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LogRocket is most useful for us when a problem only makes sense after we’ve seen the exact sequence of state changes that led up to it. Being able to record Redux state and actions gives us that missing context, and pairing it with Frontend Performance Monitoring, heatmaps, clickmaps, rage clicks, and dead clicks helps us uncover issues that never throw a JavaScript exception. A page can return 200 on every request and still feel broken if a button looks clickable but does nothing, or if the interface takes too long to become usable. Because LogRocket captures performance, network activity, console logs, and user behavior through the same SDK, we can usually tell pretty quickly whether we’re dealing with a technical failure, a usability problem, or simply a confusing interaction. Product Analytics adds another helpful layer when the issue shows up inside a funnel: we can spot the drop-off, isolate the sessions that didn’t convert, and jump straight into replay instead of comparing dashboards across tools and then manually hunting down the same users. Review collected by and hosted on G2.com.

Logrocket is essential for all of the custom platforms our team has built. Our support team can watch users in real-time, or leverage the recorded sessions in order to troubleshoot. Logrocket has decreased the amount of time that it takes to look into an issue. Our team has also saved time since we hardly ever need to be on a screen share with users. Review collected by and hosted on G2.com.

Dislike that it only goes about one month back. It would be helpful to have 6 months to 1 year back for recordings. Unable to use Logrocket for Salesforce, if we could use it for Salesforce it would meet all of my current needs. Review collected by and hosted on G2.com.

What I like best about LogRocket is how it cuts out all the guesswork when our internal users run into weird frontend bugs on our in-house tools. I’m Lukas Ogod, Business Technology Specialist at Big Sky Digital Partners. Most days I’m rolling out new software, setting up user permissions, building reports, and troubleshooting workflows for our teams. We’ve got a bunch of custom internal portals our analysts and client services staff rely on every day, and before LogRocket, debugging these issues was such a slog. When someone submitted a support ticket saying a form wouldn’t submit, or a filter was acting strange, all I’d get was a vague description and maybe a blurry screenshot. I’d fire off follow-up messages asking what buttons they clicked, what browser they used, what they saw pop up in the console, and half the time they couldn’t remember all the details.

LogRocket’s session replay changes that completely. It records their full session, paired with network calls, console errors, and page timing data all in one place. A great example popped up about six weeks ago. A handful of our data analysts reached out saying they couldn’t export CSV files from our reporting dashboard. They kept clicking the export button, nothing would download, and they couldn’t tell me if there was an error message. Instead of going back and forth for hours, I pulled up their session replay in LogRocket right away. I watched them walk through the exact steps, spotted the failed API request buried in the network tab, and sent that full session link straight to our dev team. They reproduced the root cause in minutes and pushed a fix the same day. That would’ve easily taken us two or three days to sort out the old way.

I also really appreciate how easy it is to tag and filter sessions. If we roll out a new feature on our internal portal, I can pull sessions only from the teams that are testing it, watch how they navigate the new layout, and catch friction points before they blow up into a flood of support tickets. I don’t need a heavy engineering background to dig through the recordings either. The timeline lines up every click, error, and page load together, so I can triage issues quickly and decide what needs to go to devs immediately versus what’s just a user training gap.

The built-in PII redaction works well for our info services setup too. We handle sensitive client data inside those dashboards, so I don’t want raw customer names or numbers getting captured in replays. I configured the redaction rules during setup, and it automatically scrubs those fields out of recordings without extra manual work on my end. That takes a big weight off when I’m sharing session clips with the engineering team. Review collected by and hosted on G2.com.

Honestly, the biggest pain point for me with LogRocket is how clunky its alerting and rule setup can get when I’m trying to track issues specific to our internal business portals. I’m Lukas Ogod, Business Technology Specialist at Big Sky Digital Partners. My plate is always packed — rolling out new business tools, locking down user permission sets, building operational reports, and triaging all the odd bugs our internal teams run into on our custom dashboards. We don’t have a dedicated dev team standing by just for support triage, so I lean heavily on alerts to catch widespread breaking problems early, before they snowball into a huge backlog of support tickets from our analysts and client services staff.

