UK enterprises are increasingly moving away from Google Analytics (GA4), primarily due to requirements for full data ownership, adherence to GDPR and UK GDPR, and the operational complexity of the GA4 interface. Matomo is frequently selected as the preferred alternative for organisations seeking a professional analytics solution.
A primary consideration for digital managers and data leads is the preservation of historical data integrity. Loss of performance context or disruption to event tracking during migration presents significant operational risk.
For organisations undertaking this migration, the quality of implementation is critical. TagDataTrust, as the only certified Matomo Implementation Partner in the UK, provides migration approaches that prioritise technical accuracy, regulatory compliance, and data continuity.
This document outlines a stepwise migration process designed to maintain data integrity and preserve analytical insights.
Why Data Quality is the Core Challenge
Migration between analytics platforms involves more than replacing a tracking script. Google Analytics and Matomo differ in data models, session definitions, and attribution logic. Without a structured methodology, there is a risk of data drift, resulting in misalignment between reported metrics and actual business performance.
Preserving data quality during migration requires attention to three core areas:
- Historical Continuity: Importing your UA or GA4 history so you can still perform year-on-year (YoY) analysis.
- Schema Alignment: Ensuring your custom dimensions, events, and ecommerce goals in GA map accurately to Matomo’s structure.
- Validation: Operating both systems in parallel to identify and document discrepancies prior to final migration.
Phase 1: The Pre-Migration Audit and Mapping
Prior to any technical changes, a comprehensive audit of the current analytics implementation is required. Legacy GA configurations frequently contain redundant events or obsolete tracking elements that do not align with current business objectives.
1. Inventory Your Assets
Compile a comprehensive inventory of all tracked elements within GA4:
- Core KPIs: Sessions, users, conversion rates, and revenue.
- Custom Dimensions/Metrics: Methods used for categorising users or content.
- Events: Essential user interactions, such as clicks, scrolls, and form initiations.
- Ecommerce: Product IDs, categories, and checkout funnel steps.
2. Create a Data “Crosswalk”
It is necessary to map Google Analytics terminology to Matomo terminology. GA4 utilises an event-based model, whereas Matomo provides a flexible structure capable of supporting both pageview-based tracking and advanced event modelling.
This is also where specialist Matomo expertise becomes particularly valuable. As the only certified Matomo Implementation Partner in the UK, TagDataTrust helps organisations define a clear mapping document so that each GA4 event property is stored appropriately in Matomo and critical reporting logic is preserved during the import phase.
Phase 2: Setting Up the Matomo Environment
You have two primary choices: Matomo Cloud or Matomo On-Premise.
- Matomo Cloud: Rapid deployment, managed by Matomo, and includes the Google Analytics Importer as standard.Matomo On-Premise: Provides maximum control and data sovereignty. Data is hosted on the organisation’s own servers or private cloud, ensuring that all data remains within the required jurisdiction. This is particularly relevant for sectors with stringent compliance requirements, such as finance and healthcare.
TagDataTrust, as the only certified Matomo Implementation Partner in the UK, assists organisations in evaluating infrastructure options based on traffic volume, governance requirements, and security standards. For enterprise clients, On-Premise deployments are frequently the preferred choice where high-performance querying and strict data control are required.
Phase 3: Importing Historical Data
The objective is to migrate historical Google Analytics data into Matomo, ensuring continuity in reporting and analysis.
The Google Analytics Importer
Matomo offers a dedicated plugin that extracts data directly from the Google Analytics API.
- Authentication: You’ll need to create a Google Cloud Project and authorise Matomo to access your GA data.
- Configuration: You select which properties and date ranges to import.
- Execution: The duration of the import process is dependent on data volume and Google API rate limits, and may require several days to complete.
Note regarding GA4: The importer is effective for Universal Analytics (UA), but GA4’s data structure introduces additional complexity. Where significant volumes of custom data are stored in BigQuery, standard import processes may not capture all required details. In such cases, specialist implementation support is recommended. TagDataTrust employs custom ETL (Extract, Transform, Load) processes to ensure accurate reconstruction of GA4 custom dimensions within Matomo.
Phase 4: Implementation and Dual Tagging
Following the commencement of historical data import, Matomo tracking should be implemented on the live site.
Parallel Tracking
An abrupt transition is not recommended. Dual tagging is implemented so that, for a period of two to four weeks, the website transmits data to both Google Analytics and Matomo in parallel.
This allows you to:
- Verify that Matomo is capturing events correctly.
- Compare session counts and identify any attribution differences.
- Ensure that your Consent Management Platform (CMP) is correctly handling Matomo’s tracking tags.
Tag Management Integration
Regardless of the tag management system in use (Google Tag Manager, Tealium iQ, or Adobe Launch), implementation should be seamless. The existing data layer is utilised to populate Matomo variables, maintaining consistent logic across both platforms.
Phase 5: Validation and Quality Assurance
This is the most important stage. If your stakeholders do not trust the new numbers, the migration has failed.
Our QA process involves:
- Reconciliation Reports: We produce a side-by-side comparison of your primary KPIs (e.g., total orders, total users).
- Discrepancy Investigation: Certain differences are anticipated, such as variations in the handling of unattributed traffic or ad blockers. These discrepancies are documented to clarify any observed variances in reported metrics.
- Data Integrity Checks: Verification that no duplicate data is generated during import and that filters, such as those excluding internal IP addresses, are functioning as intended.
Phase 6: Privacy Configuration
Privacy is a primary driver for migration to Matomo. In the final phase, Matomo is configured to align with the organisation’s specific compliance requirements:
- Anonymisation: Configuring IP anonymisation levels.
- Cookie-less Tracking: Configuring Matomo to operate without cookies where required, while maintaining session integrity.
- Data Retention: Aligning data storage policies with internal Data Protection Impact Assessments (DPIAs).
Secure Your Data’s Future
Historical data should be preserved, and migration processes must not introduce reporting uncertainty. Transitioning to Matomo provides an opportunity to enhance tracking architecture, strengthen compliance, and maintain control over the analytics environment.
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