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.
Let's analyze the Return Risk for your different products to be aware of potential changes to your net revenue early on!
Definitions
Before you dive into data analysis, let's ensure that we are on the same page:
Return Risk | Predicted Return Risk for each product |
SKU | Stock Keeping Unit, which is the unique ID associated with the product |
Order ID | Unique ID associated with the order including the product |
Order Date | Date of order placement |
Customer ID | Unique ID associated with the customer |
Title | Name used to list the product |
Brand | The associated brand of the product |
Category | The associated category of the product |
Repeat Purchase | The customer’s umpteenth order, in which the product is included |
Order Value | Gross Revenue generated by the order |
Items | Number of items included in the order |
Items Returned | Number of returned items |
Calculating Return Risk
The Return Risk is calculated for all items which still can be returned.
Your individual return time can be customized for custom integrations: it represents how long your customers are allowed to return their items sold, meaning the maximum number of days between the order date and the date of return.
A return risk is daily calculated for each individual item based on RX Prediction™. This again results in a total return risk.
RX Prediction – wait, what?
Prediction is performed via machine learning and searches data twins based on the following criteria:
- Number of days after order date
- Return behavior per customer
- Return rate per category
- Specific SKU
With every day that passes after the last order, the return risk decreases.
The return risk calculation starts on the date you added the prediction functionality to your RX account. This feature is included in the Advanced and Enterprise Plans.
Use Cases
Returns are costly because they have to be reworked or are lost due to a defect. The report answers the following questions:
- Are certain brands or categories returned more frequently on a regular basis?
- Can you prevent the return by offering the customer a discount if he keeps the goods?
- What volume of returns can I expect in the next few days (especially important during sale seasons)?
- How much money will I have to refund and what is my net revenue?
It's important to track not only the number of returns over a period of time but also their reason to maintain 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
- Incorporate product reviews
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
- Shipping Revenue
- VAT
- Discounts
- Customer ID
- Product Title
- Variant Title
- Product Returns
- Product Category
- Product Brand
How to Get More Details
The metrics are shown as a color-coded donut chart followed by absolute figures.
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