But in reality, the user simply saw the ad on one device and completed the purchase on another.

A classic example: someone watches a YouTube video on their laptop, notices the brand, and a few days later searches for it on their smartphone and places an order. In standard analytics, this would appear as “organic traffic,” even though the ad played a key role.

This is exactly the problem that cross-device tracking solves — an approach that connects user actions across different devices and allows for a more accurate evaluation of marketing performance.

In this article, we’ll explain what cross-device tracking is, how it works, its limitations, and how to use it to improve analytics and advertising.

What is cross-device tracking

Cross-device tracking is an analytics method that allows you to unify a single user’s actions across multiple devices (such as a smartphone, laptop, or tablet) into one continuous interaction history.

For example, a user might first see an ad on their laptop, and later visit the website and make a purchase from their smartphone. Cross-device tracking helps identify that this is the same person, not two different users.

This is important because without this approach, a significant portion of marketing impact remains “invisible,” leading to inaccurate evaluation of advertising performance.

Why cross-device tracking is important

According to Hootsuite, 96% of people today own smartphones, 59.7% use laptops or PCs, and 34.8% have tablets. This means a large share of users regularly interact with multiple internet-connected devices — typically a combination of phone and computer in one form or another.

In addition, people use gaming consoles, Smart TVs, virtual reality devices, and more. All of these devices can be used to deliver advertising — and in reality, they already are.

Accurate attribution

One of the main purposes of cross-device tracking is to correctly identify which channel or ad actually led the user to convert.

For example, a user may see an ad on YouTube from their laptop, remember the brand, and then search for it on Google a few days later using their smartphone. In standard analytics, that conversion would be attributed to organic search, even though the ad played the key role.

Cross-device tracking connects these actions and makes it possible to assess the contribution of each channel more accurately.

Frequency capping across devices

Another important use case is controlling how often the same user sees your ads.

For example, if the effective frequency is five impressions, showing the ad more often may no longer be cost-efficient. Without cross-device tracking, the same person may end up seeing the ad far more times — on their smartphone, laptop, Smart TV, and other devices.

As a result, the budget is spent inefficiently, while the user is exposed to an excessive number of identical ads.

Optimizing the advertising budget

When you understand the full user journey across different devices, it becomes much easier to optimize your campaigns. You can clearly see:

• which channels actually drive conversions
• where users drop off in the funnel
• which devices play a key role in decision-making

This allows you to allocate budget more effectively and avoid underestimating channels that contribute at earlier stages of the funnel.

Insight: where conversions actually happen

An important point: conversions often don’t happen on the same device where the user first interacted with the ad. A person might discover a brand on a laptop or Smart TV, but complete the action later on their smartphone. Without cross-device tracking, these transitions remain invisible.

As a result, businesses may underestimate the impact of their advertising and make decisions based on incomplete data.

How cross-device tracking works

To connect a user’s actions across different devices, analytics systems typically rely on two main approaches: deterministic and probabilistic. They differ in both accuracy and the way they identify users, but in practice, they are often used together.

Deterministic approach

The deterministic approach is based on exact user identifiers. These may include:

• an account login
• a User ID
• a Device ID on mobile devices

If a user logs in on multiple devices using the same account, the system can accurately recognize them as the same person. For example, if you sign in to a service from both your laptop and smartphone using the same login, all of your actions can be combined into a single profile.

This is the most accurate approach, but it only works in environments where users authenticate themselves.

Probabilistic approach

The probabilistic approach does not rely on a direct user identifier, so it works differently — by making data-driven assumptions. The system analyzes:

• user behavior
• timing and frequency of visits
• IP address or approximate location
• device and browser type

Based on this, it determines that different sessions are likely to belong to the same person. In simple terms, if someone regularly visits a site from both a laptop and a smartphone from the same location and behaves similarly, the system “infers” that it’s the same user.

This approach is less accurate, but it allows tracking to work even without a user login.

Why a combination of approaches is used today

Today, most systems use a combination of deterministic and probabilistic approaches.

