What is the difference between GA4 and Firebase Analytics?

TLDR

GA4 and Firebase Analytics share the same event-based data model but exist for different users and decisions. GA4 is the web-first analytics layer for marketers and growth teams who need attribution, cross-platform funnels, and audience export to Google Ads. Firebase Analytics is the in-app SDK inside the Firebase platform, built for developers who need real-time debugging, experiments, Crashlytics, and tight integration with other Firebase services.

For pure web products, use GA4. For mobile-first apps, use Firebase, optionally linked to GA4. Cross-platform products typically need both, plus a shared event taxonomy, User-ID, and strong governance to avoid duplication and messy funnels. Growth teams in Europe must also factor in GDPR, consent mode, and often BigQuery exports to combine analytics with CRM and revenue data for reliable, decision-ready reporting.

Key differences between GA4 and Firebase Analytics

Google Analytics 4 and Firebase Analytics are built on the same event-based data model and can share a single data stream, but they serve different audiences and offer distinct reporting and integration capabilities. The confusion arises because Firebase Analytics can send data to a GA4 property, and both tools can track mobile apps. The key distinction lies in implementation, user interface, and ecosystem.

GA4 in one sentence

Google Analytics 4 is a web-first analytics platform that supports mobile app tracking through Firebase or Google Tag Manager and offers audience building, attribution reporting, and integration with Google Ads. It is designed for marketers, growth managers, and analysts who need to understand user journeys across web and app, connect analytics to advertising spend, and build audiences for remarketing.

Firebase Analytics in one sentence

Firebase Analytics is the native analytics module inside Google's Firebase mobile development platform, designed for developers to measure in-app events, debug crashes, test features, and send data to BigQuery. It offers minimal reporting inside the Firebase console but provides richer developer tools like DebugView, StreamView, and direct integration with other Firebase services like Remote Config, A/B Testing, and Crashlytics.

When you should choose GA4

Choose GA4 if you operate a primarily web-based business, run paid campaigns through Google Ads or other platforms, need attribution reports that connect revenue to marketing channels, or require audience segmentation for remarketing. GA4 is the right choice for teams led by marketing managers or growth leads who need to report on conversion funnels, ROI, and campaign performance in a familiar interface that integrates with existing Google Marketing Platform tools.

When you should choose Firebase Analytics

Choose Firebase Analytics if you are building a native mobile app or game, your team lives in the Firebase console for development and testing, you rely heavily on in-app events and user properties to inform product decisions, or you need real-time debugging and integration with Firebase Remote Config and Crashlytics. Firebase Analytics is ideal for product teams, mobile developers, and technical analysts who prioritise speed, developer experience, and in-depth app behaviour insights over polished marketing reports.

If you run a product with a mobile app, a web app, or both, you have probably asked yourself which analytics platform to use. Google offers two closely related but distinct solutions, Google Analytics 4 and Firebase Analytics. They share the same underlying data model and can even send events to the same property, yet they differ in implementation, reporting, and intended audience. For growth teams and product owners who need accurate tracking to inform campaigns, experiments, and investment decisions, understanding what is the difference between GA4 and Firebase Analytics is essential to avoid wasted budget, duplicate work, and misaligned analytics strategies.

This guide explains exactly what GA4 and Firebase Analytics are, how they differ in data handling, implementation, and use cases, and when you should choose one, the other, or both. We focus on practical considerations for teams in Europe who are building web apps, mobile apps, or cross-platform products and need a clear, no-nonsense path to measurement that supports growth without technical debt.

What is GA4

Google Analytics 4 is the current generation of Google Analytics, launched to replace Universal Analytics in July 2023. Unlike its predecessor, which was session-based and web-centric, GA4 uses an event-based data model that can track both web and app interactions within a single property. Every user action, from page views to purchases to video plays, is recorded as an event with associated parameters.

GA4 was designed to address the shift toward mobile apps, privacy regulation, and cross-device user journeys. It collects data via the gtag.js library for websites, the Google Analytics for Firebase SDK for mobile apps, or server-side through the Measurement Protocol. GA4 properties can combine data from multiple platforms into one reporting view, making it possible to see a user who starts a journey on mobile and converts on desktop.

