require more time. Businesses with a qualifying use case can also request zero data retention (ZDR) for eligible API endpoints.

Customer data is retained for the duration of your service agreement.

ChatGPT Enterprise

Your workspace administrators control how long business data or conversation history is retained. Any business data in deleted conversations will be removed from OpenAI’s systems within 30 days, unless retention is legally required.

Customer data is retained for the duration of your service agreement.

The DPA states that OpenAI may continue to process de‑identified, anonymized, or aggregated versions of customer data after it’s no longer considered personal data under applicable laws and if it cannot identify individuals.

ChatGPT Team

Individual end users control how long conversation history is retained by choosing whether or not to save their chats. Any business data in conversations that are deleted or unsaved will be removed from OpenAI’s systems within 30 days, unless retention is legally required.

Customer data is retained for the duration of your service agreement.

As with Enterprise, the DPA states that OpenAI may continue to process de‑identified, anonymized, or aggregated versions of customer data after it’s no longer considered personal data under applicable laws and cannot identify individuals.

Who does OpenAI share personal data with?

OpenAI may share personal data with third-party sub-processors to support the delivery and operation of its business services. According to the DPA, these sub-processors may carry out specific processing activities on OpenAI’s behalf or to help the company fulfill its contractual obligations to customers.

These sub-processors support several functions, including:

• Cloud infrastructure: Providers that supply the servers, storage, and computing resources OpenAI uses to host and operate its services
• Data warehousing: Services that store and manage large volumes of structured or unstructured data to support processing, retrieval, and analytics
• Customer support: Companies that help respond to user questions, resolve technical issues, and assist with account or service-related inquiries.
• Content moderation: Vendors that review and filter content to meet safety, legal, or policy standards
• User authentication: Services that verify user identities to manage secure access and protect accounts

According to the OpenAI Law Enforcement User Data Request Policy, OpenAI may also be required to disclose personal data to law enforcement authorities in response to a legally binding request. In those cases, OpenAI must notify the business unless it is legally prohibited from doing so. OpenAI states that it does not initiate such disclosures and shares data only when required in order to comply with legal obligations.

Additionally, certain OpenAI group entities may access customer data while providing technical or operational support. These affiliate companies are based in the United States, Ireland, the United Kingdom, and Japan.

Are you required to have a privacy policy when using ChatGPT Team, Enterprise, or OpenAI API?

While OpenAI’s terms do not directly state that you must have a privacy policy, you do need one to fulfill contractual requirements and legal obligations.

The OpenAI Service Agreement requires your business to obtain and maintain all necessary consents from your end users to allow OpenAI to provide services. Fulfilling this requirement means you are responsible for making the disclosures needed to obtain consent. That includes informing users how their personal data will be handled, both by your organization and by OpenAI.

Further, the DPA requires you to comply with applicable data protection laws, many of which mandate that businesses publish a privacy policy. Most also include an obligation of transparency, which requires you to inform users about your data practices in a way that is easy to understand. You can do this through a clear, accessible privacy policy that’s prominently linked, e.g. from your website footer or app menu.

How to align your privacy policy with data protection laws and OpenAI’s privacy practices

If your business uses ChatGPT Team, Enterprise, or the OpenAI API, your privacy policy must explain how those uses affect your employees’ or customers’ personal data. 

Below is a non-exhaustive checklist of what to include in a privacy policy.

• Describe what personal data your business collects and uses, how it shares that data with OpenAI, and for what purposes. Note that OpenAI may use the data according to the DPA.
• Disclose that personal data sent to OpenAI may be shared with third parties, such as its sub-processors and affiliate companies.
• Summarize the rights users have under applicable data privacy laws and how they can exercise those rights.
• Explain OpenAI’s policies on data retention, including how long personal data is stored and the conditions under which it is deleted.
• Provide contact details for users who have questions or concerns about your data practices. If you have a Data Protection Officer (DPO) or another designated privacy contact, include their information.

Your privacy policy must be written in simple, clear language that is easy to understand. It should be easily accessible, such as through a link in your website’s footer or within your application’s menu.

Finally, keep your privacy policy up to date. You are responsible for keeping it current and reflective of any changes to your data practices, OpenAI’s terms, or applicable privacy laws.

Usercentrics does not provide legal advice, and information is provided for educational purposes only. We always recommend engaging qualified legal counsel or privacy specialists regarding data privacy and protection issues and operations.

You’ve probably felt it: the data you rely on for campaign optimization is becoming less reliable. Client-side tracking, which has powered digital marketing for over a decade, faces increasing limitations from browser restrictions, privacy regulations, and ad-blocking software.

At the same time, businesses need more accurate attribution data to optimize their marketing spend effectively. Server-to-server tracking provides a solution by moving data collection from the user’s browser to your own infrastructure.

This approach gives you direct control over how customer data flows to advertising platforms and analytics tools. You don’t have to hope that browser-based scripts work correctly, because you manage the entire data pipeline yourself.

What is server-to-server (S2S) tracking?

Server-to-server tracking (S2S), also known as server-side tracking, is a method of data collection in which your server communicates directly with third-party platforms like Google Analytics, Facebook, or advertising networks. Instead of relying on JavaScript code running in the user’s browser, your backend system handles the data transmission.

Rather than asking the user’s browser to tell Facebook about a purchase, your server tells Facebook directly. The user’s device doesn’t need to load multiple tracking scripts or make dozens of requests to different advertising platforms.

“You’re firmly in control with server-to-server tracking. Your systems speak directly to platforms like Google or Facebook, without relying on the user’s browser. You choose exactly what information is shared, when it’s sent, and who receives it.”