This is largely because the internet is moving away from third-party cookies, and access to precise user data is becoming more limited (for example, due to privacy policies and frameworks like Apple’s App Tracking Transparency).

In this environment, deterministic data remains the most reliable, but it is not enough to cover the entire audience. That’s why it is complemented with probabilistic models.

At newage., we prioritize the deterministic approach for its accuracy, but combine methods to build the most complete picture of user behavior.

How newage. uses cross-device tracking

In our work, we use cross-device tracking as part of a comprehensive media advertising analysis framework. Our primary tool is Google Campaign Manager, which allows us to track how users interact with ads across different devices and account for delayed conversions.

In practice, this works as follows: the system records a user’s interaction with an ad (for example, viewing a banner or video) and then tracks their subsequent actions — even if those actions take place on a different device.

⁣⁣Did you know that Google Campaign Manager can help you analyze your ads and campaigns? We have the perfect article for you: “How to Analyze Advertising with Google Campaign Manager.”

Scenario example

A user sees a video ad on YouTube from their laptop, but doesn’t visit the website right away. After some time, they remember the brand, pick up their smartphone, search for it, and complete a purchase. In standard analytics, this conversion would appear as organic traffic. However, with Google Campaign Manager, we can see the full journey:

• ad exposure
• delayed visit
• conversion from another device

This allows us to:

• accurately evaluate the effectiveness of media advertising
• avoid “losing” its impact in reports
• make more informed decisions when optimizing campaigns

This type of tracking is based on user-level identifiers used by Google. Similar approaches are applied by other major platforms (such as Meta, Apple, and programmatic systems), but each operates within its own ecosystem.

That’s why, to get the most complete picture, we combine data from multiple sources and build analytics around real user behavior rather than individual devices.

Limitations of cross-device tracking

Despite its advantages, cross-device tracking is not a perfect solution and comes with several limitations that should be taken into account when analyzing data.

No single unified system

Today, there is no universal system capable of connecting all of a user’s devices across different advertising platforms.

Each ecosystem — such as Google, Meta, or Apple — uses its own identity framework and does not share complete data with others. As a result, analytics remains at least partially fragmented.

The impact of privacy policies (Apple ATT and others)

Frameworks such as Apple’s App Tracking Transparency (ATT) have significantly limited the ability to track users, especially in mobile environments.

Users can opt out of tracking, and when they do, part of the data is simply unavailable. This reduces the accuracy of both deterministic and probabilistic approaches.

Dependence on user authentication

The most accurate method — the deterministic approach — only works when a user logs in across different devices.

If a user does not log in, the system has no direct way to connect their actions across devices. In such cases, it has to rely on less accurate probabilistic models.

Cookie limitations and the cookieless environment

The modern internet is gradually moving away from third-party cookies, which used to be one of the main tools for tracking.

Browsers are restricting their use, while users are more frequently clearing data or browsing in private mode. This makes behavior tracking more difficult and reduces data completeness.

As a result, cross-device tracking should not be seen as a perfectly precise tool, but rather as a way to significantly improve the understanding of user behavior in an environment with limited data.

What is cross-device in Google Analytics?

Google Analytics provides Cross-Device reports, which are available within User ID views.

A User ID view is a special reporting view that includes only sessions where a unique identifier and its associated data are sent to Analytics. To analyze your full dataset, you should use a separate standard view alongside it.

Within this view, you can access reports such as “Device Overlap,” which aggregate data on how users interact across multiple devices. However, before analyzing these reports, you need to configure the User ID feature and create the corresponding view.

In practice, this works as follows: to identify users via User ID, your website must have an authentication system. When a user registers, they receive a unique login, which can be used to generate a unique identifier and pass it to Google Analytics as the User ID value. This allows Analytics to recognize a logged-in user across different devices.

You can find step-by-step instructions for setting up User ID in Google Analytics in the official documentation.

Practical use of cross-device tracking

Cross-device tracking not only improves analytics but also opens up new opportunities for building more effective advertising strategies. Below are some common use cases.

