Recommended Issues

LogRocket uses machine learning to recommend certain issues that your team may consider to be severe. Our issue recommendation models are trained on data from LogRocket sessions and issues, and we use them to generate severity scores for your issues.


Recommended Issues is currently in Beta

Issues Severity Scores and Issues Digest are both currently in beta and are constantly improving. We'd love your feedback! Please reach out with feedback to [email protected].

Severity Scores

Issues with higher severity scores are more likely to be associated with user frustration and may indicate that users were prevented from completing an in-app task. Severity scores are computed over a time range (e.g., last day, last week) and may change as you select different time ranges. An issue's severity score is also more accurate when more data is available for it. If you see a message that LogRocket doesn't have enough data to assign a severity score to an issue, try increasing the time range or wait for more data to be collected.


Issue severity scores

Showing Recommended Issues Only

By default, LogRocket shows all issues sorted by severity score with recommended issues highlighted. When viewing untriaged issues, you can use the "Show recommended issues only" toggle to hide untriaged issues that aren't recommended.


"Recommended issues only" toggle

Issues Digest

LogRocket delivers a weekly Issues Digest to your Slack channel of choice. The digest is a summary of your app's top recommended issues from the last week. To set up Issues Digest, go to LogRocket Settings -> Issue Settings.


Issues Digest delivered via Slack integration

Making Recommendations Better

LogRocket's issue recommendations are constantly improving, and you can help! Use our issue triage features to teach LogRocket that an issue is or is not severe.

For example, if you agree that a recommended issue is severe, triaging it as "High" or "Low" impact will make those kinds of recommendations more likely in the future. If you don't think an issue should have been recommended to you, triaging it as "Ignored" will make those kinds of recommendations less likely in the future. Similarly, if you think LogRocket should have recommended an issue but it didn't, triaging it as "High" or "Low" impact will make it more likely that similar issues are recommended in the future. And if you agree that LogRocket correctly decided not to recommend an issue, triaging it as "Ignored" will help to reinforce that behavior.


Issue triage popover


Changing issue group conditions may change severity score

Keep in mind that customizing grouping conditions may cause the triaged issue's severity score to change.