How GA4 handles web and app tracking

For websites, GA4 deploys a JavaScript tag that fires events on page views, clicks, form submissions, and custom interactions defined in Google Tag Manager or directly in code. Enhanced measurement automatically captures scroll depth, outbound clicks, site search, video engagement, and file downloads. This makes GA4 faster to set up than Universal Analytics for standard web tracking, though custom event implementation still requires configuration and testing.

For mobile apps, GA4 relies on the Firebase SDK, which sends events to a GA4 property if you link your Firebase project to Google Analytics. The Firebase SDK tracks screen views, in-app purchases, user engagement, and custom events you define in your app code. These events appear in GA4 reports alongside web events, but the implementation is fundamentally different, you are running Firebase Analytics under the hood and exporting the data to a GA4 property.

The event based data model in GA4

What is the difference between GA4 and Firebase Analytics in terms of data structure? Both platforms use the same event-based model, where every interaction is an event with a name and up to 25 custom parameters. This differs sharply from Universal Analytics, which organised data into sessions, hits, and page views. In GA4, a page view is simply an event called page_view, and a purchase is an event called purchase with parameters like transaction_id, value, and currency.

Events in GA4 can be automatically collected, enhanced measurement events, recommended events with predefined names and parameters, or custom events you define yourself. Parameters are key-value pairs attached to events, such as item_name, method, or campaign_source. User properties are attributes assigned to users, like subscription_status or first_platform, and persist across sessions. GA4 can link events and user properties to Google Signals data for cross-device tracking when users are signed in to Google, but this requires consent under GDPR.

This flexibility makes GA4 powerful for growth teams running experiments and tracking complex funnels, but it also introduces risk. Poorly named events, inconsistent parameters, or missing user properties lead to messy reports and make attribution impossible. Growth teams should define event naming conventions and governance rules early to avoid technical debt and ensure every team member understands what is the difference between GA4 and Firebase Analytics when both are sending events to the same property.

Reporting, audiences, and integrations in GA4

GA4 offers a range of built-in reports organised by lifecycle, acquisition, engagement, monetisation, and retention. Acquisition reports show how users arrive via organic search, paid ads, social media, or referral. Engagement reports break down page views, screen views, events, and conversions. Monetisation reports track ecommerce transactions, in-app purchases, and revenue by source. Retention reports show cohort analysis and user lifetime value.

The Explore section in GA4 provides flexible analysis tools like funnel exploration, path exploration, segment overlap, and user lifetime reports. These are more powerful than standard reports but require familiarity with dimensions, metrics, and filters. For teams that need custom dashboards, GA4 integrates with Looker Studio for free visualisation or BigQuery for advanced SQL analysis and data warehouse integration.

GA4 audiences are segments of users defined by events, user properties, or predictive conditions like purchase probability. Once created, audiences can be exported to Google Ads, Display and Video 360, or third-party platforms for remarketing. This tight integration with paid media platforms makes GA4 the preferred choice for marketing-led teams who need to close the loop between analytics and advertising spend. Firebase Analytics, by contrast, has no direct audience export to ad platforms, though you can use Firebase Remote Config to serve personalised content based on user properties.

What is Firebase and Firebase Analytics

Firebase is a comprehensive mobile and web development platform owned by Google, offering backend services, authentication, real-time databases, cloud storage, hosting, crash reporting, performance monitoring, and analytics. It was originally developed as a startup focused on real-time databases, acquired by Google in 2014, and expanded into a full suite of tools designed to accelerate app development and improve developer productivity. Firebase is especially popular for startups and lean teams that want to build, launch, and iterate on mobile apps without managing their own backend infrastructure.

Firebase Analytics sits inside Firebase as one of its core services. It is designed to capture in-app events, user properties, and engagement metrics automatically once you integrate the Firebase SDK into your Android, iOS, Flutter, or web app. The SDK collects standard events like first_open, screen_view, and app_update, plus any custom events you define. Firebase Analytics sends this data to your Firebase project, where it appears in the Firebase console and can be linked to a GA4 property to enable cross-platform reporting. Understanding what is the difference between GA4 and Firebase Analytics is crucial for teams deciding how to structure their analytics stack.

Firebase as a mobile development platform

Firebase provides a suite of over twenty modular services that developers can enable as needed. Authentication handles sign-in flows for email, phone, Google, Facebook, and other providers. Cloud Firestore and Realtime Database offer NoSQL databases that sync data across devices in real time. Cloud Functions enables serverless backend logic triggered by database writes, user actions, or scheduled events. Remote Config lets you change app behaviour and appearance without deploying a new version, which is useful for A/B testing and rolling out features gradually.