Scenario: TV / YouTube → smartphone

A user watches a video on a Smart TV or YouTube and sees an ad. At that moment, they are not ready to visit a website — it’s simply inconvenient from a TV screen. To avoid losing the interaction, the ad includes a QR code or a short URL. Then:

• the user scans the QR code with their smartphone
• lands on the website
• interacts with it or completes a conversion

Cross-device tracking makes it possible to connect these actions and understand that the video ad was the source of the conversion.

Scenario: Desktop → Mobile conversion

A user sees a banner or video ad on their laptop but does not take action right away. Later, they:

• pick up their smartphone
• search for the brand on Google
• visit the website and make a purchase

Without cross-device tracking, this conversion appears as organic traffic. In reality, however, the ad played its role at the first stage of the journey.

This is one of the most common scenarios — and one of the main reasons

Scenario: cross-device remarketing

A user interacts with a website on one device but doesn’t convert. For example, they:

• browse a product on their laptop
• leave the site without completing a purchase

After that, ads “follow” them on another device:

• on social media via their smartphone
• in mobile apps
• through video ads

Cross-device tracking makes it possible to:

• retain the user when they switch devices
• build more precise remarketing campaigns
• control the frequency and sequence of communication

Adapting landing pages for different devices

When you understand how users switch between devices, you can tailor the experience to match that behavior. For example, you can:

• simplify forms for mobile users
• preserve progress across devices (such as cart items or saved products)
• optimize speed and UX for different screen formats

This helps reduce drop-off on the path to conversion and makes the user experience more seamless.

As a result, a cross-device approach not only improves ad measurement, but also helps build more consistent and logical communication with users at every stage of their journey.

Benefits of cross-device tracking for businesses and users

Cross-device tracking is valuable not only for analytics but also for the overall logic of advertising communication. It helps businesses measure marketing performance more accurately, while giving users a more relevant and less intrusive ad experience. Let’s look at these benefits separately.

For businesses

For businesses, cross-device tracking is first and foremost a way to see a more complete picture of advertising effectiveness. It helps to:

• attribute conversions more accurately
• better understand the customer journey to purchase
• avoid underestimating media channels that influence users at the top of the funnel
• control ad frequency across different devices
• allocate advertising budgets more efficiently

As a result, businesses gain a stronger basis for informed decision-making and can optimize advertising not at the level of individual devices, but around real human behavior.

For users

For users, a cross-device approach can also be beneficial. When advertising campaigns are set up correctly, people:

• see the same ads less often
• receive more relevant messages
• interact with the brand more consistently across devices
• enjoy a smoother path to conversion

In other words, instead of chaotic advertising across every screen, users get a more logical and personalized experience.

Cross-device tracking helps reveal what often remains invisible in standard analytics: how users actually move between devices on the path to conversion. It gives businesses more accurate data for evaluating advertising performance, while giving users a more relevant and comfortable brand experience.

If you want to measure media advertising more accurately and better understand how your audience behaves across devices, the newage. team can help you build analytics tailored to your business goals.

FAQ

Does cross-device tracking work without cookies?

Yes, but with limitations. In today’s cookieless environment, cross-device tracking increasingly relies on deterministic data (such as user logins) and is supplemented with probabilistic models. Without cookies, accuracy may decrease, but tracking does not disappear entirely.

What tools support cross-device tracking?

The most common solutions include Google Campaign Manager, Google Analytics (via User ID), Meta (Facebook/Instagram), and various programmatic platforms. Each system operates within its own ecosystem and comes with its own limitations.

How accurate is cross-device tracking?

Accuracy depends on the approach. Deterministic tracking (based on logins or User ID) is highly accurate, while probabilistic tracking relies on assumptions and may introduce some margin of error. In most cases, a combination of both methods is used.

Can cross-device tracking be implemented without user authentication?

Yes, but in this case, it relies on probabilistic models, which are less accurate. The best results are achieved when a business can identify users through logins or other unique identifiers.

Why can cross-device data differ across platforms?

Because each platform (such as Google, Meta, Apple, etc.) uses its own algorithms and data sources. They do not share full information with each other, so the user journey may appear differently across systems.