Of course growing is great, but with an increasing number of orders you can have an increasing number of returns. Product Returns increase the cost and complexity of your business, so it should always be a goal to try to reduce these to the minimum.
So let's analyze your Product Returns!
Definitions
Before you dive into data analysis, let's ensure that we are on the same page with some definitions:
| Date | Time where the original purchase was made - product returns are attributed back to the purchase date |
| Revenue Returned | Sum of revenue lost from returned products of the brand and product category selected |
| Revenue Return Rate | Percentage of returned revenue from the total gross revenue generated by products of the brand and category selected |
| Items Returned | Sum of items returned from the brand and product category selected |
| Items Return Rate | Percentage of returned items from the total gross items sold by products of the brand and category selected |
In addition, you can specify the following settings:
- Segment: choose if you want to see all customers represented in the numbers or only those belonging to a certain segment.
- Time: day, week, month, day, quarter, half a year, year.
- Metric: choose if you want the bars to show the number of items returned or the sum of revenue returned.
- Brand: show the performance of one brand within your store. If it is left blank, then it shows the performance of all brands together.
- Category: show the performance of one product category within your store. If it is left blank, then it shows the performance of all categories together.
Difference between Return and Refund
As the purchasing and return dates are different, returns are attributed to the date of purchase: if a certain day the Gross Revenue generated is $100, and a month later a return comes in for $20, then the Net Revenue generated in the day of the original purchase will be updated to $80.
Cash-flow movements due to refunds are reflected in the Refund report.
Use Cases
Returns are costly because they have to be reworked or are lost due to a defect. That's why it's important to track not only the number of returns over a period of time but also to keep it as low as possible. The top reasons why customers return products are:
- Damaged products
- The product received looks different
- Item received is the wrong one
Based on your customer feedback you should initiate the right measures to reduce your return rate. Think about the following:
- Offer high-quality product visuals
- Build a segment for your high returners and exclude them from special shipping conditions/discounts
- Incorporate product reviews
- Remove products with high return rates due to low production quality from your portfolio, only if improving quality has a larger impact on your production costs and therefore on your profitability.
What You Need
For this report to work properly, the following data must be imported:
- Order ID
- Order Date
- Stock Keeping Unit (SKU)
- Items Sold
- Item Price
- Customer ID
- Product Returns
- Product Return Date
- Product Category
- Product Brand
- Shipping Revenue
- Value Added Tax (VAT)
- Discounts
How to Get More Details
The metrics are shown as a color-coded combined chart followed by absolute figures.
If the Category and Brand filters are left blank, then your Overall Return Rate should be exactly the same as your Items Returned Rate.
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