Analyzing post-holiday returns at the start of the year is one of the most effective ways to uncover data-driven solutions that will improve outcomes for the rest of the year and the next holiday season.
Even under the best circumstances, the post-holiday season sees more returns than at any time of the year. However, many anticipate that returns are only going to increase. A recent Salesforce report found that, compared to 2021, returns almost doubled the week after 2022 Cyber Week. What’s more, they now predict that “...over 1.4 billion orders purchased this holiday season (13% of orders) will be returned - up 57% YoY.”
While that doesn’t immediately sound like a good thing, it does create a massive amount of data. When that data is expertly analyzed, return rates are reduced, customer loyalty and lifetime value increase, hundreds of hours in operating costs can be saved, and so much more.
Essentially, correctly leveraging return analytics allows businesses to have more control over their bottom line. Want examples? Let’s take a peek at what that might look like…
When A Specific SKU Has a High Return Rate…
When return data shows that a specific SKU has a high return rate, it can indicate several issues depending on a few variables.
First, it’s important to analyze this information within reference to similar products. For example, say the item in question is a tee shirt of a specific color. Are the other colors also being returned at the same rate? If so, the issue lies with a variable that all of these products share. That could be sizing, product description, material quality, etc.
If just one of the colors has a high return rate, however, then you need to assess the way that color is being communicated to customers during the consideration stage. Is the lighting on the image distorting the actual color? Is the name of the color misleading? Once the issue has been identified, it can be resolved so that customer satisfaction increases and returns decrease.
When Single Customers Purchase Items in Multiple Sizes…
When someone purchases the same item in multiple sizes (or even similar products in multiple styles) it’s known as bracketing.
This practice helps customers ensure they’ll receive their ideal product upon the first shipment instead of needing to return an item and shop again when the product might no longer be available. Customers will keep the items they want and then usually, but not always, return the rest.
The tricky thing about bracketing, however, is that it doesn’t necessarily happen because customers are dissatisfied with any particular product or experience. For the most part, it’s simply to avoid multiple transactions, wait times on shipping, or simply not wanting to shop in-store and try things on in a dressing room.
Plus, while this may sound like a big loss for businesses, some retailers discovered that more than 75% of consumers who bracket end up keeping more than one item. The exception to this, however, is when customers bracket the same item in multiple sizes. To combat this, providing detailed sizing information can be incredibly beneficial. It’s important to note, however, that bracketing issues related to sizing can be resolved in several different ways.
For example, adding things like a detailed sizing guide or adding product images with a variety of model sizes can provide the necessary information to negate the necessity of bracketing. Conversely, social sales data can provide information about specific platforms or influencers that may be performing well with fewer returns related to bracketing. Analyzing the way product information is conveyed via those channels can provide insights that can resolve bracketing issues in other sales channels.
When First-Time Customers Don’t Repurchase After a Return…
The importance of the customer experience during their first purchase with a business can’t be emphasized enough. Even before they’ve decided to make that purchase, they’ve likely researched the products, read reviews, reviewed the return policy, and possibly even compared brands. So, that first purchase is an opportunity for businesses to not only meet customer expectations, but to exceed them.
Unfortunately, returns data suggests that the majority of customers who return their first purchase aren’t likely to make another one. While the goal is obviously to avoid these returns, this scenario also creates an important opportunity for data analysis.
Understanding why first-time buyers return can help retailers try to win them back, inform retailers which products are problematic for customer acquisition, and much more. All of this information will help retailers ensure new future customers become repurchasing customers.
Not sure what the main issue is or what the correct solution might be? The Returnalyze dashboard allows businesses to cross-reference different data sets to verify which specific issue might be leading to a return. This means solutions can be implemented based on hard data.
Improve Outcomes with Data-Driven Solutions
Considering the wide variety of hurdles that 2022 presented us with (supply chain issues, rising costs, etc.), there’s never been a better time to increase operational efficiency in every area of business. Bottom line? Modern businesses need to make data-driven decisions in order to succeed.
That’s why our in-depth dashboard gives businesses access to detailed analytics that make it easier to identify issues, opportunities, and solutions. In addition, a partnership with Returnalyze comes with step-by-step guidance and expert data analysis so businesses can leverage this information efficiently and effectively.