Cross-domain tracking

Cross-domain tracking follows users between different domains and merges fragmented sessions into one customer journey. Without it, each domain switch counts as a new visitor.

Data fragmentation

Cookies are bound to one domain. Other domains can't read them, by design. That breaks tracking on multi-domain setups.

Typical e-commerce flow

Store on example-store.com uses payments at payment-provider.com:

Without cross-domain tracking:

User from ad campaign: session #1 on main site
Payment redirect: session #2 on payment domain
Result: 2 different users, lost conversion attribution

With cross-domain tracking:

Single session across both domains
Original source preserved
Transaction credited to ad campaign

What breaks without it

Metric	Distortion	Business impact
Users	Inflated 40-60%	Wrong audience size
Sessions	Duplicated on each transition	Skewed engagement
Sources	Original lost	Misallocated budget
Conversions	Attribution to direct	Undervalued campaigns
Bounce rate	Inflated	False quality signals

How it works

Cross-domain tracking passes user identifiers via URL parameters between domains. Cookies keep the same IDs, transferred through a _gl URL parameter on links and forms.

sequenceDiagram
    participant U as User
    participant A as Domain A
    participant B as Domain B
    participant GA as Analytics

    U->>A: Page visit
    A->>GA: Create Client ID
    A->>A: Store _ga cookie
    U->>A: Click link to Domain B
    A->>B: Pass ID via _gl parameter
    B->>B: Extract Client ID
    B->>GA: Continue same session

Components

Linker (source)Acceptor (destination)

Functions:

Track clicks on cross-domain links
Generate _gl parameter with encrypted Client ID
Auto-append to URL
Handle forms and redirects

Notes:

Linker parameters expire after two minutes, so they're added at click time
Multi-domain support
Works with dynamic links

Functions:

Parse incoming _gl parameter
Validate timestamp
Restore Client ID
Overwrite local cookie

Notes:

Auto-rejects expired parameters
Verifies data integrity
Preserves original source

GA4 setup

GA4 simplified cross-domain tracking compared to Universal Analytics. Setup is in the admin UI, no code or GTM required.

Step by step

Requirements

Editor rights on GA4 property
Same Measurement ID on all domains
Code access on every tracked domain
Maximum 100 domain conditions

Configuration:

Open Data Stream settings

Admin → Data Streams
Pick the web stream
Click "Configure tag settings"

Add domains

In Settings, click "Configure your domains"
If the same Google tag is used across domains, they appear in Recommendations
Add manually via "Add condition"

Match conditions

Match type	Example	Includes
Contains	example.com	All subdomains and paths
Exact match	shop.example.com	Only that domain
Starts with	secure.	All domains with prefix
Ends with	.example.com	Main and subdomains
Regex	^(shop\|pay).example	Complex patterns

Google Tag Manager

GTM gives more flexibility:

// Google Tag configuration with cross-domain
gtag('config', 'G-XXXXXXXXXX', {
  'linker': {
    'domains': ['example.com', 'checkout.example.com', 'payment-provider.com']
  }
});

Why GTM

Centralized management across domains
Conditional firing
Versioning
Pre-publish testing
Easy integration with other tags

Testing and debugging

Verifying setup is critical. Open a page with a link to the second domain, click it, and confirm the URL contains _gl, e.g. https://www.example.com/?_gl=1*abcde5*.

Verification

Quick checkDetailed debug

Steps:

Open first domain in incognito
Click link to second domain
Check URL for _gl
Open dev console
Compare _ga cookie on both domains

Success signs:

_gl present
_ga matches on both
Session continues in GA4

Tools:

GA4 DebugView for real-time
Tag Assistant for tag validation
Network tab for request analysis
Cookie inspector for values

What to verify:

Client ID consistency
Session ID preserved
Source attribution
Event parameters

Common issues

Issue	Cause	Fix
`_gl` missing	Wrong domain config	Check exact domain match
Parameter dropped on transition	Redirects clear query	Preserve params in redirect rules
Different Client IDs	Cookie not overwritten	Check `allowLinker` on receiving domain
Session resets	Parameter expired (>2 min)	Reduce redirects
Cookie blocking extensions	User privacy settings	Use server-side tracking

Special cases

Subdomains

GA4 tracks across subdomains by default. Caveats:

When subdomain setup is needed

Different cookie domain settings
Different GTM containers
Custom JS implementation
Need to filter specific subdomains