Adelina Peltea

— CMO of Usercentrics

What is server-to-server tracking in Google Tag Manager?

Google Tag Manager introduced server-side tagging to address the limitations of traditional client-side implementations. This core feature essentially enables you to run a version of Google Tag Manager on your own server infrastructure, rather than just in the user’s browser. It’s worth noting that this capability is not enabled by default.

It works by sending your website data to a server-side Google Tag Manager container that you control. This container processes the data according to your rules and then forwards relevant information to your chosen platforms, like Google Analytics, Google Ads, or third-party tools.

The server-side container runs either on Google Cloud Platform or your own infrastructure. It receives HTTP requests from your website, processes them through your configured tags and triggers, and sends the resulting data to destination platforms via their application programming interfaces (APIs).

S2S tracking vs. client-side tracking

The main difference between server-side and client-side tracking is where data processing happens and who controls the flow of information.

Let’s compare the two further.

What are the uses of server-to-server (S2S) tracking?

Server-to-server tracking is becoming essential for modern marketers, developers, and data teams. By sending data directly from your backend systems, S2S tracking makes your customer insights more accurate, more reliable, and more powerful. 

Here’s how it works across different use cases.

Ad platforms integration

Platforms like Facebook (through the Conversions API) and Google Ads (via Enhanced Conversions) use server-to-server data to improve conversion tracking. Instead of relying on browser-based pixels that can fail or get blocked, your server sends the data directly to the platform.

Server-to-server conversion tracking means more accurate attribution, more reliable reporting, and ultimately, better ad performance.

Affiliate marketing measurement

Affiliate programs also benefit from server-to-server tracking because it eliminates disputes over conversion attribution. By having your server directly transmit conversion events to affiliate networks, you remove ambiguity about whether a conversion was properly tracked.

Traditional affiliate tracking, which relies on browser redirects and tracking cookies, can be unreliable. With server-to-server tracking, your system tells the affiliate network exactly when and where a conversion happens.

Mobile app attribution

App store restrictions and device limitations have always made mobile attribution challenging. Server-to-server tracking enables mobile marketing platforms to receive conversion data directly from your app’s backend.

This approach works particularly well for in-app purchases and subscription conversions. S2S tracking can help to ensure accurate attribution, regardless of the user’s device settings or network conditions.

Advanced analytics pipelines

Server-to-server tracking is particularly useful if you’re managing complex data flows across teams and platforms. It enables you to build sophisticated data pipelines that transform and route customer data to different destinations based on your specific requirements.

You can route raw events to your data warehouse, send refined conversion data to your ad tools, and push curated metrics to business intelligence dashboards from one trusted source.

“Moving tracking to the server isn’t just a tech tweak — it’s a smarter way to run marketing. You get cleaner, more reliable data, full control over what’s shared, and the clarity to spend budget where it truly delivers.”

Adelina Peltea

— CMO of Usercentrics

Benefits of server-to-server tracking

Moving tracking to the server side is both a technical and a strategic upgrade. Whether you’re scaling performance marketing or simplifying data compliance, server-to-server tracking provides valuable benefits: 

• Improved data accuracy: Your conversion data becomes more complete when it doesn’t depend on browser behavior. When users close tabs quickly, have slow internet connections, or use ad blockers, they won’t create gaps in your attribution data.
• Increased data control: You decide exactly what information gets sent to each platform. Want to send conversion data to Google Ads but exclude personally identifiable information? Your server-side setup can transform data before transmission.

Cost optimization: Better attribution data leads to smarter budget allocation across marketing channels. When you can accurately track which campaigns drive conversions, you stop wasting money on underperforming audiences.

Server-to-server tracking and global privacy regulations

Server-to-server tracking gives you granular control over consent implementation. That matters, as privacy regulations like the General Data Protection Regulation (GDPR) in the EU and the California Privacy Rights Act (CPRA) require explicit consent for data processing. 

When a user opts out of marketing cookies, your server must immediately stop sending their data to advertising platforms. You don’t need to wait for browser-side consent management platforms to update dozens of tracking scripts.

When you control the transmission process, it also makes data minimization easier. Instead of sending all available data points, you can filter information based on your privacy policy requirements and user consent levels.

Cross-border data transfers also become more manageable. Your server can keep European user data within EU boundaries while still enabling marketing measurement and optimization.

“Server-to-server tracking helps make it far simpler to meet the requirements of global privacy laws. Since you control exactly what data is sent and when, and where it’s stored, consent can be honored instantly, data stays where it needs to, and privacy compliance and smart marketing don’t get in each other’s way — they work together.”

Adelina Peltea

— CMO of Usercentrics

How does server-to-server tracking work?

Let’s look at how the S2S process works.

1. A user interacts with your website or application

When someone interacts with your website or app, such as by making a purchase or submitting a form, your frontend doesn’t rely on third-party scripts in their browser. Instead, it sends that event data directly to your server.

2. Your server receives this event data

Once your server receives the event, it processes the data based on your business logic. This processing step is where the power of server-to-server tracking becomes clear. You can:

• Validate incoming data
• Apply privacy preferences
• Check user consent preferences
• Format and transform the data for specific destinations

This step gives you full control over how the data is handled moving forward.

3. Your server communicates with third parties

After processing, your server sends the refined data to third-party platforms like Google Analytics, Facebook (via Conversions API), or your own data warehouse, all via direct API calls. Each platform only receives what you decide to send, and in the right format.

The entire process typically takes just milliseconds and doesn’t depend on the user’s browser capabilities, internet connection speed, or privacy settings.

How to set up server-to-server tracking?

