Data analytics is imperative from a business perspective because it helps you identify the loose ends that are affecting your brand’s image and growth.
AfterShip Returns Center shows well-detailed data in a segregated manner, allowing its users to take necessary actions to improve returns management.
➡️ Steps to check AfterShip Returns Center analytics
Only paid plan users are eligible to use AfterShip Returns Center analytics. If you have multiple stores with different currencies and use only one AfterShip Returns Center account, you’ll see data only for the latest connected store.
Go to the ‘Analytics’ section of your AfterShip Returns Center account
You will see data based on the default settings, so set the date range according to your preference for the desired results
Let’s understand what data AfterShip Returns Center analytics has to offer:
➡️ Key indicators
Pro-tip: Click on 'View details' to see data in-depth. You can even export it in the CSV format to share further with your teams 🙂.
Date range: Define the period for which you want to see return requests. Available options are: ‘Custom,’ ‘Today,’ ‘Yesterday,’ ‘Last 7 days,’ and ‘Last 30 days’
In case you want to compare the current return data with the old one, click on the checkbox given for the ‘Compared to previous period’ option and specify the period
Returns request: It shows how many return requests have been raised within your selected date range
Return item(s) per return request: It tells you how many items are being returned per return request on average. It calculates the percentage by dividing the number of items by the number of returns requests
Returns rate: It tells you the returns rate of your store. If it’s dropping, it means you’re heading in the right direction. It divides the total number of returned items by the total number of ordered items
Let’s say you’ve sold 100 products in the month of January but 30 were returned or exchanged by customers, your return rate for Jan is 30% {(30/100) x 100}
Returns value: It shows the total amount that you have to return to customers within your selected date range
Returns value per returns request: It tells how much revenue you lose per each return request. It calculates the percentage by dividing the total value of returned items by the number of returns requests
Saved revenue: It puts the spotlight on the revenue that you’ve saved on each return request. For example, you save a notable amount of revenue when a customer decides to replace with the same item or exchange for any other. Similarly, you save the refund amount when the return gets settled as store credit.
➡️ Returns data
Pro-tip: Click on 'View details' to see data in-depth. You can even export it in the CSV format to share further with your teams 🙂.
Return reasons: You learn about all the reasons that customers have mentioned while raising a return request. It helps you identify hidden issues and tie up the loose ends quickly
Top returns by variant: It tells you about the variants of your products that customers generally return. It helps you with SKU and reducing the return rate
Refund rate: It’s self-explanatory. It signifies your rate of initiating refunds. To calculate the data, the total number of refunded items gets divided by the volume of items refunded within your chosen period
Exchange rate: It tells you about your percentage of receiving exchange requests. You learn about how many times customers have opted to replace with the same item and exchange with other items
To calculate the data, the total number of exchanged items gets divided by the volume of items exchanged within your chosen period
Total refund: You can easily see how much money you have refunded so far
New revenue: It shows the revenue that has been generated when customers paid an additional amount for item exchange. Check this example (case 1) for a better understanding
➡️ Customer-focussed data
Avg. resolution time: It shows how much time you take on an average to provide resolutions to customers
Automated returns: It tells you how many return requests have been handled by automation rules set by you
Customer country/region: It helps you identify those countries from where you get maximum return requests. Basically, you learn about your customers' country or region
In case you need help with analytics, chat with our support team now
Updated on: 29 / 03 / 2022