Performance Monitoring tracks app startup time, network latency, and screen rendering performance. Crashlytics captures crash reports with stack traces and device context, helping developers identify and fix bugs faster. App Distribution streamlines beta testing by distributing pre-release builds to internal testers. Firebase also integrates with Google Cloud Platform, so you can extend your app with BigQuery, Cloud Storage, and AI services. This ecosystem makes Firebase a one-stop shop for mobile developers, reducing the number of third-party tools and vendor integrations required to build and scale an app.

What Firebase Analytics tracks inside your app

Firebase Analytics automatically collects a set of predefined events when you integrate the SDK. These include first_open when a user installs and opens your app, session_start when a session begins, screen_view when a user navigates to a new screen, and user_engagement when a user actively interacts with the app for a meaningful duration. Automatically collected events also cover app updates, in-app purchases, ad impressions, and app removal, giving you baseline measurement without writing extra code.

You can define custom events using the logEvent method in the Firebase SDK. For example, you might log a level_complete event in a game, a search event in an ecommerce app, or a lead_form_submit event in a business app. Events support up to 25 custom parameters, such as content_type, item_id, or campaign_source, and these parameters enable detailed analysis in GA4 Explorations and BigQuery. User properties like subscription_tier, preferred_language, or first_purchase_date can also be set via the SDK, and these persist across sessions, allowing you to segment users and build audiences based on behaviour and attributes.

How Firebase Analytics connects to GA4

When you link a Firebase project to Google Analytics, Firebase Analytics events automatically flow into a GA4 property. This connection is established in the Firebase console under Project Settings, and once linked, all data from Firebase Analytics appears in GA4 reports alongside web data if you also have a web data stream. The Firebase SDK becomes the data source for mobile app tracking in GA4, so every event, parameter, and user property you send via Firebase appears in GA4 with the same structure as web events collected via gtag.js or Google Tag Manager.

This integration allows you to build unified cross-platform audiences in GA4. For example, you can create an audience of users who completed a purchase on mobile and visited a product page on web, then export that audience to Google Ads or Display and Video 360 for remarketing. However, Firebase also retains a simplified set of reports in its own console, which are designed for developers and focus on real-time debugging, crash correlation, and in-app behaviour. If your team is deciding what is the difference between GA4 and Firebase Analytics, the key distinction is that GA4 offers richer attribution and audience tools, while Firebase offers tighter integration with app development services like Remote Config and Crashlytics.

What is the difference between GA4 and Firebase Analytics

The core technical difference between GA4 and Firebase Analytics is that GA4 is a front-end analytics platform designed for marketers and analysts, while Firebase Analytics is a backend SDK embedded in your app that sends data to Firebase, which can then forward events to GA4. Both use the same event-based data model, but they differ in implementation, reporting, audience export, integrations, and intended user. Teams often struggle to understand what is the difference between GA4 and Firebase Analytics because Google markets them as complementary rather than separate, and because Firebase events can appear in GA4 if linked.

In practice, many product teams use both. Firebase Analytics provides real-time event debugging via DebugView and StreamView, which are invaluable during development and QA. GA4 provides polished reports, conversion attribution, predictive audiences, and integration with Google Ads. If you run both, you must maintain consistent event naming and parameter structures to avoid data mismatches. If you choose only one, your decision should be based on who will use the data and what actions they need to take. Marketing and growth teams gravitate toward GA4 because it connects to paid media platforms, supports attribution models, and offers audience export. Mobile developers and product managers often prefer Firebase because it lives in the same console as Crashlytics, Remote Config, and A/B Testing, enabling faster iteration.

Data model, events, and user properties

Both GA4 and Firebase Analytics use an event-based data model where every interaction is an event with a name and optional parameters. Event names in both platforms are case-sensitive and should follow snake_case convention. Parameters are key-value pairs that provide context for each event, such as item_name, price, or method. User properties are attributes assigned to individual users that persist across sessions and can be used for segmentation and audience building in GA4, or for personalisation in Firebase Remote Config.