There’s no one-size-fits-all S2S setup. Some teams build everything from scratch, others rely on ready-made platforms. Most businesses choose a mix of both, combining custom development with proven infrastructure to get the best of both worlds.

1. Start with a plan

Begin by auditing your current tracking setup. What events are you capturing? Where does that data go? Map your customer journey and highlight the conversion points that matter most. These are the events that you need to track accurately and consistently.

Then, choose how you’ll build your solution. A fully custom setup gives you full control, but it takes time and resources. Tools like Google Tag Manager’s server-side container or the Usercentrics server-side tracking solution can speed up the process without sacrificing flexibility.

2. Set up your technical foundation

Create server endpoints that can receive event data from your website or app. These endpoints should handle:

• Authentication
• Data validation
• Logging for any errors or failed requests

Next, connect your server to the platforms where the data needs to go. That means setting up API credentials, learning what each platform expects, and making sure you have solid error handling in place.

3. Use server-side tagging platforms to simplify setup

Server-side tagging platforms, like Usercentrics’ solution, handle much of the technical complexity for you. Your developers will not need to write a single line of code. Instead, you’ll have a visual interface where you can define data flows, set consent rules, and map events to their destinations. Making it easy to use while saving you time and resources.

Our tool comes with pre-built templates for GA4, Google Ads, Meta (CAPI), and more. So you can quickly get started. But if you have any questions along the way, our detailed documentation will guide you through the installation process.

4. Test, monitor, and validate

No matter how you implement your tracking setup, you’ll need to test it. Compare your new server-side tracking with your existing browser-based system to spot any gaps. Monitor response times, error rates, and delivery success to verify that your data is flowing as expected.

Drawbacks of using S2S tracking

Server-to-server tracking offers major advantages, but it’s not plug-and-play. There are some trade-offs you should be aware of before making the switch.

• Implementation complexity: Unlike dropping a client-side script into your site, S2S tracking requires real infrastructure. You’ll need server environments, API connections, and the ability to monitor and maintain tracking.
• Development resources: Building and maintaining a server-side setup takes time. Your developers will need to handle the initial integration as well as future updates.
• Attribution challenges: Some ad platforms still rely on browser-based signals to model attribution. With S2S, you might lose some of that detail, especially around view-through conversions or multi-touch journeys.
• Cookie limitations: S2S helps bypass many browser limitations, but it’s not a total replacement. For user identification, personalization, or cross-site tracking, client-side components may still be necessary.
• Cost considerations: With custom infrastructure comes added cost. It’s an investment, especially compared to simpler client-side tools.

Is server-to-server tracking right for me?

Server-to-server conversion tracking offers powerful benefits, but it’s not the right fit for every business. Whether or not to invest depends on your current challenges, technical resources, and the role data plays in your marketing strategy.

When S2S tracking makes sense

If your website performance is suffering from heavy client-side tracking or if you’re seeing major attribution gaps due to ad blockers, S2S tracking can provide a more reliable alternative. 

It’s also a strong choice if you need detailed control over what data is shared for privacy compliance purposes, or if marketing performance is a key growth lever and attribution accuracy impacts your bottom line. 

You also need to have the technical resources to manage implementation and maintenance.

When it might not be the right time for S2S tracking

On the other hand, if your current tracking setup is delivering reliable data, you may not need to make the switch. Businesses with limited development capacity or smaller marketing budgets may find the investment harder to justify. 

Similarly, if browser restrictions aren’t significantly impacting your data quality, a client-side solution might still be sufficient.

The decision comes down to cost vs. value. For teams that rely on precise, consistent data to drive revenue, S2S tracking can offer a competitive edge. For others, it may be a future consideration rather than an immediate priority.

“Server-to-server tracking is a powerful upgrade, but it’s not a race. Make the move when the value clearly outweighs the cost. If your current setup is working well and resources are tight, it can stay on the roadmap for when precision data becomes business-critical.”

Adelina Peltea

— CMO of Usercentrics

Moving beyond browser limitations

Server-to-server tracking represents a shift toward more sustainable marketing measurement. As privacy regulations evolve and browsers increasingly restrict tracking capabilities, businesses need measurement approaches that don’t solely depend on client-side scripts.

The transition may require upfront investment or technical setup. However, the long-term benefits of reliable data collection, improved page performance, and better privacy compliance often justify the investment.

The way you collect customer data directly impacts your bottom line. Whether you’re dealing with declining attribution windows, rising ad costs, or privacy compliance headaches, your tracking setup is probably costing you money.

Browser restrictions are tightening, privacy regulations are expanding, and traditional tracking methods are becoming less reliable by the day. That’s why many businesses are switching from client-side to server-side tracking.

This chapter can help you make that decision. We break down everything you need to know about both approaches and when to use each.

What is client-side tracking?

Client-side tracking involves collecting data directly from your visitor’s browser. When someone lands on your website, JavaScript code executes on their device to record their behavior and send that information to your analytics platforms.

This approach relies on cookies stored in the user’s browser to identify returning visitors and track their journey across sessions. Popular tools like Google Analytics, Facebook Pixel, and most marketing automation platforms use client-side tracking by default.

Here’s how the process works. A visitor loads your web page, tracking scripts fire in their browser, your tags or software development kits (SDKs) collect data about their actions, and your analytics tools receive that information in real time.

Client-side tracking became the standard because it’s relatively simple to implement. Just add a few lines of JavaScript to your website, and data starts flowing immediately. Most marketing teams can set this up without a lot of need for development resources.

Despite the simplicity, client-side tracking comes with growing limitations. Browser restrictions, privacy settings, and ad blockers can prevent client-side scripts from loading or functioning properly.

What is server-side tracking?

