Custom Event & Parameter Tracking Custom event tracking features an incredibly flexible, flat event taxonomy that allows product teams to define unlimited custom events with highly granular metadata. 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. Funnel & Drop-off Analysis This conversion analysis feature features one of the most powerful, highly customizable funnel analysis engines on the market, tracking conversion steps across any timeline or sequence. Users can build custom funnel explorations to track sequential user steps and identify drop-off rates across any combination of events. E-commerce Tracking While exceptionally strong at analyzing the purchase funnel, it requires custom event configuration rather than providing a pre-built retail schema. 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. Identity Resolution The platform uses a sophisticated ID resolution framework, automatically merging anonymous device IDs with authenticated User IDs into a single profile. The platform uses a blended approach, prioritizing user-provided IDs, then vendor signals, and finally device IDs to deduplicate users across devices. GDPR / CCPA Compliance out-of-the-box The platform provides robust data governance tools, including strict PII redaction and automated APIs to handle complex data deletion requests. 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. Mobile app analytics Mobile app analytics is a market leader in mobile app measurement, offering deep insights into complex in-app behaviors, lifecycle stages, and version adoption. App tracking is handled natively through deep Firebase integration, providing a unified reporting structure for both web and mobile platforms. Audience Segmentation Users can create highly dynamic behavioral segments based on intricate combinations of past actions, predicted behaviors, and user properties. Users can create highly specific audience segments based on behavior, demographics, and predictive metrics, which seamlessly sync with Google Ads. 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. Path Exploration / User Flows The Pathfinder tool visually maps all possible user journeys branching out from a starting event or converging toward a target goal. 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. Cohort & Retention Analysis Advanced cohort capabilities allow teams to group users by complex behavioral triggers and track their long-term retention and engagement decay. The cohort tool enables teams to group users by shared characteristics (like acquisition date) to track retention, engagement, and conversion decay over time. Attribution Modeling The platform uses data-driven, machine learning models to distribute conversion credit across multiple marketing touchpoints in a user's journey. Raw Data Export (BigQuery/S3) Enterprise users can seamlessly route raw, user-level event streams to external data warehouses like Snowflake or Amazon S3 via native pipelines. Users can export their complete, unsampled event data seamlessly and at no additional platform cost via a native integration with Google BigQuery. Native SDKs The platform offers extensive, highly reliable native SDKs for iOS, Android, and numerous other environments, designed specifically for product-centric event streaming. 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. 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. 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. Data Retention Limits The platform generally retains granular, user-level behavioral data indefinitely, supporting multi-year historical analysis for enterprise accounts. Administrators can configure how long user-level and event-level data is stored before it is automatically deleted from the platform's servers. Custom Dashboard Builder The platform offers dynamic, collaborative workspaces and custom dashboards tailored for cross-functional product and growth teams. 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. 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. Custom Data Models This schema design relies on a flat, highly flexible event-driven schema, completely replacing rigid session-based web analytics models. Automated Schema Management The native Data integration tool provides robust schema governance, automatically flagging unexpected events and preventing taxonomy bloat. Built-in A/B Testing Built-in A/B testing tightly integrates with a native Experiment module, allowing teams to analyze A/B test results using deep behavioral metrics. 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. Anomaly Detection Anomaly Detection automatically highlights statistically significant deviations in event volumes or conversion rates within standard trend charts. The platform utilizes machine learning to automatically establish baselines and flag statistically significant deviations in core metrics like traffic or revenue. Predictive Analytics (Churn/LTV) Machine learning models predict future user behavior, automatically generating cohorts of users with high probabilities of churn or conversion. Machine learning models automatically predict future user actions, such as purchase probability or churn risk, based on historical behavior patterns. SSO Support Secure enterprise access is managed through native SAML 2.0 Single Sign-On, integrating directly with major identity management providers. Single Sign-On (SSO) is supported via Google Workspace or Cloud Identity, allowing enterprise teams to centralize authentication and access control. 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.