The difference lies in how you send and manage this data. In GA4, events are typically fired via gtag.js or Google Tag Manager on web, or via the Firebase SDK on mobile. If you use Firebase Analytics and link it to GA4, the Firebase SDK sends events to Firebase, which forwards them to GA4. This means Firebase events appear in GA4, but GA4 web events do not appear in the Firebase console. User properties set in Firebase can also be used in GA4, but the reverse is not true. For teams managing both platforms, the key challenge is ensuring that event names, parameters, and user properties are consistent across web and app so that funnels and audiences work seamlessly.

Platforms, SDKs, and implementation workflows

GA4 supports web, iOS, and Android tracking. For websites, GA4 uses the gtag.js JavaScript library or Google Tag Manager. For mobile apps, GA4 relies on the Firebase SDK. If you have a native iOS or Android app and want to send data to GA4, you must install the Firebase SDK and link your Firebase project to a GA4 property. This means Firebase is the de facto implementation path for GA4 mobile tracking, which explains why what is the difference between GA4 and Firebase Analytics is often unclear to newcomers.

Firebase, by contrast, is a mobile-first platform. The Firebase SDK is available for iOS, Android, Flutter, Unity, and web apps, and it integrates natively with Swift, Kotlin, Dart, and JavaScript. Implementation involves adding the Firebase SDK to your app via CocoaPods, Gradle, or pub, then initialising Firebase in your app startup code. Once initialised, Firebase Analytics begins collecting events automatically. GA4 implementation for web requires adding a gtag snippet to your HTML or deploying tags via Google Tag Manager, which is faster and more flexible for teams that do not control source code directly.

Reporting, debugging, and developer experience

GA4 offers a rich set of reports organised by acquisition, engagement, monetisation, and retention. It includes funnel exploration, path analysis, cohort analysis, and user lifetime value reports in the Explore section. GA4 reports are designed for marketing managers, analysts, and growth teams who need to understand campaign performance, conversion attribution, and user journeys. The interface is polished and supports custom dashboards, scheduled exports, and integration with Looker Studio for external reporting.

Firebase Analytics provides a much simpler reporting interface inside the Firebase console. Reports include dashboards for events, conversions, audiences, and user properties, plus DebugView for real-time event monitoring and StreamView for observing individual user sessions. DebugView is especially useful for developers and QA teams because it shows every event as it fires, along with parameters and user properties, making it easy to validate that tracking is working correctly before deploying to production. GA4 has a similar real-time report, but Firebase DebugView is faster and more granular.

Pricing, limits, and data ownership considerations

Both GA4 and Firebase Analytics are free to use within Google's standard limits. Firebase Analytics is free without data volume limits, but if you want to export raw event data to BigQuery for advanced analysis or long-term storage, you need to enable the BigQuery export, which incurs BigQuery storage and query costs. GA4 is also free, but the free version has a 14-month data retention limit for user-level and event-level data, and it samples reports when data volumes exceed certain thresholds. GA4 360, the paid version, offers unsampled reports, longer data retention, and higher event quotas, but it costs significant enterprise-level fees.

Both platforms store data on Google servers in the United States by default, which raises GDPR and data residency concerns for EU businesses. Google offers data processing agreements and consent mode for both GA4 and Firebase, but teams must implement consent banners, anonymise IP addresses, and ensure that event data does not include personally identifiable information unless explicitly consented to. Firebase data can be exported to BigQuery in real time, giving you full ownership and control of raw event data for compliance, backup, or integration with data warehouses and BI tools. This flexibility makes Firebase attractive for teams that need to combine analytics with CRM, revenue, and operational data.

GA4 vs Firebase Analytics for web, app, and cross platform products

When deciding what is the difference between GA4 and Firebase Analytics and which to use, the most important factor is whether your product is primarily web, primarily mobile, or a mix of both. Each scenario has different implementation requirements, reporting needs, and team ownership models. A pure web product should use GA4 with gtag.js or Google Tag Manager. A pure mobile app should use Firebase Analytics, optionally linked to GA4 if you need audience export or attribution reporting. A cross-platform product with web and mobile needs both, implemented carefully to ensure consistent event naming and user identification.

For growth teams in Belgium and the wider European market, it is common to work with SaaS products that have a marketing website, a web app, and native iOS and Android apps. In this scenario, you typically implement GA4 on the marketing website and web app using Google Tag Manager, and Firebase Analytics in the mobile apps, linked to the same GA4 property. This gives you unified reporting in GA4, where you can analyse user journeys that start on web and continue on mobile, or vice versa. However, you must configure user identification via User-ID in both GA4 and Firebase to enable cross-device tracking, and you must respect GDPR consent settings consistently across platforms.