A couple weeks back, I tried building an alert to notify our Slack channel when multiple users hit that same CSV export failure we ran into on the reporting dashboard. My goal was pretty straightforward: only trigger an alert if three or more people within our data analyst user group encountered that exact export error in a one-hour window. But the filtering logic was really rigid and finicky. I could easily target the basic error event, but stacking extra conditions — matching the correct user group, the specific dashboard page URL, and the occurrence threshold together — kept falling apart. It either went off for random, harmless one-off console warnings that didn’t impact anyone’s work, or stayed completely silent when the real export bug was actively hitting our team. At its worst, it spammed our shared Slack channel with 12 irrelevant notifications in a single afternoon, distracting everyone on the team. I had no choice but to delete that alert rule entirely. Now I end up hopping into LogRocket to manually scan for issues every day, which means some smaller but recurring bugs can sit unnoticed for much longer than they should.

I also hit frustrating limits when it comes to organizing and sharing session replays with our engineering teammates. I make sure to tag every recording by issue type — export bug, filter glitch, login error and so on — but there’s no built-in way to bundle a batch of related sessions into one neat shared case folder. If five different analysts submit tickets about the exact same dashboard problem, I have to copy out five separate replay links one by one and paste all of them into our support ticket thread. It gets disorganized fast. Our devs have told me more than once how tedious it is to jump between separate replay tabs to compare the user flows, and they’ve repeatedly asked for a cleaner way to pull up grouped, related sessions all in one view. It’s a small workflow gap on the surface, but it adds extra friction every time we’re investigating a widespread portal issue. Review collected by and hosted on G2.com.

It's super easy to use when we need to review a customer's session. We can pinpoint where issues occur and then using the developer tools, this information can be handed over to our dev time to resolve. I've contacted customer support previously about a change that was made in LogRocket that made the interface harder to use and they immediately responded, took the feedback on and reverted back to the previous state within a couple of days. Review collected by and hosted on G2.com.

The sessions need a unique identifier (like a number) The randomly generated animals are cute but not unique to each session. Review collected by and hosted on G2.com.

Session replay with the technical context attached. You see what the user did alongside the console logs, network requests, Redux/state changes, and DOM. That often turns “can’t reproduce” into a bug you can fix. Review collected by and hosted on G2.com.

It’s frontend-centric. You’ll still need backend APM or logging tools, so you end up correlating across tools. Review collected by and hosted on G2.com.

Being able to review the headers and body of network requests and responses easily from the main pane has helped cut down on debugging time immensely. It was easy to add into our tech stack after the initial setup, and it's intuitive enough for non-technical users on our team to get value out of as well. It's nice to be able to organize sessions by error, and being able to talk to the LogRocket AI has helped me interpret trending errors better. Review collected by and hosted on G2.com.

The descriptions of some errors are a bit exaggerated, and performance on some sessions tends to lag. One common issue I see is that we have an endpoint that returns a 400 by design, but it's picked up as a top-priority error. Review collected by and hosted on G2.com.

We've used other platforms in the past that were far more expensive and required extensive mapping and custom code to implement that did not offer the same level of detail as LogRocket. Immediately after adding the tracking snippet, we saw immediate results in more detail than our previous provider Pendo which required countless hours of mapping features and would break every time there was a UX update. Integrating LogRocket into our daily CS and Product analytics workflow only took about 15 minutes. Review collected by and hosted on G2.com.

I would like more of a focus on the analytics side of the process rather than the sessions but the data is there and retrievable. Review collected by and hosted on G2.com.

LogRocket is an integral tool for our product development. It allows us to replay user sessions and narrow in on hard-to-reproduce bugs and user behavior. Session replay allows us to pair factual data and actions with user feedback to triage and quickly find the root of a user's problem. We couldn't imagine creating and iterating on new products without it! Review collected by and hosted on G2.com.

LogRocket's additional features outside session replay are harder to set up and understand. We have not been able to fully maximize our platform use or find extra value outside of session replay, but this may vary depending on the use case. Review collected by and hosted on G2.com.

The filtering UI is very easy to use and much cleaner than competitors like DDRUM. Our support team refuses to walk away from logrocket when we tried to migrate to DDRUM citing cost issues. Discoverability is easy on LR. Review collected by and hosted on G2.com.

Nothing much, LR serves all our use cases Review collected by and hosted on G2.com.

It's gives the most detailed and most reliable session recordings out of all similar products we've tried (we tried Sentry and Posthog), is very useful for inspecting sessions and captures a huge amount of detail. The network traffic data is invaluable for seeing the API calls the user made at different times, with incredibly detailed timestamp information, which helps us map user behaviour to our logs. Review collected by and hosted on G2.com.

It can be hard to track exactly what's going on if the user is on multiple tabs or refreshes the page or does other weird things. Also sometimes sessions aren't linked to specific users so it's hard to track down certain users issues, but I think that may be the users privacy setting. Review collected by and hosted on G2.com.