Server-side tracking moves data collection from the user’s browser to your own servers. Instead of relying on JavaScript codes running on your visitors’ devices, your website sends data to your servers, which then process and forward relevant information to your marketing platforms.

You can imagine it as a central data hub that receives information from your website and distributes it to the tools that need it. Your server acts as an intermediary, controlling what data gets shared with which platforms.

When someone interacts with your website, their browser sends basic interaction data to your server. Your server then enriches the data, applies privacy controls, and forwards it to Google Analytics, your customer data platform, or other tools in your marketing stack.

Server-side tracking gives you more control over your data flow. You decide what information gets shared with third-party platforms, when it’s shared, and in what format. You can also apply consent preferences at the server level so that data only flows to approved tools.

Server-side tracking does require more initial setup than client-side tracking. You need server infrastructure to handle data processing and application programming interfaces (APIs) to connect with your marketing platforms. But once implemented, it often provides more reliable data collection and stronger privacy compliance.

Server-side vs. client-side tracking: What’s the difference?

The main difference between server-side and client-side tracking lies in where data processing happens and who controls the flow of information.

Here are the more granular differences:

Where client-side tracking excels is in its simplicity and immediate implementation. You can have basic tracking running within minutes just by adding code to your website. It’s also cost-effective for smaller businesses that don’t have dedicated technical resources.

Server-side tracking shines when you’re prioritizing control, compliance, and reliability. It’s particularly valuable for companies dealing with strict privacy regulations or those experiencing data quality issues with traditional tracking methods.

When to use server-side vs client-side tracking?

The choice between client vs server-side tracking depends on your business needs, technical resources, and compliance requirements.

Choose client-side tracking when:

• You’re a smaller business with limited technical resources. Client-side tracking gets you up and running quickly without requiring server infrastructure or dedicated developers.
• Your website traffic is primarily from regions with less stringent privacy laws. If most of your visitors aren’t subject to the EU’s General Data Protection Regulation (GDPR) or similar regulations, client-side tracking may provide sufficient data quality.
• You need immediate implementation. Client-side tracking can be deployed within hours, so it’s ideal when you need to start collecting data quickly.
• Your marketing budget is tight. The lower upfront costs of client-side tracking make it accessible for businesses with limited resources.

Choose server-side tracking when:

• You lack control over tracking data sent to third parties.
• Your marketing performance is declining due to data quality issues. If ad blockers, browser restrictions, or iOS updates are affecting your attribution models, server-side tracking provides more reliable data collection.
• You operate in heavily regulated industries or serve customers in privacy-focused regions. Server-side tracking makes compliance with laws like the GDPR or the California Privacy Rights Act (CPRA) more manageable.
• Your website performance is suffering from multiple tracking scripts. Server-side tracking can significantly improve page load speeds by reducing the number of third-party scripts that execute in the browser.
• You have the technical resources to implement and maintain server infrastructure. Server-side tracking requires ongoing technical support, but also provides more long-term benefits.
• Your business operates at scale. High-traffic websites and complex customer journeys benefit more from server-side approaches because the improvements to performance and data consistency become more valuable.

Why are more companies switching over to server-side tracking?

The shift toward server-side tracking might seem like a trend. It’s really a response to numerous recent changes in how browsers handle data collection and how privacy regulations shape business practices.

Browser restrictions are tightening every year. For instance, Apple’s Safari and Mozilla’s Firefox now limit traditional tracking methods. These changes directly impact marketing attribution and campaign optimization.

Companies are seeing their marketing performance metrics decline not because their campaigns are less effective, but because they’re collecting less data. Attribution windows are shrinking, conversion tracking is becoming less accurate, and audience building is getting more difficult.

Performance benefits drive adoption

Every third-party tracking script you add to your site increases page load time. That’s worth considering, because website speed directly affects conversion rates and search rankings. Server-side tracking consolidates data collection, which can improve Core Web Vitals scores and user experience.

Data quality improvements matter

Ad blockers now affect roughly 30 percent of web traffic in many markets. iOS updates continue to limit tracking capabilities, and browser restrictions on tracking cookies impact attribution accuracy. Server-side tracking bypasses many of these limitations and provides more complete data for marketing optimization.

Compliance becomes a competitive advantage

Of course, you need to avoid GDPR penalties and California Consumer Privacy Act (CCPA) fines. But privacy compliance is also becoming a competitive differentiator. Companies that can demonstrate responsible data handling build more trust with customers and partners.

Server-side tracking makes privacy compliance audits easier because all data flows through your controlled infrastructure. You can implement consent preferences consistently across all marketing tools and provide clear audit trails for regulatory reviews.

Server-side tracking and global privacy laws

Privacy regulations are reshaping how businesses are able to collect and use customer data. The GDPR and a number of other international privacy regulations require explicit consent for most marketing activities. US state-level privacy laws give residents the right to know what data you collect, how you use it, and the ability to opt out.

When someone opts out of advertising cookies, your server can immediately stop sending their data to advertising platforms while continuing to send anonymized analytics data to Google Analytics. This level of granular control is difficult to achieve with client-side tracking.

The regulatory landscape will only get more complex, and will increasingly include government regulation, industry-specific laws, and policy requirements by influential tech platforms like Google. 

Server-side tracking provides a foundation to help you adapt to new rules without requiring complete overhauls of your data collection strategy.

Can client-side and server-side tracking work together?

You don’t have to pick just one approach. Many companies use both methods to get the benefits of immediate browser-based data collection and controlled server-side processing.

In a hybrid setup, server-side tracking typically handles core data collection and privacy compliance, while client-side tracking manages specific use cases that need instant browser processing.