Multiple domains

For more than two domains:

graph TD
    A[Main Site<br/>example.com] --> B[Blog<br/>blog.example.com]
    A --> C[Store<br/>shop.example.net]
    C --> D[Payments<br/>payment-gateway.com]
    C --> E[Support<br/>support.example.io]

    style A fill:#e8f4f8
    style C fill:#fff4e6
    style D fill:#ffe6e6

Strategies:

Minimize cross-domain transitions
Keep critical processes on one domain
Add fallback for parameter loss
Monitor data integrity with custom alerts

Payment gateways

Payments add complexity:

Scenario	Problem	Fix
Redirect-based payment	Multiple redirects	Webhooks for server-side tracking
iFrame integration	Isolated context	PostMessage API
External checkout	Full context loss	Enhanced e-commerce with transaction ID matching
Multi-step verification	Parameter timeouts	Session storage backup

Alternatives

Server-side tracking

For business-critical flows:

sequenceDiagram
    participant Browser
    participant Server A
    participant Server B
    participant Analytics API

    Browser->>Server A: Request with Client ID
    Server A->>Server A: Store ID in session
    Server A->>Analytics API: Send event
    Browser->>Server B: Navigate to Domain B
    Server A->>Server B: Pass ID via API
    Server B->>Analytics API: Continue tracking

Benefits:

No browser limits
Full data control
Easy enrichment
Ad-blocker resistant

First-party data

Build your own ID system:

Components

Identification:

Persistent ID generation
Cross-device matching
Probabilistic fingerprinting

Storage:

Centralized database
Real-time sync
State backup

Application:

Push to analytics
Enrich CRM
Personalize experience

Impact on metrics

Metric	Before	After	Change
Users	10,000	6,500	-35%
Sessions	15,000	8,000	-47%
Bounce Rate	65%	45%	-20pp
Conversion Rate	1.2%	2.1%	+75%
Avg. Session Duration	1:30	3:45	+150%
Pages/Session	2.3	5.7	+148%

Historical data

When implementing:

Annotate the implementation date in GA4
Save baseline metrics
Recalculate KPIs with new methodology
Update dashboards with explanations
Inform stakeholders about reporting impact

Best practices

Architecture

Optimal domain structure

Minimize domain count:

Use subdomains over separate domains where possible
Consolidate on main domain
Avoid unnecessary redirects

Standard naming:

Consistent subdomain prefixes
Logical URL hierarchy
Consistent parameters

Documentation

Maintain:

All tracked domains
Domain transition matrix
Per-domain configuration
Test procedures
Owner contacts
Change history

Monitoring

Regular checks:

graph LR
    A[Daily] --> B[Check<br/>_gl parameter]
    C[Weekly] --> D[Analyze<br/>self-referrals]
    E[Monthly] --> F[Configuration<br/>audit]
    G[Quarterly] --> H[Full<br/>testing]

Future

Privacy-first

Privacy regulation forces new solutions:

Privacy Sandbox APIs for aggregate reporting
Consent-based tracking with granular permissions
Federated Learning for analysis without data transfer
Differential Privacy for individual data protection

Innovations

Emerging approaches

Edge Computing:

Processing at CDN level
Minimal latency
Geographic distribution

Blockchain ID:

Decentralized identification
User-controlled data
Transparent attribution

AI matching:

Probabilistic user matching
Behavioral pattern recognition
Predictive journey completion

Statable approach

Statable removes the friction of traditional cross-domain tracking. Automatic detection of related domains and intelligent session linking, no complex setup or maintenance.

We are building tracking that survives cookie blocks and parameter loss. Multiple signals identify users.

The platform shows a visual map of cross-domain transitions with auto-detection of problem points. Find and fix tracking gaps without deep technical analysis.

No fixed domain limits. Each new domain joins the unified tracking system automatically.

About AI participation in writing articles

This article, like many others on our site, was created, written and proofread by a team of developers. Of course, not without the participation of AI assistants. We don't hide this and believe that modern systems are already quite good at handling simple tasks and, relatively speaking, writing an article about Viewport yourself is quite strange. It won't come out significantly better and will take a lot of time. But providing basic understanding to beginner webmasters is necessary. Of course, after the article is written by assistants - there's always proofreading, and this is where not one or two people participate, and only after that the article is published.

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