Return Reason Ratio Metric
Essential knowledge
Intended Audience:
Business User
Author:
Holger Lierse
Changed on:
23 Oct 2025
Overview
Learn about the Return Reason Ratio Metric in Fluent Analytics
Key points
- Return reasons directly indicate improvement opportunities
- Customer-provided reasons may not always reflect actual issues
- Reason patterns can guide prevention strategies and process improvements
What it measures
Breakdown of return requests by customer-provided reason categories.
When to use this metric
- Identify root causes of customer returns
- Guide product improvement and quality control priorities
- Assess the accuracy of product descriptions and marketing
- Develop targeted return prevention strategies
How to interpret
- Good performance: Return reasons are diverse with no dominant negative patterns
- Potential issues: High concentration in quality or description-related reasons
- Benchmark guidance: Reason patterns should guide specific improvement actions
Technical details
Formula:
COUNT(orders) where status = {RETURNED_STATUS} grouped by returnReason within the selected time period
Configurable elements:
- RETURNED_STATUS: Status definitions for complete fulfillments (default: COMPLETE)
