Jira Service Management satisfaction report via JQL search and export

Summary

The standard Jira Service Management Customer Satisfaction report aggregates results and limits filtering, making it hard to isolate segments (e.g., by project, request type, time window, agent, or organization). Instead, if you export the matching issues to CSV, and then analyze CSAT fields in a spreadsheet or BI tool, you'll have the ability to filter, pivot, and validate more accurately based on the data.

We are tracking interest in improving JSM satisfaction reports as a feature request: JSDCLOUD-4749 - Export Satisfaction Report. The approach in this article is recommended when you:

• Need a granular CSAT segmentation beyond the built-in report.

• Want to audit how many responses are included and which issues contributed to averages.

• Plan to join CSAT with other operational fields (SLA breaches, components, labels) for deeper insights.

Solution

Our suggested approach involves three main steps:

1. Identify the JQL that represents your target dataset

2. Export the issues to CSV using this JQL

3. Analyze and filter in your spreadsheet or Business Intelligence (BI) tool

Identify dataset

1. Open Issue Navigator.

2. Write JQL that matches the issues you need to evaluate for CSAT.

   • For example, you can filter by project, resolution date range, request type, assignee group, or organization.

   • Ensure the JQL mirrors the scope you would use in the report.

Here's an example of JQL you could use to gather a dataset:

Export issues

1. From the search results page, choose Export > CSV (All fields) or CSV (Current fields).

   • Use Current fields for a focused dataset of only certain issue fields based on your Column selection.

2. Verify the row count in the CSV matches the count in the Issue Navigator to confirm parity.

Analyze in spreadsheet or BI tool

Here are some suggestions for how to analyze our exported data. You can:

• Create filters or pivot tables to slice CSAT by request type, team, time period, and organization.

• Calculate averages, medians, response distributions, and identify outliers using rating and comment text.

Alternative solutions

Other options to help analyze customer satisfaction from JSM data include:

• Save satisfaction comment in a custom field

• Export of Customer Satisfaction Rating and Comment via API