Analytics
LogRocket - the practical guide.
LogRocket is session replay and frontend monitoring built primarily for engineers. Founded in 2016, it pairs the user-facing video of a session with the technical detail engineers need to debug it - console logs, network requests, Redux state, errors and performance traces - making it the closest thing to time-travelling into a user's browser when something breaks.
What LogRocket does
The core captures session replays alongside JavaScript errors, network failures, console output, Redux/Vuex/NgRx state and performance metrics. Engineers can jump from an error in their issue tracker straight to the exact moment the user hit it, with full context. Heatmaps, funnels and conversion analysis cover the product analytics side, though the centre of gravity is debugging and quality.
Galileo AI surfaces the most impactful issues automatically and writes plain-language summaries. Native integrations cover Sentry, Bugsnag, Jira, GitHub, Linear, Slack, Segment, Mixpanel, Amplitude and the rest of the dev and product stack, with a clean API and SDK coverage across web, React Native and native mobile.
Who it's for
Engineering, product and design teams at SaaS, ecommerce and consumer apps that want to close the loop between bug reports, frontend errors and what the user actually saw. Particularly strong for teams shipping React, Vue or Angular SPAs where state and console context are critical to debugging.
Pricing, in rough terms
Per month, billed annually, by session volume and tier (Free, Team, Professional, Enterprise). Free supports up to 1,000 sessions per month; Team starts around USD 99 per month; Professional and Enterprise are quote-based and scale into the thousands per month. Mobile, advanced AI and longer retention are usually priced separately.
When LogRocket is the right fit
The right call when engineering owns the tool, frontend bugs are hard to reproduce, and existing error monitoring (Sentry, Bugsnag) tells you what broke but not why. Also a sensible pairing with FullStory or Hotjar when product wants the qualitative UX side and engineering wants the technical depth. A weaker fit for marketing-led teams that just want heatmaps and recordings (Hotjar or Clarity), or for backend-heavy services with limited frontend complexity.
Watch-outs
Privacy and PII masking need careful setup before going live - the level of detail captured can become a liability if not configured properly. Session volume drives cost; sample aggressively in low-signal areas. Like all replay tools, value depends on engineers actually opening sessions when bugs come in - bake it into the triage workflow or it becomes shelfware.