Choosing for pure web or marketing sites

If your business operates a marketing site, blog, or web-based SaaS platform without a mobile app, GA4 is the clear choice. Implement GA4 using gtag.js via Google Tag Manager, which allows your marketing team to add, edit, and test tags without deploying code. Configure enhanced measurement to automatically track scrolls, outbound clicks, site search, video engagement, and file downloads. Define custom events for form submissions, demo requests, lead magnets, and trial signups, and mark these as conversions in GA4.

Connect GA4 to Google Ads to import conversions and build remarketing audiences. Use GA4's attribution reports to understand which channels, campaigns, and keywords drive the most valuable conversions. Export data to BigQuery if you need to combine GA4 data with CRM, email, or revenue data in your data warehouse. For pure web businesses, Firebase is irrelevant unless you plan to launch a mobile app in the future, in which case you should design your event naming and parameter structures with Firebase compatibility in mind.

Choosing for mobile apps and in app behaviour

If you operate a mobile-first product such as a consumer app, game, or utility, Firebase Analytics is the best choice. Integrate the Firebase SDK into your iOS and Android apps using Swift, Kotlin, or a cross-platform framework like Flutter. Configure automatic event collection and define custom events that capture user actions specific to your app, such as level_up, share_content, or subscription_renewal. Use user properties to segment users by subscription tier, engagement level, or feature usage.

Enable Firebase Remote Config to personalise in-app experiences based on user properties or A/B test features without deploying new app versions. Use Firebase Crashlytics to correlate crashes with specific events or user segments, helping you prioritise bug fixes based on business impact. Link your Firebase project to a GA4 property if you need to export audiences to Google Ads or if your marketing team requires polished reports, but the Firebase console should remain the primary interface for product managers and developers.

Choosing for cross platform funnels and user journeys

Cross-platform products are the most complex scenario, and they require careful planning to ensure that what is the difference between GA4 and Firebase Analytics does not become a source of confusion or data fragmentation. A typical cross-platform funnel might look like this, a user discovers your product via Google Ads, lands on your marketing website, signs up for a trial, downloads the mobile app, completes onboarding, and makes an in-app purchase. To measure this journey, you need GA4 tracking on the website and Firebase Analytics in the mobile app, linked to the same GA4 property.

Implement user identification by passing a User-ID from your authentication system to both GA4 and Firebase. On the website, set the user_id parameter in gtag when a user logs in. In the mobile app, call setUserId in the Firebase SDK. This enables GA4 to stitch sessions across devices and platforms. Define a shared event taxonomy with consistent event names, parameters, and user properties across web and app. For example, if you log a sign_up event on web, use the same event name in the mobile app, and ensure that parameters like method and user_type match. Inconsistent naming breaks funnels and makes it impossible to compare performance across platforms.

Implementation choices: GA4 only, Firebase only, or both

Many teams wonder whether they should run GA4 and Firebase Analytics in parallel, use only one, or migrate from one to the other. The answer depends on your product architecture, team structure, and measurement goals. Running both is the most common pattern for cross-platform products, but it introduces complexity and requires governance to avoid duplication, drift, and technical debt. Running only GA4 is simpler for web-first businesses and teams that prioritise marketing attribution over developer tooling. Running only Firebase is appropriate for mobile-only products where the marketing team does not need GA4's reporting and audience export features.

If you choose to run both, you must decide whether to send all events to GA4 via the Firebase link, or implement GA4 separately on web and link Firebase only for mobile. The former is simpler but gives you less control over web tracking. The latter is more flexible but requires maintaining separate implementations. In either case, you should document your event taxonomy, establish naming conventions, and enforce governance through code reviews, automated tests, or a centralised tracking plan tool.

When to run GA4 and Firebase Analytics in parallel

Running GA4 and Firebase Analytics in parallel makes sense when you have a product with meaningful usage on both web and mobile, a marketing team that needs GA4 for attribution and audience export, and a product or engineering team that relies on Firebase for feature flags, crash reporting, and performance monitoring. In this scenario, implement GA4 on your website using Google Tag Manager, integrate the Firebase SDK into your mobile apps, and link Firebase to the same GA4 property so that mobile events appear in GA4 reports alongside web events.