Here are some reasons you might opt for a hybrid model.

Real-time personalization requires client-side speed

If you’re showing personalized content based on user behavior, client-side tracking provides the immediate data you need. Server-side processing has slight delays that can affect on-page personalization.

Progressive migration reduces risk

You can gradually move from client-side to server-side tracking without disrupting your current campaigns. Start by moving your most important data flows server-side while keeping existing client-side tracking for less critical tools.

Different tools have different preferences

Some marketing platforms work better with direct browser data, while others are more effective with server-side integration. For instance, Facebook’s Conversions API works great server-side, but some personalization tools still need client-side data.

The challenge with hybrid approaches is avoiding data duplication and managing consent across both tracking methods. Your teams will need clear documentation about which system handles which data points.

Using client-side and server-side tracking to collect data

Your tracking setup directly affects marketing performance, compliance costs, and website speed. The choice between server-side and client-side tracking goes beyond technical preference. Instead, it’s a strategic move.

Client-side tracking works well for simple implementations and immediate needs. Server-side tracking provides better data quality, privacy compliance, and long-term reliability. Hybrid approaches can combine the benefits of both, though they require careful management.

The key is matching your tracking approach to your business needs and resources. Start where you are, plan for where you’re going, and implement changes that provide clear returns.

The way we track user behavior online is changing rapidly. Third-party cookies are disappearing, ad blockers are becoming more sophisticated, and privacy regulations are growing increasingly strict.

If you’re part of a marketing team, you’ve probably felt the pressure. Maybe your tracking isn’t as accurate as it used to be, your conversion data has gaps, or your attribution models are breaking down.

Server-side tracking promises to solve these problems. But is it better than traditional cookie-based tracking? And which approach should you be using for your business?

We’ll walk through both methods, compare their strengths and weaknesses, and help you decide which tracking strategy best suits your needs.

Why tracking matters: the basics of tracking and cookies

Web tracking is the foundation of data-driven marketing. Every interaction and customer touchpoint generates data that informs your campaigns, budget, and strategy.

Traditional tracking infrastructure relies primarily on cookies, which are small text files stored in users’ browsers, and that maintain session data and behavioral information across site visits. 

These cookies enable attribution modeling, audience segmentation, and conversion tracking that marketers depend on for performance measurement.

This tracking method faces increasing limitations that directly impact campaign measurement and attribution accuracy, so it’s important to understand how cookies function.

First-party vs. third-party cookies

Cookies don’t all work the same way. First-party cookies are created by your website and stored on the user’s device. They help with basic functionality like keeping users logged in or remembering their preferences.

Third-party cookies are created by external services, like advertising networks, and track users across multiple websites. These cookies have attracted the most privacy scrutiny and are being phased out by browsers.

The distinction between the two matters because they affect how your tracking works and what data you can collect.

How does traditional cookie-based tracking work?

Traditional client-side cookie-based tracking happens directly in the user’s browser. When someone visits your website, JavaScript code executes in their browser, drops cookies, and sends data to your analytics platforms.

Here’s what typically happens once a user lands on your product page. Your Google Analytics code fires. A cookie then gets set in their browser with a unique identifier. When the user visits other pages or completes actions, that same identifier tracks their journey.

The process feels seamless, but it depends entirely on the user’s browser cooperating. Their browser needs to accept cookies, run JavaScript, and allow data to be sent to third-party services.

How cookies store and collect data

Cookies store data as key-value pairs directly on the user’s device. The stored data might include their unique visitor ID, the source of their visit, their previous page views, or items in their shopping cart.

Every time the user interacts with your site, their browser reads these cookies and uses that information to maintain context. It’s like having a conversation where each party remembers what was said before.

The data collection happens automatically through JavaScript tags embedded in your website. These tags fire when specific conditions are met, such as a page loading, when a button gets clicked, or when a form is submitted.

Limitations of tracking cookies

Traditional cookie-based tracking faces an increasing number of challenges that directly impact data quality and, consequently, your marketing strategies. These limitations have grown more pronounced as privacy awareness increases and various browser technologies develop.

Browser restrictions

Multiple browsers have taken action against third-party cookies. For example, Apple’s Safari now blocks all third-party cookies by default and limits some forms of first-party storage through Intelligent Tracking Prevention (ITP), making cross-site tracking virtually impossible. 

Mozilla’s Firefox enforces “Total Cookie Protection,” which partitions cookies, so third parties can’t track users across different sites. 

Google’s Chrome, after announcing and then delaying it, has not phased out third-party cookies and no longer plans to. Instead, users are given privacy controls to manage their cookie preferences.

No matter the browser, when cookies get blocked, attribution models break and conversion tracking becomes incomplete.

Ad blocker interference

Ad blockers actively prevent tracking scripts from loading, rendering significant portions of your website traffic invisible to analytics platforms. 

As adoption of ad blockers continues to rise across age groups and regions, the gap in measurable user behavior widens. That gap makes it increasingly difficult to get a complete view of your audience.

Data reliability issues

Cookie data suffers from inherent reliability problems. Users regularly delete cookies, browse in incognito mode, or switch between devices. Each action creates attribution gaps that lead to incomplete customer journey analysis and inaccurate campaign measurement.

Compliance complexity

Privacy regulations like the EU’s General Data Protection Regulation (GDPR) require explicit consent for non-essential cookies, and US state-level privacy laws require enabling users to opt out of data collection. 

Users who decline consent disappear from your tracking entirely, which creates systematic bias in your data that affects strategic decisions.

What is server-side tracking?

Server-side tracking fundamentally changes where data processing happens. Instead of relying on JavaScript and cookies in the user’s browser, data collection and processing move to your server infrastructure.

