Return Reason Ratio Metric
Essential knowledge
Intended Audience:
Business User
Author:
Holger Lierse
Changed on:
19 Jan 2026
Overview
Learn about the Return Reason Ratio Metric in Fluent AnalyticsKey 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
Domain:`return_order`Formula: COUNT(returnOrder) where returnOrder.status = {STATUS_COMPLETE} grouped by returnReason within the selected time periodReference Filter Parameters:
`return_order.created_date`: Filters the metric to return orders created within the selected time period`return_order.status`: {STATUS_COMPLETE} - Status definitions for complete returns (default: COMPLETE)`return_order.type`: Filters the metric to return orders of specific order types`retailer.ref`: Filters the metric to return orders from the selected retailer
