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# Use Analytics to Improve Return Management

### Overview
Return data can help you identify operational and product issues.

For example:
* A high number of returns for one product may indicate a product-quality issue.
* Frequent size-related returns may indicate unclear sizing information.
* A high number of exchange requests may indicate that customers prefer replacements instead of refunds.
* Frequent return reasons can help you improve product descriptions.

**Step 1:** Review your most common return reasons.
![](https://storage.crisp.chat/users/helpdesk/website/-/3/7/f/d/37fde77105fa8400/image_144h4cn.png)

**Step 2:** Identify products with high return activity.
![](https://storage.crisp.chat/users/helpdesk/website/-/3/7/f/d/37fde77105fa8400/image_ply54y.png)

**Step 3:** Compare return activity over different periods.
![](https://storage.crisp.chat/users/helpdesk/website/-/3/7/f/d/37fde77105fa8400/image_uf88xt.png)

**Step 4:** Adjust your product information or return policy where necessary.

**Step 5:** Monitor the results over time.
![](https://storage.crisp.chat/users/helpdesk/website/-/3/7/f/d/37fde77105fa8400/image_fvhnf9.png)