Think of it as changing the conversation. With traditional tracking, the user’s browser talks directly to Google Analytics, Facebook Pixel, and other platforms. Server-side tracking puts your server in the middle. It collects data from user interactions, processes and enriches that data, then forwards it to your marketing platforms on your behalf.

This shift gives you more control over data collection, reduces your dependence on user browser settings, and provides more consistent data quality regardless of external factors.

How does server-side tracking work?

When a user visits your website, basic interaction data is still collected in their browser. But instead of sending this data directly to multiple third-party services, it gets sent to your server first.

The enrichment process provides additional context, like server-side user identification or purchase history, and the forwarding to analytics and advertising platforms is more controlled — by you — based on information like user consent preferences.

How does server-side tracking store and collect data?

Server-side tracking can rely on multiple data storage methods. First-party cookies still play a role, but they’re supplemented by server-side storage, databases, and user account information.

Data collection becomes more sophisticated with server-side tracking. Your server can combine behavioral data with customer database records, purchase history, and other business contexts that aren’t available client-side.

Instead of relying solely on browser-based identifiers, you can use more stable identifiers like customer IDs, email addresses (when users are logged in), or proprietary tracking methods.

Server-side tracking vs cookies: key differences compared

Whether you use server-side tracking or cookies affects the quality of your data, your ability to comply with privacy regulations, and your long-term tracking strategy.

Here are the key differences between these methods.

Why businesses are moving to server-side

The shift toward server-side tracking helps solve technical problems, but it’s also a response to a changing environment where traditional tracking methods are becoming less reliable.

Privacy regulations continue to expand. Browsers are restricting tracking capabilities. Users are becoming more privacy-conscious. As a result, they’re adopting tools that block traditional tracking.

Businesses need tracking solutions that work regardless of external factors. Server-side tracking provides that stability.

Benefits of server-side tracking

Server-side tracking addresses the core limitations of traditional cookie-based methods while providing additional advantages for data-driven marketing operations.

Better data accuracy and completeness

Server-side tracking bypasses browser restrictions and ad blockers that cause data loss in traditional setups. You can capture user interactions regardless of browser settings, privacy tools, or device switching.

This completeness matters for attribution accuracy. If you’re missing 20–30 percent of your traffic data due to browser restrictions, your attribution models will make decisions based on incomplete information. 

Server-side tracking can fill these gaps, giving you a more reliable foundation for campaign optimization and budget allocation decisions.

Improved privacy compliance control

You gain granular control over data collection and sharing. Consent management becomes more precise, and you can determine exactly what data gets sent to which platforms based on specific user preferences. Complying with the GDPR and other privacy regulations then becomes more straightforward.

Better data security and governance

Instead of being exposed to multiple third-party services in users’ browsers, data travels through your controlled infrastructure. This reduces data exposure points and gives you better oversight of how customer information is handled throughout your marketing stack.

Which tracking method should I use?

The choice between server-side tracking and cookies isn’t always obvious. Many successful implementations combine both methods strategically, leveraging the strengths of each approach where they provide the most value.

Your decision depends on several factors that determine both the feasibility and potential impact of server-side implementation.

• Business size and maturity: Smaller businesses with limited technical resources might benefit from a gradual approach, starting with traditional cookie-based tracking and introducing server-side elements as they grow. However, larger enterprises with dedicated technical teams can implement server-side tracking tools that provide better data quality and compliance control from the start.
• Compliance needs: If you operate in heavily regulated industries or serve users in regions with strict privacy laws, server-side tracking offers better control over data handling and sharing with third parties.
• Tech resources: Server-side tracking requires ongoing technical maintenance, server infrastructure, and specialized knowledge that may not be initially accessible to every team.

Consider starting with server-side tracking for your most critical data collection. For example, you could prioritize revenue tracking, conversion measurement, and primary KPI monitoring while maintaining client-side tracking for less essential metrics. This hybrid approach lets you gain experience with server-side methods while maintaining data continuity during the transition.

Server-side tracking: the future in a cookieless world

The decline of third-party cookies and rising privacy demands have introduced challenges for traditional tracking methods. Server-side tracking offers a more reliable and privacy-friendly way to collect data. It doesn’t replace cookies entirely, but it reduces dependence on them by shifting control to your servers.

To get started, focus on your key metrics where improved accuracy matters most, like revenue and conversions. Meanwhile, keep client-side tracking for less critical data to maintain continuity.

It’s easier than ever to make a purchase online. With a few clicks, you can add purchases to your cart, check out — even faster if you’ve saved your credit card details — and transaction complete.

Online payment processors power that experience for everything from shoe shopping to SaaS subscriptions. Stripe ranks second globally in market share, holding around 20.6 percent of the market as of April 2025. 

For businesses, Stripe does more than process payments. The company also supports terminal transactions, invoicing, identity verification, card programs, and other services for businesses across industries.

If you’re a Stripe Business User — meaning you use Stripe’s services for your business — you’re sharing data with Stripe about your customers. In some cases, Stripe will also share data with you.

Stripe’s privacy policy governs what happens to the personal data you share, including how the platform uses it and shares it with third parties.

We look at what data Stripe collects, how it uses this data, and what steps you need to take to meet your legal obligations and be transparent with your customers.

What data does Stripe collect?

When your business uses Stripe, the platform collects customer data to process payments, prevent fraud, and meet regulatory requirements.

Transaction data

Stripe collects payment data from your customers during online or in-person transactions. This may include:

• Name and contact details, such as email addresses, phone numbers, and billing/shipping addresses
• Payment method details, such as credit/debit card numbers, bank account info, or card images
• Purchase amounts and transaction dates
• In some cases, information about what was purchased

Importantly, Stripe can begin collecting data before the customer clicks “Pay.” Stripe may collect information that customers type into your business’s checkout form even if the customer leaves the page without completing the purchase.