This setup allows your marketing team to view unified funnels in GA4, build cross-platform audiences, and optimise campaigns based on lifetime value. Your product and engineering teams can use Firebase DebugView to validate tracking during development, Firebase Remote Config to test new features with subsets of users, and Firebase Crashlytics to identify which events or user segments experience crashes. The key risk is data inconsistency. If your web and mobile implementations use different event names or parameters for the same action, GA4 reports will be fragmented, and funnels will show drop-offs that do not reflect real user behaviour.

Dual tagging strategy and common pitfalls

Dual tagging refers to implementing both GA4 and Firebase Analytics in parallel and ensuring that events, parameters, and user properties are consistent across both. This requires a shared tracking plan that documents every event, its purpose, the platforms where it should fire, the parameters it should include, and the user properties that should be set. Without a tracking plan, teams tend to implement web and mobile tracking independently, resulting in event names like form_submit on web and formSubmit on mobile, or purchase on web and in_app_purchase on mobile. These inconsistencies break cross-platform funnels and make it impossible to compare performance.

Another common pitfall is duplicating events when Firebase is linked to GA4. If you fire a purchase event in your mobile app using the Firebase SDK, and you also fire a purchase event in GA4 via a separate Google Ads conversion tag, the same purchase may be counted twice in GA4 reports. To avoid this, rely on the Firebase SDK for all mobile tracking and link Firebase to GA4, or use GA4's Firebase integration exclusively and disable any duplicate tags. Test your implementation using GA4's DebugView and Firebase's DebugView before deploying to production, and validate that events fire once and only once per user action.

Migrating from Universal Analytics or legacy Firebase

Universal Analytics was sunset in July 2023, forcing all web properties to migrate to GA4. Many teams delayed migration and now face gaps in historical data, broken reporting, and inconsistent tracking. If you are migrating from Universal Analytics to GA4, start by mapping your Universal Analytics goals and events to GA4 conversions and custom events. Universal Analytics used pageview, event, transaction, and social hits, while GA4 uses only events with flexible parameters. For example, a Universal Analytics event with category, action, and label maps to a GA4 event with custom parameters.

If you are migrating from a legacy Firebase project that predates the Firebase-GA4 integration, you need to link your Firebase project to a new or existing GA4 property. This is done in the Firebase console under Project Settings, and once linked, Firebase events automatically flow into GA4. However, historical data in the old Firebase project does not migrate to GA4. You should export Firebase data to BigQuery before linking to ensure you retain access to historical events for analysis or compliance. For teams deciding what is the difference between GA4 and Firebase Analytics during migration, the key point is that GA4 is the successor to Universal Analytics for web tracking, and Firebase Analytics is the successor to older Firebase projects that sent data to Firebase-only reports.

Analytics strategy for growth teams in Europe

Growth teams in Europe face unique challenges when implementing GA4 and Firebase Analytics. GDPR requires explicit user consent before collecting personal data, and regulators in several EU countries have ruled that using GA4 without consent or adequate safeguards can violate GDPR because data is transferred to US servers. Server-side tracking, consent mode, and data anonymisation are now essential components of any compliant analytics strategy. Understanding what is the difference between GA4 and Firebase Analytics also means understanding how each tool handles consent, data residency, and privacy by design.

For growth teams working with B2B SaaS or ecommerce clients, analytics should not exist in isolation. GA4 and Firebase events should flow into a data warehouse where they can be combined with CRM data, revenue data, and product usage data to build attribution models, customer lifetime value calculations, and cohort analyses. This requires BigQuery exports, ETL pipelines, and a data team or partner that can design and maintain the infrastructure. At 6th Man Digital, we help growth-minded businesses design and implement analytics architectures that support experimentation, attribution, and decision-making while respecting European privacy regulations.

Event naming conventions and data governance

Event naming conventions are the foundation of scalable analytics. Without clear conventions, teams create inconsistent event names like btn_click, button_click, and click_button for the same action, which fragments reporting and makes it impossible to trust the data. GA4 and Firebase both recommend using snake_case for event names and parameters, and Google provides recommended event names for common actions like login, sign_up, search, add_to_cart, and purchase. Use recommended events whenever possible because they unlock enhanced reporting features in GA4 and ensure compatibility with future platform updates.

