Ecommerce Task
Find product return causes
Connect return reasons to products and original customer comments. Choose one evidence-backed fix to test first.
“This is costing me margin and reverse-logistics work without telling me which product problem to fix.”
Outcome
The result to aim for
Identify recurring causes by product, inspect the supporting customer evidence, and test one measurable intervention.
Best practices
- Choose one comparable date range and the products or category you want to investigate.
- Choose the period, market, products and return state. Separate the quantity of goods physically returned from cancellations, edits and refunds without returned goods.
- Record the launch date and affected products. Compare the same cause and denominator over a suitable later window. Note changes to promotions, price, stock and policy.
- Confirm that the cohort contains physical returns and uses the same filters for return and sales data.
- If a category-specific issue falls under a generic code, refine the taxonomy and reclassify the affected rows.
Related sources
Further information
- Documented guidance: National Institute of Standards and Technology: Artificial Intelligence Risk Management Framework (AI RMF 1.0)
- Related guidance: Shopify: ShopifyQL returns fields deprecated and replaced with sales reversals fields
- Related guidance: Shopify: Better insights with category-specific return reasons
- Related guidance: Association for Computational Linguistics: Learning Reasons for Product Returns on E-Commerce