Cluster Bug Reports From Tickets
Every morning, WebRun scans Intercom conversations tagged as bugs, groups them by the underlying error or symptom, creates or updates a Jira issue per cluster with the affected customer count, and posts a prioritised bug-cluster report to your #engineering Slack channel.
How can I automatically cluster bug reports from support tickets?
Every morning, WebRun scans Intercom conversations tagged as bugs, groups them by the underlying error or symptom, creates or updates a Jira issue per cluster with the affected customer count, and posts a prioritised bug-cluster report to your Slack #engineering channel - so engineers know which bugs are hitting the most customers.
- Bugs grouped by symptom so engineers see real impact at a glance
- Jira issues created or updated automatically with affected customer counts
- Prioritised report in Slack before the engineering standup
Built for engineering teams · SaaS companies · product managers · support operations teams
What does WebRun do on every run?
The exact actions WebRun takes, in order - in plain language, so you can adjust anything.
-
WebRun signs in and gets to work
Opens
app.intercom.comin a real browser with your saved login - no setup, no API keys. -
1
Intercom - read and group bug-tagged conversations
intercom.com
WebRun opens Intercom to read and group bug-tagged conversations. - Open Intercom and filter conversations tagged 'Bug' or 'Error' created since the last run
- Read each conversation and extract: the error message or symptom, the product area, and the customer ID
- Group conversations by similar error signature or symptom using keyword overlap
Done when All bug-tagged conversations are read and grouped into clusters by shared symptom.
-
2
Jira - create or update a bug issue per cluster
atlassian.com
WebRun opens Jira to create or update a bug issue per cluster. - For each new cluster, create a Jira bug issue with the symptom as title and affected customer count in the description
- For existing Jira issues matching the cluster, update the affected-count field and add the new conversation IDs
- Set priority based on the customer count: P1 for 5+ affected, P2 for 2–4, P3 for 1
Done when Every bug cluster has a Jira issue with an up-to-date affected-customer count and priority.
-
3
Slack - post the ranked bug-cluster report
slack.com
WebRun opens Slack to post the ranked bug-cluster report. - Post today's bug-cluster report to #engineering sorted by affected-customer count
- Include a one-line symptom description and a Jira link for each cluster
Done when Engineering has a ranked bug report in Slack ready to act on.
How is each run configured?
Secure by default
Connect once, stays signed in
WebRun signs in once and keeps each session in a persistent environment, so every run picks up right where it left off.
Every action is checked against this policy before it runs.
Questions, answered
What if two clusters are really the same bug?
An engineer can merge the Jira issues manually; the next run will update the surviving issue with the combined count. You can also teach WebRun a canonical symptom phrase to pre-merge them.
Does it close Jira issues when a bug is fixed?
No - only engineers close Jira issues. WebRun only creates and updates them, so nothing gets closed automatically.
How far back does it look each morning?
It looks at conversations since the last run (default 24 hours). You can widen the window during a backlog catch-up.
Related templates
Put this on autopilot.
Turn it on in minutes - or have our team set it up for you.