Average Return Order Items Metric
Essential knowledge
Intended Audience:
Business User
Author:
Holger Lierse
Changed on:
23 Oct 2025
Overview
Learn about the Average Return Order Items Metric in Fluent Analytics
Key points
- Multi-item returns increase processing complexity and costs
- May indicate systemic fulfillment or quality issues
- Return item patterns can guide process improvements
What it measures
Average number of items per return order.
When to use this metric
- Monitor return complexity and processing requirements
- Assess customer return behavior patterns
- Plan return processing capacity and workflows
- Evaluate product bundling impact on returns
How to interpret
- Good performance: Low items per return indicates isolated product issues
- Potential issues: High items per return may suggest order fulfillment problems
- Benchmark guidance: Should be lower than average order items
Technical details
Formula:
COUNT(returnOrder.items) / COUNT(returnOrders) where status = {COMPLETE_STATUS} within the selected time period
Configurable elements:
- COMPLETE_STATUS: Status definitions for complete fulfillments (default: COMPLETE)