Identity and verification information

Beyond standard payments, Stripe offers identity and fraud prevention services. If you use these services to verify a customer’s identity, Stripe collects some information directly from your customer. This may include:

• Government-issued ID

• Selfie for biometric verification

• Personal data visible on physical payment methods, such as a credit card image

This level of data collection is not standard for every Stripe transaction and only applies if you use identity verification services. This may constitute collection of sensitive personal data, which brings added legal obligations under laws like the GDPR.

Stripe may also cross-check this data with other sources, such as public records, identity verification services, financial institutions, and previously collected data from other Stripe Business Users.

Online activity

Stripe collects technical details about a customer’s device, browser, and online actions when that customer uses Stripe on your website or app.

These details may include:

• Device and browser details including IP address, language settings, plug ins
• Browsing behavior like pages visited, time spent, referring URLs, link clicks
• Activity signals such as mouse movements or other engagement cues
• Payment methods used

This data collection happens through the Stripe scripts (like Stripe.js) and mobile software development kits (SDKs) that you install on your website or integrate into your app.

While this collection is standard on your checkout page, you might also use these scripts on other website pages or app screens for purposes like advanced fraud detection.

How does Stripe use personal data?

Stripe uses personal data in the following ways to deliver its services to Business Users and, where permitted, for its own operational, security, legal, and marketing purposes.

Payment processing and accounting

Stripe uses transaction data to process online payments, calculate taxes, handle invoices and disputes, and to support Business Users with revenue tracking and accounting tasks.

Financial services

For Business Users offering financial products through Stripe, such as branded payment cards, Stripe collects and uses personal data to provide and manage those products. This includes to prevent misuse or fraud.

Identity verification

Stripe uses identity-related personal data to verify users, prevent fraud, and improve security. Verification may involve:

• Comparing selfies with ID documents using biometric tools
• Verifying phone numbers via carrier data

Fraud detection and prevention

Stripe collects and analyzes personal data to identify potentially fraudulent or harmful activity across its services. It also seeks to secure both personal data and funds against unauthorized access, use, alteration, or misappropriation.

Efforts include:

• Reviewing attempted transactions
• Using data obtained from you, your customers, public sources, and credit bureaus
• Receiving identifying information like IP addresses from third parties to assess risk

Compliance with legal obligations

Stripe uses personal data to fulfil its contractual and legal obligations regarding anti-money laundering, Know Your Customer (KYC) laws, anti-terrorism activities, export control, and trade restriction requirements. They may monitor transactions and “other online signals“ to detect and identify potential money laundering or other illegal activity.

Analyzing, improving, and developing services

Stripe uses personal data across its platform to improve and develop services and user experience. This use includes:

• Tracking usage and diagnosing issues through analytics and cookies
• Generating aggregate and statistical information to evaluate how people use their services
• Training AI models to prevent fraud and power its services
• Analyzing transaction data to reduce disputes and improve approval rates

Communications

Stripe uses contact information to:

• Send service-related communications, such as authentication codes via SMS
• Provide updates about services and invite users to events, surveys, or user research
• Follow up after service inquiries or event participation
• Record calls, where legally permitted, for quality assurance, research, or compliance

Social media and promotions

If users participate in promotions or offers, Stripe may use the personal data they provide — as well as any publicly available information — to manage those promotions or offers and for marketing purposes.

Who does Stripe share personal data with?

Stripe shares personal data with a range of recipients to deliver services and fulfill legal, operational, and business requirements.

Third parties that Stripe shares data with include:

• Business Users and their authorized partners: You, the Business User, and any third-party services you explicitly authorize to access customer data
• Financial partners: Financial institutions that receive data to support services offered through Stripe, such as financing or payment products
• App Marketplace developers: Third-party developers who receive business data through Stripe when you install a Marketplace app and authorize sharing
• Stripe affiliates: Other entities within the Stripe group that receive data for purposes outlined in Stripe’s privacy policy
• Service providers: External vendors Stripe relies on for cloud infrastructure, analytics, security, identity verification, customer support, and auditing
• Referral partners (with consent): Third-party service providers that Stripe refers users to with prior consent
• Corporate transaction participants: Third parties involved in mergers, acquisitions, or other business restructuring transactions
• Legal and regulatory authorities: Courts, law enforcement, and government agencies that request data under applicable laws

Does Stripe sell personal data?

Under many US privacy laws, the terms “sell” or “share” have a broad legal definition. They don’t just mean exchanging data for money. They can also apply to providing data to partners, like advertising networks, in exchange for valuable services. Both terms often apply even when no money changes hands.

Stripe’s privacy policy states that it does not transfer personal data to third parties in exchange for payment. It also confirms that it does not sell or share sensitive personal information — such as government IDs or biometrics — for behavioral advertising.

However, the Stripe privacy policy also acknowledges that the company provides certain types of personal data to third party partners — including advertising partners, analytics providers, and social networks — to assist in advertising Stripe’s own products and services.

Since data is being exchanged for a service, this may be considered either “selling” or “sharing” data as those terms are defined under the California Consumer Privacy Act (CCPA) / California Privacy Rights Act (CPRA) and other applicable US privacy laws. 

