Attribution & Analytics
LogRocket
LogRocket is a digital experience platform centered on session replay, product analytics, and frontend issue diagnosis. It records user sessions alongside console output, JavaScript errors, network activity, performance details, and application state, then adds funnels, paths, cohorts, issue detection, search, integrations, and AI summaries to help teams locate consequential friction. It is best for product engineers, support teams, and product managers that need to reproduce user-reported problems and connect technical failures with conversion or engagement impact.
What it does
LogRocket is a frontend monitoring and product analytics platform that records real user sessions together with the technical context behind them. Each session replay is paired with console logs, JavaScript errors, network requests, Redux or state changes, and performance metrics, so teams can watch exactly what a user saw and why something broke. Product and growth teams use its analytics to build conversion funnels, segment users, and quantify how bugs or slow pages affect key flows. Engineers jump from a spike in errors straight to the replay that reproduces it. The combination shortens the loop between noticing a drop in conversions and finding the frontend cause.
Where it fits
It sits on your web or app frontend to connect what users experienced with the technical events behind a conversion problem.
Core features
- Session replay with synchronized console, network, and error data
- Frontend error tracking and issue grouping
- Product analytics funnels, retention, and segmentation
- Performance monitoring for slow pages and requests
- Heatmaps and click tracking on replayed sessions
- Alerting on error spikes and conversion anomalies
Best for
- Frontend engineers debugging hard-to-reproduce issues
- Product teams linking UX friction to conversion drops
- Growth teams diagnosing funnel leaks
Beginner notes
- Mask sensitive fields like passwords and payment data before recording in production.
- Start by replaying sessions that hit a known error to learn the workflow.
- Tie funnels to a single high-value flow first instead of instrumenting everything at once.