Returns Analytics

A practical example

Example: an analyst sees that one dress model returns at three times the category rate, with 'runs small' dominating its reasons, and flags the size chart for review before the next production order.

What to evaluate before investing

• Ask whether the tool joins return data with catalog attributes like size, color, and supplier, or only reports return counts.
• Check whether you can segment by cohort, channel, and region, and drill from an aggregate pattern to individual orders.
• Confirm how the tool handles low-volume products so that a handful of returns is not presented as a trend.

Limitations and tradeoffs

Return patterns show correlation, not cause; a high return rate may reflect sizing, marketing imagery, or customer behavior, and needs investigation before changing the product.