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Google Analytics 4 vs PostHog

Side-by-side feature matrix for these two tools with per-row priority sliders. Adjust weights in the last column to recalculate System SCORE instantly.

Full category matrix: Product Analytics

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Features Google Analytics 4 PostHog Your Priority
Actions Visit Website ↗ Visit Website ↗ Priority controls
Custom Event & Parameter Tracking The platform offers a highly flexible, parameter-based event model to track any specific user interaction. Instead of traditional category-action-label hierarchies, users define custom event names and append specific key-value parameters. The platform uses a flexible event-based schema that uniquely combines automatic frontend capture (autocapture) with precise custom instrumentation.
10
0 10
Funnel & Drop-off Analysis Users can build custom funnel explorations to track sequential user steps and identify drop-off rates across any combination of events. Users can build complex conversion funnels with advanced features like strict step-ordering, time-to-convert metrics, and direct links to session recordings.
10
0 10
E-commerce Tracking E-commerce tracking provides a dedicated, structured schema for tracking the complete e-commerce lifecycle, from item views and cart additions to final purchases and refunds. While it lacks predefined retail templates, e-commerce workflows can be deeply analyzed using its flexible custom event schema and conversion funnels.
10
0 10
Identity Resolution The platform uses a blended approach, prioritizing user-provided IDs, then vendor signals, and finally device IDs to deduplicate users across devices. The platform handles cross-device tracking by allowing developers to explicitly map anonymous session IDs to authenticated internal user IDs.
10
0 10
GDPR / CCPA Compliance out-of-the-box Its compliance features offers features like Consent Mode, IP redaction, and data deletion requests, but full compliance relies heavily on proper implementation by the user. The platform offers EU data residency and open-source deployment options to ensure strict compliance with global privacy regulations.
10
0 10
Mobile app analytics App tracking is handled natively through deep Firebase integration, providing a unified reporting structure for both web and mobile platforms. This mobile analytics capability provides robust support for mobile app measurement via dedicated SDKs, unifying mobile behavior, feature flags, and session replays.
10
0 10
Audience Segmentation Users can create highly specific audience segments based on behavior, demographics, and predictive metrics, which seamlessly sync with Google Ads. Users can build highly complex, dynamic behavioral cohorts and instantly use them to target A/B tests or feature flags.
10
0 10
Cookieless Ping / Consent Mode This platform utilizes Consent Mode to send anonymized, non-identifiable data signals when users deny cookie tracking. These signals feed into machine learning models to fill measurement gaps rather than tracking individual user journeys.
9
0 10
Path Exploration / User Flows The pathing tool visualizes the sequential flow of users through a site or app, starting from a specific event or working backward from a conversion. The Paths tool visualizes organic user navigation, allowing teams to map journeys based on pageviews, custom events, or screen names.
9
0 10
Cohort & Retention Analysis The cohort tool enables teams to group users by shared characteristics (like acquisition date) to track retention, engagement, and conversion decay over time. The platform provides robust cohort and retention analysis, allowing teams to group users by complex behavioral triggers over customized timeframes.
9
0 10
Attribution Modeling The platform uses data-driven, machine learning models to distribute conversion credit across multiple marketing touchpoints in a user's journey.
9
0 10
Raw Data Export (BigQuery/S3) Users can export their complete, unsampled event data seamlessly and at no additional platform cost via a native integration with Google BigQuery. The Data Pipelines feature allows seamless, automated export of raw, unsampled event data to external warehouses like BigQuery or S3.
9
0 10
Native SDKs Mobile app measurement is supported through dedicated Firebase SDKs for both iOS and Android environments. It features automatic logging for standard app interactions alongside the ability to define custom events. The platform offers an extensive suite of open-source SDKs for web, mobile, and backend environments, deeply integrated with feature flags and session recording.
8
0 10
Data Sampling Control To maintain platform speed during complex queries on large datasets, the system applies data sampling, estimating results based on a subset of data.
8
0 10
Proxy Deployment / Custom Domain Through Server-Side Google Tag Manager, businesses can route their tracking data through a first-party server before it reaches the analytics platform.
8
0 10
Data Retention Limits Administrators can configure how long user-level and event-level data is stored before it is automatically deleted from the platform's servers. Data retention policies are flexible, with standard cloud plans offering 1 to 7 years of retention, and self-hosted instances providing limitless storage.
8
0 10
Custom Dashboard Builder Native dashboard capabilities are limited to customizing standard reports and creating Explorations. For comprehensive, executive-level dashboards, users must rely on the native integration with Looker Studio. Dashboards are highly customizable, collaborative workspaces that support SQL queries, Markdown text, and embedded session recordings.
7
0 10
Real-time Reporting Live data monitoring provides a snapshot of current active users, their geographic locations, and the events they are triggering within the last 30 minutes.
7
0 10
Custom Data Models Custom data modeling operates entirely on an event-driven schema, allowing for unlimited custom event definitions rather than relying on rigid session tracking.
7
0 10
Automated Schema Management The Data Management feature provides a centralized dictionary to verify, annotate, and govern custom events and properties across the organization.
7
0 10
Built-in A/B Testing The experimentation framework uniquely integrates A/B testing and multivariate experimentation directly into the analytics platform alongside feature flags and session replay.
7
0 10
Bot Filtering Automated filtering actively excludes traffic originating from known web spiders and bots based on internally maintained lists. This feature operates entirely in the background and cannot be customized or disabled by the user.
6
0 10
Anomaly Detection The platform utilizes machine learning to automatically establish baselines and flag statistically significant deviations in core metrics like traffic or revenue. Anomaly detection automatically highlights statistical outliers in event trends and correlates them directly with qualitative session recordings.
6
0 10
Predictive Analytics (Churn/LTV) Machine learning models automatically predict future user actions, such as purchase probability or churn risk, based on historical behavior patterns.
6
0 10
SSO Support Single Sign-On (SSO) is supported via Google Workspace or Cloud Identity, allowing enterprise teams to centralize authentication and access control. Secure access is managed through native SAML 2.0 Single Sign-On, allowing seamless integration with corporate identity providers like Okta or Azure AD.
6
0 10
Pre-built Industry Templates The platform offers a basic set of report collections and exploration templates tailored to general use cases, rather than highly specialized industry frameworks.
5
0 10
System SCORE 6.8 / 10 5.8 / 10

Make your pick

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Google Analytics 4

Google Analytics 4 is a robust analytics platform that offers real-time insights and advanced features to track user behavior across websites and apps.

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PostHog

PostHog is a powerful, self-hosted analytics platform designed to provide deep insights into user behavior with a highly customizable and privacy-focused approach.

Visit Website ↗ Read Full Review