For custom events, define a naming taxonomy based on object-action or action-object patterns. For example, product_view, product_add_to_cart, and product_purchase follow an object-action pattern, while view_product, add_product, and purchase_product follow action-object. Choose one pattern and enforce it across all platforms. Document every event in a tracking plan spreadsheet or tool, and include columns for event name, description, platforms, parameters, parameter types, and example values. Require developers and marketers to reference the tracking plan before adding new events, and enforce governance through code reviews and automated tests that validate event structure before deployment.

Consent, GDPR, and server side tracking basics

GDPR requires that you obtain user consent before setting cookies or collecting personal data via analytics tools. GA4 and Firebase both support consent mode, which adjusts how data is collected based on whether the user has granted consent for analytics and advertising cookies. If the user declines consent, GA4 and Firebase switch to cookieless measurement and send anonymised pings to estimate conversions and traffic without tracking individual users. This degrades data quality but ensures compliance.

Server-side tracking offers a more privacy-friendly alternative to client-side analytics. Instead of loading the GA4 or Firebase SDK directly in the browser or app, your server receives events from the client, validates and enriches them, and forwards them to GA4 or Firebase via the Measurement Protocol. This gives you control over what data is sent, allows you to anonymise IP addresses and user identifiers before transmission, and reduces the risk of data being blocked by ad blockers or browser privacy features. Server-side tracking requires engineering effort and infrastructure, but it is increasingly necessary for European businesses that want accurate analytics without violating GDPR.

Combining GA4, Firebase, and business data in dashboards

GA4 and Firebase Analytics are powerful for understanding user behaviour, but they do not tell the full story. To understand business impact, you need to combine analytics data with revenue, customer acquisition cost, churn, lifetime value, and operational metrics. This requires exporting GA4 and Firebase data to BigQuery, joining it with data from your CRM, payment processor, email platform, and customer support system, and building dashboards in Looker Studio, Tableau, or a similar BI tool.

For example, a typical growth dashboard for an ecommerce business might show sessions and conversions by channel from GA4, joined with revenue and order value from Shopify, joined with customer lifetime value calculated from subscription renewal events in Firebase and payment data from Stripe. Building these dashboards requires SQL skills, data modelling, and an understanding of how to join datasets based on user IDs, session IDs, or timestamps. At 6th Man Digital, we help clients design and implement these integrations, ensuring that data flows smoothly from GA4 and Firebase into their data warehouse and BI tools, and that dashboards provide actionable insights that inform campaign optimisation, product development, and paid media strategy.

How 6th Man Digital chooses between GA4 and Firebase Analytics

At 6th Man Digital, we approach analytics strategy from a business outcome perspective, not a tool-first perspective. When a client asks us to recommend GA4, Firebase Analytics, or both, we start by understanding their product architecture, their team structure, their growth goals, and their current analytics setup. We ask questions like, do you have a mobile app, a web app, or both? Who will use the data and what decisions will they make? What are your current tracking gaps and pain points? Are you compliant with GDPR, and do you have consent management in place?

Our recommendations are pragmatic and opinionated. We do not believe in over-engineering analytics stacks or implementing tools just because they are popular. We prioritise speed, simplicity, and data quality, and we help clients avoid the common mistake of running parallel implementations that produce conflicting data. For most B2B and ecommerce clients in Belgium and Europe, we recommend GA4 for web tracking, Firebase Analytics for mobile tracking if they have an app, and BigQuery for data export and long-term storage. We help clients implement server-side tracking where necessary, design event taxonomies, and build dashboards that connect analytics to revenue.

Typical scenarios with B2B and ecommerce clients

For a B2B SaaS client with a marketing website and a web app, we implement GA4 using Google Tag Manager for the marketing site and GA4 for the web app, with user identification via User-ID to track the journey from visitor to trial to paid customer. We connect GA4 to Google Ads and LinkedIn Ads to import conversions and measure campaign ROI. We export GA4 data to BigQuery and join it with CRM data from HubSpot or Salesforce to calculate customer acquisition cost by channel, lifetime value by cohort, and conversion rates by landing page and traffic source.

For an ecommerce client with a Shopify store and native mobile apps, we implement GA4 on the Shopify store using Google Tag Manager and Shopify's built-in GA4 integration, and Firebase Analytics in the mobile apps linked to the same GA4 property. We configure the purchase event with transaction_id, value, and item parameters on both platforms, and we validate that purchases are not duplicated in GA4 reports. We build dashboards in Looker Studio that show revenue by channel, product performance, and customer cohorts, combining GA4 data with order data from Shopify and subscription data from Recharge.

