Return analytics: Understanding customer return behavior
Tara Daly
·August 19, 2024
Customer returns are a common part of the ecommerce experience—and if you’re not paying attention to the data behind your customer returns, there’s a huge blind spot in your business.
By collecting data analytics around product returns, you can use this business intelligence to help you improve the customer experience, optimize your supply chain, and even improve your product selection and product development processes.
In this article, you’ll learn how to collect the right returns data from your customers, and how you can use it effectively to boost your operations.
Types of returns data
At the bare minimum, your business should already be calculating the percentage of sales that end up as returns. This information can help you understand your profitability rate, and can be used to forecast the future rate of returns so that you understand how many sales you’ll need to make to turn a profit.
Beyond that, there’s a wealth of returns data that you likely haven’t yet uncovered. This includes:
- Most frequently returned categories
Do you see a higher return rate in swimwear than in outerwear? You should be able to break down your return rate by product category to understand which product types are coming back most frequently. - Most frequently returned products
Even within categories, does one particular product see a higher than average return rate? With the right data, you’ll be able to identify your outliers. - Reasons for returns
This is the most crucial data point, where you’ll be able to see where things went wrong. Determine what percentage of returns are due to sizing errors, a poor color choice, defects, shipping damage, or whether the customer simply didn’t like the product. - Customers with the highest return rates
Here, you can drill down to an individual level to see which shoppers are returning items at a high rate. You’ll also be able to segment customer groups by category based on their purchase and return history: You might find, for example, that Gen Z shoppers return products at a higher rate than Millennials. - Delivery error data
Another category of return takes place even when the shopper hasn’t actually received the product: Instead, they’ve experienced a “delivery error,” resulting in a missing or delayed package. Pay attention to historical delivery error data to uncover trends on a carrier and route level. - Return outcome
Did the customer request a refund, a product exchange, or store credit? - Average time to return
Once a customer has requested a return, how long on average do they take to send the product back?
Now that we’ve covered the most important data to collect, let’s discuss how to collect it—and most importantly, what to do with it.
How to effectively gather returns data
To get these returns insights at your fingertips, it’s important to have an automated system for managing your returns.
By using a returns management solution like Loop, you’ll be able to build return workflows to streamline the collection of your returns data. Loop can provide your customers with a multiple choice questionnaire as soon as they request a product return. With a click of a button, they can tell you what went wrong—whether it was a sizing or style issue, didn’t meet quality expectations, was defective, or just wasn’t right for them. Beyond information provided directly by customers, Loop can also collect data around return outcomes and average return time, based on aggregated customer return behavior.
Loop’s Insights tool can showcase different trends in return performance across a user-friendly dashboard. You can pull together different trends to create customized reports, drilling down across variables such as customer segment, product category, product type, and other key metrics. With customizable dashboards, it’s easy to get the right context to understand all of your return data, regardless of what you’re looking for.
What can you do with your returns data?
Finally, now that you have all of these valuable returns insights, how can you use them effectively to improve your business?
Your returns data can help inform everything from your marketing strategy to your carrier selection to your product development. Here are some crucial ways you can make the most of your data:
- Fix sizing issues
When you see performance trends around a certain brand or product being returned frequently because it’s too small or too large, it’s obvious that the sizing information on your product page isn’t accurate. In this case, it’s important to provide sizing guidance to shoppers, recommending that they size up or down based on past feedback to ensure that they get the right fit the first time around. See how a Loop merchant leveraged return insights to reduce their return rate by 10%. - Improve your product quality
If you’re receiving recurring return feedback that a product is poor quality or has defects, it’s time to take a deeper look. Inspect the products at your warehouse for flaws, and discard any items that don’t meet your standards. You can then work with your manufacturer or supplier to correct the issue for future runs, or remove the product from your inventory entirely. - Optimize your shipping process
Shipping errors, delays, and damage can happen—but if it happens too often with the same carriers, that’s a fixable problem. If you’re seeing trends in issues with the same carriers, it’s time to switch to a more reliable carrier. If shipping damage is happening across all carriers, it’s important to improve your packaging process to provide better protection during transit. - Personalize the customer journey
Customer return insights can be paired with other behavioral and purchase data to give you a 360-degree view of each customer. You can use this data to help you build personalized offers and experiences for each customer, including recommending products for exchange based on what they’ve liked in the past. By optimizing for exchanges during the return process, you’ll be able to retain revenue and grow your customer loyalty.
By collecting granular insights around your product returns, your brand will be able to use the data to improve business operations and boost customer loyalty.
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