Return Reason Ratio Metric
Essential knowledge
Intended Audience:
Business User
Author:
Holger Lierse
Changed on:
16 Nov 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
Count of the number of completed return orders where the return orders where created in the selected time period, grouped by the return reasons
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(returnOrder) where returnOrder.status = {STATUS_COMPLETE} grouped by returnReason
within the selected time period
Configurable elements:
- STATUS_COMPLETE Status definitions for complete returns (default: COMPLETE)
Reference Parameters:
`return_order.created_date`: Filters the metric to return orders created within the selected time period`retailer.ref`: Filters the metric to return orders from the selected retailer`return_order.type`: Filters the metric to return orders of specific order types
