In fact, one could argue that the challenges associated with returns are on the rise, particularly for Shopify merchants.
With an average return rate of 20% to 30% in ecommerce, returns of products purchased online negated $41 billion of sales revenue in 2019.
Still, returns are a natural and healthy part of the ecommerce shopper experience. Up to 40% of your shoppers will return a product by their 3rd purchase.
Inevitably, the question arises in some form: “Whose fault are returns?"
Often, we fall victim to citing blatant patterns of customer behavior, such as wardrobing or fitting room purchases, as the driving factor of returns.
Wardrobing refers to cases in which a shopper purchases a product, take a lavish dress as an example, for a particular occasion or event. Essentially renting the item, the customer exploits the return policy by purchasing and using a product that she had no intent of keeping.
The main problem with this explanation is: there currently is not a generalized and robust way to identify it.
Without implementing a sophisticated tagging system, or examining returned products for signs of prolonged use, merchants cannot be certain whether or not a shopper has committed wardrobing.
Fitting room purchases, or bracketing, occurs when a shopper purchases multiple variants of a given item, with the intention of keeping those she wants and returning the rest.
In these cases, the shopper uses her home in place of a typical in-store fitting room.
Fitting room purchases are much easier to identify - you can simply look for orders that contain multiple variants of the same product.
These purchases, however, simply do not seem to contribute a sizable percentage of orders for most retailers.
For one retailer we partner with, multi-size purchases have made up only 4.34% of their total orders since 2019.
And although they have an astronomical return rate of 58.43%, fitting room purchases have contributed less than 20% of the total units returned in this time.
As a result, even if all of the fitting room purchases for this retailer had been shifted to single-variant purchases, the overall return rate would have moved less than 3%, assuming their typical return rate.
So, while fitting room purchases in many cases guarantee that more products will be returned, they usually account for a small proportion of total orders.
The main objective for fitting room purchases should be identifying why shoppers feel the need to try multiple variants, and then addressing those concerns.
Patterns of serial returning are often referenced as driving forces of returns in ecommerce.
But, their true impact can be elusive to capture, and most likely comprises the minority of returns.
The bulk of returns, then, cannot be attributed to a fraudulent or glaringly problematic behavior on the part of the customer.
Through returns data, we can dig into the root causes of returns. And we'll see that the return reasons that imply clear fault - whether it be on the retailer, the shopper, the 3PL, or another partner - are often the least prominent.
Let's start by breaking down the return reasons for a women's fashion brand.
In fashion / apparel, sizing is often the most prominent reason for returns. And this retailer is no exception.
“Too Big" and “Too Small" combined make up more than 60% of the units returned, followed by “Do Not Like This Item."
While perhaps shoppers are not engaging with product sizing details as much as they should, we cannot blame them for these cases.
It may not be anyone's fault. It can be extremely difficult to purchase products online, especially things like pants, dresses, or formalwear - all of which require a precise and comfortable fit.
The reason “Do Not Like This Item" is much more vague.
For this case, a deep-dive into return comments may prove to be the most effective.
This video demonstrates how a word cloud can be leveraged as a way to expose and research new issues within open-ended comments, even filtering to concentrate on specific products and/or return reasons.
Next, we'll check out the return reasons for a retailer that specializes in women's fitness apparel.
We see, again, that sizing is a driving reason for this merchant's returns. Particularly “Too Small," which has accounted for over 50% of their total returns volume.
Fitness apparel often fits on the tighter side: so what's the retailer to do?
Most likely, social proof, in the form of user-generated photos, videos, and reviews, could help shape a more realistic perception of the product.
On top of that, it may be useful to include a guide comparing their sizes to sizes of brands that shoppers are likely to be familiar with.
And again, “Just Didn't Like It" is one of the more common return reasons, behind sizing.
Now, let's take a look at the breakdown of return reasons for a brand that sells phone cases and other accessories.
This is a more nuanced case, because phone cases and accessories are substantial different from apparel.
In this product category, quality and defects are most often the driving factors of returns.
This is another case in which leveraging return comments may be the most beneficial option. They may highlight particular issues that shoppers are experiencing, which could connect back to suppliers, materials, or manufacturing techniques.
And lastly, we'll examine the return reasons for a brand that focuses on women's fashion essentials.
Just like the other women's fashion brand, Retailer A, sizing is the most prominent reason for returns within Retailer B.
However, unlike Retailer A, “Too Big" far exceeds “Too Small" for Retailer B.
This tells us immediately that there could be a systematic issue in the production or presentation of products that is leading to these returns.
“Changed Mind" is the second most common return reason cited for this retailer, which indicates that impulse or unconfident purchases may be a significant contributing factor to their returns volume.
Without examining ecommerce returns data, we simply cannot tell who is to blame for the high volume of returns that occur in ecommerce.
And many times, fault is difficult to determine even with the data.
Blatant patterns of serial returns, such as wardrobing or fitting room purchases, simply do not seem to cause most returns. And return reasons that indicate fault - quality, defect, damage, or wrong item sent - do not make up a sizable volume of returns for many retailers.
But it's important to remember that who is right does not matter nearly as much as what is right.
Returns data empowers retailers to investigate the root causes behind returns, and address issues before they are widespread. You can reduce your return rate, drive exchanges over refunds, and ultimately create value for your shoppers.
In doing so, they will create value for you.