LaunchDarkly Experimentation
Modernize product testing with feature-flag-driven A/B testing and Bayesian statistical analysis.
Real-time event-based analytics for builders to explore, analyze, and optimize user behavior.
Mixpanel is a premier event-based product analytics platform that has evolved by 2026 into a 'Warehouse Native' powerhouse. Its core technical architecture centers around 'Arbiter,' a proprietary columnar storage engine optimized for high-cardinality behavioral data. Unlike traditional BI tools that rely on aggregate SQL queries, Mixpanel's infrastructure allows for real-time exploratory analysis without pre-aggregating data. In 2026, the platform heavily leverages 'Spark AI,' a generative AI layer that converts natural language prompts into complex behavioral queries and predictive models. The platform's strategic shift toward Warehouse Connect allows enterprises to query data directly from Snowflake, BigQuery, and Databricks, eliminating the 'data silo' problem common in legacy analytics. This architecture supports sub-second latency for complex funnel and retention analysis across billions of events. Mixpanel maintains a dominant market position by bridging the gap between raw data storage and actionable product insights, providing non-technical stakeholders the ability to perform deep-dive data science tasks through an intuitive, visual interface.
A generative AI interface that allows users to query data using natural language, automatically generating charts and identifying correlations.
Modernize product testing with feature-flag-driven A/B testing and Bayesian statistical analysis.
Automated product analytics specifically designed for B2B SaaS teams.
The digital analytics platform that helps teams build better products through behavioral data and AI-driven insights.
Quantifying digital experiences through AI-driven behavioral heuristics and automated friction detection.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A zero-copy architecture that reads data directly from cloud warehouses like Snowflake and BigQuery.
A correlation analysis tool that identifies which user actions are most predictive of long-term retention or conversion.
Allows for the analysis of data at the 'Account' or 'Company' level rather than just individual users.
Measures the causal effect of a specific launch or experiment on a key metric using a 'Before & After' analysis with control groups.
A powerful JavaScript-based framework for running custom, complex analyses on raw event data.
Features like 'Lexicon' allow for renaming, hiding, and merging events and properties without changing code.
Identifying where users drop off during the multi-step registration process.
Registry Updated:2/7/2026
A/B test a change and measure impact.
Understanding the behavioral differences between users who renew and those who cancel.
Determining if a new feature release actually drove user value.