Our process to audit your current analytics setup

Our analytics audit process starts with a kickoff call to understand your business model, growth goals, and current tracking setup. We request access to your GA4 property, Firebase project, Google Tag Manager container, and any data warehouse or BI tools you use. We review your event taxonomy, check for data quality issues like missing parameters, duplicated events, or inconsistent naming, and identify gaps in your tracking such as missing conversion events or broken funnels. We also review your consent management setup, data retention policies, and GDPR compliance.

We deliver a written audit report with findings, recommendations, and a prioritised roadmap. The roadmap typically includes quick wins that can be implemented in one to two weeks, such as fixing broken tags or adding missing conversion events, and longer-term improvements such as migrating to server-side tracking, exporting data to BigQuery, or redesigning your event taxonomy. We can implement the roadmap ourselves as part of an embedded marketing team engagement, or we can hand off the roadmap to your internal team with documentation and support. Either way, our goal is to ensure that your analytics setup is accurate, compliant, and decision-ready.

What you gain from an embedded analytics and growth team

Working with 6th Man Digital means you get senior-level analytics and growth expertise without the overhead of hiring full-time specialists. We operate as an extension of your team, attending your stand-ups, using your project management tools, and aligning our work with your quarterly goals. We bring cross-vertical experience from ecommerce, B2B SaaS, and service businesses, and we apply best practices from each vertical to accelerate your growth without the trial and error that comes with building an analytics practice from scratch.

Our embedded model is especially valuable for companies that need to move fast but do not have the budget or headcount for a full in-house data and analytics team. We set up your tracking, build your dashboards, design your experiments, and train your team to maintain and improve the setup over time. We do not lock you into long-term contracts or hide our methods. Our goal is to make your team self-sufficient while providing ongoing support for complex projects like server-side tracking, attribution modelling, or data warehouse integration. If you are deciding what is the difference between GA4 and Firebase Analytics and need help choosing and implementing the right stack, we can deliver a working solution in weeks, not months.

Talk to 6th Man Digital about your analytics setup

Choosing the right analytics setup is only the first step. The real value comes from implementing it cleanly, structuring events so they support experimentation and attribution, and maintaining data quality as your product evolves. Most companies struggle not with the choice between Google Analytics and Firebase Analytics, but with the execution, governance, and long term maintenance that turn tracking into insight.

That is where a lean, embedded team makes the difference. At 6th Man Digital, we help growth minded businesses in Belgium and across Europe design and implement analytics stacks that drive decisions, not confusion. We work with founders, marketing managers, and product owners who need accurate data without the overhead of a full in house analytics team. We handle the technical setup, event design, consent flows, and data integrations so you can focus on growth experiments and business outcomes.

We bring senior level expertise in both the marketing and technical side of analytics. We understand how to bridge the gap between marketing teams who need conversion funnels and attribution in GA4, and development teams who rely on Firebase Analytics for in app behaviour and crash tracking. We help you choose the right implementation for your product, avoid dual tagging pitfalls, and integrate your analytics data into dashboards and business intelligence tools. We also ensure your setup respects GDPR requirements, implements proper consent flows, and uses server side tracking where needed to improve data quality and privacy compliance.

Our process starts with a practical audit of your current analytics setup. We identify what is working, what is broken, and what is missing. We map out your user journeys, define the events and parameters that matter for your growth strategy, and build a clean implementation plan. Then we execute it, working side by side with your team as if we were part of your business. No long timelines, no junior staff, no surprises. Just clear reporting, transparent pricing, and measurable results.

If you are building a mobile app, scaling an e-commerce store, or managing a cross platform SaaS product and you need analytics that actually support growth, we can help. Whether you need to choose between GA4 and Firebase Analytics, implement both tools together, migrate from Universal Analytics, or integrate your analytics data with CRM and revenue systems, we have done it before and we know how to do it fast.

Understanding what is the difference between GA4 and Firebase Analytics is important, but applying that knowledge to your specific product, user journeys, and business model is what drives results. That is what 6th Man Digital does. We are your on demand marketing team, embedded in your workflow, obsessed with data quality, and focused on helping you grow smarter and faster. If you want to get your analytics setup right and start making decisions based on reliable data, talk to 6th Man Digital about your analytics setup and let us show you how a lean, expert led team can transform your measurement strategy.