In its Privacy Center, Stripe clarifies that it has “sold” or “shared” the following categories of personal information (as defined under the CCPA/CPRA) to third parties, including advertising partners, in the past 12 months:

• Device and activity data including device identifiers, browser and usage information across Stripe-enabled business websites
• Geolocation data such as general location inferred from IP addresses

International data transfers

If your business uses Stripe, your customers’ personal data may be transferred to other countries, including the US. This can happen if your customers use an international payment method or financial partner service, or when Stripe or its service providers process data in other jurisdictions.

To carry out these data transfers in compliance with privacy laws, Stripe relies on mechanisms such as: 

• The EU-U.S. Data Privacy Framework for transfers between the EEA/EU and the US
• The UK Extension to the EU-U.S. Data Privacy Framework and the UK International Data Transfer Addendum for transfers between the UK and the US
• The Swiss-US Data Privacy Framework for transfers between Switzerland and the US
• Standard Contractual Clauses (SCCs) approved by the European Commission

Stripe may also rely on other alternative data transfer mechanisms approved by relevant privacy authorities to transfer personal data to a third country.

This means you are relying on Stripe’s legal frameworks to lawfully transfer data. Your own privacy policy should inform your customers that their data may be processed in other countries, including the US.

Jurisdiction-specific provisions in the Stripe privacy policy

Since Stripe operates globally, it must handle personal data in compliance with data privacy laws in different regions based on the location of the individuals whose data it processes. The Stripe privacy policy includes jurisdiction-specific provisions that reflect several data protection regulations, including:

• The EU’s General Data Protection Regulation (GDPR)
• Brazil’s Lei Geral de Proteção de Dados Pessoais (LGPD)
• Several Canadian privacy laws, including the federal Personal Information Protection and Electronic Documents Act (PIPEDA) and some provincial laws
• Switzerland’s Federal Act on Data Protection (FADP)

For end users in the US, Stripe applies both federal and state-level privacy laws. The Stripe privacy policy states that US-based individuals have the right to opt out of the sale or sharing of their personal information and to limit how their sensitive personal information is used or shared.

If you send Stripe your customers’ personal data, you’re required to give customers a way to exercise those opt-out rights.

Does Stripe require you to have a privacy policy?

Stripe’s privacy policy states that you are directly responsible for making disclosures to your customers about your own data collection and use.

This means you must be transparent with your customers about how you use their personal data, which includes disclosing that you share it with Stripe. Typically, this is done through a privacy policy.

Stripe’s data processing agreement (DPA) also requires transparency. Stripe’s DPA covers both your obligations and Stripe’s regarding personal data processing. It explicitly obligates you to provide “all necessary information (including by means of offering a transparent and easily accessible public privacy notice).” In other words, a privacy policy.

How to align your business with privacy laws and Stripe’s privacy requirements

As a business using Stripe, your data handling practices must meet the requirements of relevant global privacy regulations. Stripe includes many of these legal obligations as a formal part of your contract through its own specific terms.

Meet consent requirements under global data privacy laws

Your DPA with Stripe requires you to have a valid legal basis for processing personal data. Where required by law, you must obtain all necessary consents from customers for both your own and Stripe’s data processing activities.

Under laws like the GDPR, you typically need to obtain explicit user consent before you collect individuals’ personal information. 

While many US states use an opt-out consent model, generally prior consent is required if the data to be processed is categorized as sensitive or belongs to children. This is especially relevant if you use Stripe’s identity verification services, as these can require processing sensitive personal data like biometric information.

You must provide a clear way for customers to opt out of the sale or sharing of their personal information even if it’s not considered sensitive. You must also provide a way to limit how their sensitive data is used where required by state law.

Follow purpose limitation principles

If you receive data from Stripe, you can only use it for the specific purposes that you have disclosed to users in your privacy policy, and only if you have obtained the proper consent where required by law.

Follow data minimization principles

Practice data minimization by collecting only the personal data that is strictly necessary for your stated purpose. Doing so will help you comply with laws like the GDPR and avoid the risk of collecting or sharing data that is prohibited or unnecessary.

This principle is especially important for transaction data. Certain types of financial information are considered sensitive personal information under many US state privacy laws and are therefore subject to stricter rules.

Be transparent with your users

Your privacy policy must clearly explain how your business uses Stripe’s business services and what that use means for your customers’ personal data. Below is a non-exhaustive checklist of what to include in your privacy policy.

• Describe how your business collects, uses, and shares personal data with Stripe and for what purposes. Note that Stripe may use the data according to its own privacy policy.
• Inform users that data shared with Stripe may be further shared by Stripe, including with its service providers or affiliates.
• Include links to Stripe’s privacy policy.
• If you use Stripe’s identity verification services, be explicit that customers may be required to share sensitive personal information with Stripe.
• Explain users’ rights under relevant laws and how they can exercise them, such as the right to object (under the GDPR) and the right to opt out (under the CCPA/CPRA).
• If you use tools that access or store data on user devices — such as the Stripe.js or SDKs — include:
  • A disclosure that your website or app uses third-party tracking technologies, including Stripe
  • A description of the types of data collected and how they are used
  • Opt-out mechanisms where required by law
  • Clear, accessible links that enable users to exercise those choices
• Share your contact details for users to reach out with any questions or concerns they may have about your data policies or their rights. Include information about your Data Protection Officer (DPO) if you have one, or any other qualified corporate privacy contact.

Your privacy policy must be written in clear, non-legal language for anyone to understand. It should also be easily accessible on your website or app. Most businesses share their privacy policies on the footer of their website, on their app’s menu, or both if applicable.

You are also responsible for keeping the policy up to date with changes to data protection laws, Stripe’s terms, or your own data handling practices.

Usercentrics does not provide legal advice, and information is provided for educational purposes only. We always recommend engaging qualified legal counsel or privacy specialists regarding data privacy and protection issues and operations.