Online shopping is growing at an exponential rate. Just last year, an estimated 5.7 trillion U.S. dollars were spent on retail e-commerce worldwide, and this figure is expected to grow in the coming years.
While this is good news for retailers, the other side of a massive growth in sales is a massive increase in returns.
High return rates cost your business a lot of money because of:
- Costs associated with restocking and/or reselling the item
- Paying to have the item shipped back to you
Therefore, leading retailers keep a close eye on their rate of returns and continuously conduct product return rate analysis to figure out why products come back.
Let’s get a better understanding of what analyzing rates of product returns is all about.
What is product return rate analysis?
Product return rate analysis is essentially a way for companies to examine how often customers are returning their products, and why they’re returning them.
There are many reasons why consumers may return something, but they usually fall into three categories:
- Customer dissatisfaction
- Shipping errors
By gathering information on the number and types of returned products, as well as the reasons for those returns, you can identify areas where you can improve your inventory, your manufacturing processes (if as a retailer you manufacture goods), or even your customer service.
In doing so, you can reduce the high costs associated with returns.
So, what are the statistics on product returns telling us?
Product return statistics represent millions of dollars
Profits are made and then lost on the cost of returns.
According to industry-wide data, return rates vary depending on the category. This means clothing and electronics have higher return rates than books and pet supplies.
However, it has been recorded that globally, around 30% of online sales end up being returned, compared to 8.89% of brick-and-mortar sales. And a recent US study claimed returns cost US online retailers 21% of order value. These percentages translate into millions of dollars.
Therefore, you need to analyze why those returns happen and start with metrics like merchandise return rates also called product return rate formulas to determine what returns are costing you.
Product Return Rate Formula
Retailers can measure returns with two commonly used metrics.
Merchandise return rate
Measures the frequency of all items sold being returned, including products as well as services.
It is calculated by dividing the cost of what is being returned by the total cost of merchandise sold.
(Merchandise returns ፥ Total merchandise sold) x 100
This metric is important because it takes into account the actual value of the products being returned. A high merchandise return rate may indicate that customers are returning high-ticket items.
Product return rate
On the other hand, the product return rate formula only measures the frequency of products being returned.
So, you divide the number of products returned by the total number of products sold.
(Product returns ፥ Total products sold) x 100
For example, if you sold 1,000 products and 100 of them were returned, your return rate would be 10%. By tracking your return rate over time, you can determine whether your return rate is increasing or decreasing and take action accordingly.
Now that you understand these two metrics, you may be asking what actions you can take to manage and analyze your product returns.
Best practices for product return rate analysis
The next three actions outlined will help you conduct your product return rate analysis as a best practice so you can identify potential issues with products or your supply chain, increase customer satisfaction, and improve your business’s bottom line.
1. Collect accurate and detailed data
In order to conduct an effective product return rate analysis, you need accurate and detailed data on product returns. This includes data on:
- Number of returns
- Types of products returned
- Reasons for returns
- Associated costs
That data holds a lot of useful information that will benefit you when deciding how to address the returns.
However, depending on the size of your retail business, this might generate more data than a human can sift through. You might therefore need technology (like retail analytics) to extract the details, bring clarity and make sense of the data collected.
2. Use technology for a consistent methodology
It’s important to use a consistent methodology when conducting product return rate analysis, so it’s accurate and reliable, and you can compare data over time.
Technology, such as AI-driven analytics is a powerful tool to help keep your methodology consistent as it provides many beneficial features including:
If you can forecast product returns based on historical data, market trends, and other variables, you’ll be able to prepare for spikes in product returns, and adjust your operations accordingly, like reducing inventory for certain products because you’ll know a significant portion of them will be back on your shelves due to returns.
AI-powered analytics are designed to be objective and data-driven, eliminating human bias and ensuring that the methodology is consistently applied to all data sets, regardless of individual interpretations.
There’s no time like the present, advanced analytics provides real-time insights and recommendations based on the data, which helps you identify issues and opportunities and make decisions as soon as possible, eliminating costly delays.
The need for speed in a rapidly moving supply chain and marketplace is what AI-driven analytics delivers as it quickly analyzes large datasets, and identifies patterns and trends in product returns.
Root cause analysis
Addressing a problem at the root is the only way to solve it. AI-driven analytics identifies the root cause of product returns by analyzing data from multiple sources, such as customer feedback, social media, and product reviews. So, you’ll understand the specific product features and issues driving returns.
Now that analysis of the data has given you the insights you need and a clear picture of what you have to address, you can move forward.
3. Take action
You need to take decisive action to minimize return costs and customer dissatisfaction.
For instance, if your return rates are high due to shipping and handling errors, you may choose to improve your packaging and shipping processes.
Some retailers are even revisiting their return policies, and removing the option of free returns.
Clothing retailer Zara has already started charging £1.95 (about $3 Cdn) in the U.K. for online returns.
Ultimately, product return rate analysis should be an ongoing activity for continuous improvement. By regularly analyzing data and taking action to address issues, you can improve product quality, reduce return costs, and enhance customer satisfaction over time.
Turn product returns into a positive with best practices
Understanding product return rates is crucial for all leading retailers, as returns cost retailers millions of dollars annually.
By analyzing return rates and tracking the critical metrics of product and merchandise return rates, you can make informed decisions about your business and take action to improve your bottom line.
Additionally, you’ll be ahead of the retail returns game when you:
- Make sure your data is accurate
- Leverage advanced analytics to make sense of your data
- Take action to address reasons for returns
Turn product returns into a positive by seeing them as an opportunity to build even stronger customer loyalty and drive more sales in the future, creating a win-win situation for both your retail business and your shoppers.