Returns root-cause analysis
High return rates are hard to explain when reasons, product variants, and delivery events are disconnected.
The challenge behind the workflow.
High return rates are hard to explain when reasons, product variants, and delivery events are disconnected.
Connect demand, inventory, orders, fulfillment, and customer permissions. Give merchandising and operations teams a common view of what changed, where the data is incomplete, and which action needs review.
Data to bring together
- Return transactions
- Product attributes
- Delivery events
Source systems are examples of the data required. Confirm connector availability, permitted access, refresh timing, and the authoritative owner before implementation.
How Genedata supports the work.
Configure one connected workflow, then reuse its mappings, definitions, and review process as the business grows.
- 01
Connect and prepare
Standardize return reasons and connect each return to the original order and variant.
Build the preparation as a reusable visual workflow or reviewed code, with explicit source mappings and validation checks. - 02
Investigate and validate
Compare patterns across product cohorts, suppliers, and fulfillment conditions.
Keep shared definitions and source versions with the analysis so another team can reproduce the result. - 03
Publish and review
Publish a review dashboard with representative cases and source links.
Make the output available to the right people with appropriate access, ownership, and review evidence.
A returns investigation dashboard
Make the next run easier.
Shared return definitions help teams investigate causes without rematching orders.
Start from one approved example. Save the agreed mappings and definitions, publish the reviewed output, and let the next team follow the same evidence instead of rebuilding the preparation.
Measure your own improvement
Time to identify recurring return patterns
Record a baseline before the pilot and compare like-for-like work afterward. Results depend on source quality, configuration, and adoption.Review and responsibility
Review reason-code quality before attributing responsibility to products or suppliers.
AI with professional judgment.
Use AI to explain anomalies and draft planning commentary. Merchandising, pricing, customer outreach, and stock decisions stay with authorized teams.
Try the workflow with your team.
Use representative, approved sample data. Agree the expected output and a review owner before extending the workflow to a live process.