What ticket analysis is
Reading customer-submitted issues as one body of evidence, to find recurring problems, product gaps and what is worth fixing first.
Findings · Support ticket analysis
Analyze Support Tickets for Insights
Upload a ticket export or connect Zendesk or Intercom. Usercall groups the tickets into themes and keeps the original messages behind each one. Recurring issues show up in minutes.
Free to start25+ languagesEvery theme opens to its quotes
What you can learn
Read the tickets together. See what keeps coming back.
Agents read tickets to close them. Patterns only appear when hundreds are read side by side, and that is the part nobody has time for.
Themes, not tickets
A theme is a group of tickets with the same underlying cause. It gives product and support a ranked list instead of a pile of one-offs.
The why behind the numbers
Metrics say how many customers churned. Tickets say why, in the customer's own words.
Who uses it
Product managers, customer success leads and UX researchers. Anyone who has to defend a roadmap choice with evidence.
What the AI does
Reads, tags and groups every ticket. You get the top themes in minutes and keep the final say on each one.
From a real report
Themes tied to quotes. Nothing invented.
Every theme opens to the tickets behind it. This is the theme map from a real shared report, not a mock-up.
Usercall does not paraphrase. Each theme keeps its count, its source and the original words, and a finding is flagged when the evidence is thin.
Theme map from a shared Usercall report. Every theme opens to the quotes behind it.
How it works
Bring the data. Read the patterns.
The AI does the first pass the way an experienced researcher would. You keep the final call on every theme.
1
Connect your ticket source
Sync Zendesk or Intercom, or upload a .csv export. Historical and new tickets land in one project.
2
Get the first pass
Usercall reads every ticket and groups them into named themes, with counts and the original messages.
3
Refine and share
Merge, split and rename themes. Flag weak findings. Share a report your team can check against the tickets.
By outcome
Start from the outcome. Pick what you need to find.
Each page below covers one source and one question, with the steps for that case.
Product issues
The bugs and gaps customers report most
Churn signals
Frustration that shows up before a cancellation
Feature requests
What customers keep asking for
Knowledge base gaps
Questions a help article should answer
Zendesk tickets for product issues
The same analysis on a Zendesk export or sync
Zendesk tickets for feature requests
Requests grouped and counted from Zendesk
Intercom conversations for support trends
Recurring trends across chat conversations
Help desk tickets for automation
Repeat requests a macro or a bot could handle