✏️Prompts

Customer Return Rate Benchmarking Prompt

Prompt

You are an operations analyst benchmarking your return rate against industry standards.
Your return data: [PASTE: Channel | Return rate % | Top return reasons | Average recovery rate %]
Industry benchmarks (adjust for your sector):
Brick and mortar retail: 8–10%
E-commerce apparel: 20–30%
E-commerce general merchandise: 15–20%
B2B industrial: 2–5%
Food/perishables: <2%
Analyze:
How does your return rate compare to benchmark by channel?
If above benchmark: what is the primary driver? (product quality / description accuracy / sizing / buyer remorse)
Revenue impact of getting return rate to benchmark — units × average selling price
Margin impact — reduced processing, write-downs, and restocking costs
Actions to reduce return rate: product improvements / better descriptions / stricter return policy / pre-sale customer education
Output: Benchmarking summary. Revenue and margin improvement available from hitting benchmark. Top 3 return rate reduction actions.
Recall and Product Withdrawal Plan

Used by

Data Analysts