Use insights from returns data to uncover missing product details that can bring in more revenue.
Since customers have different size needs and preferences, detailed sizing charts are obviously a necessary part of e-commerce. This not only makes it easier for customers to find the right product, but it also promotes positive customer experiences, minimizes size-related bracketing, reduces unwanted returns, and more.
From including brand-specific size details to offering conversion charts that are easy to understand, businesses can do a lot to help customers learn what size they should purchase. But is that enough?
Not anymore. Today, customers have tons of options when it comes to online shopping, and it’s easier than ever for them to research and compare products. While size details are important, you can also find retailers that allow shoppers to filter products by garment length, pattern, materials, stretch, occasion, and much more.
When comparing products from different retailers, shoppers will ultimately feel more confident purchasing a product that has more information. Fortunately, your returns transactions have a wealth of information that can uncover missing product features that may be contributing to returns.
Discover how insights from returns analytics can help you optimize product details for fewer returns, better customer experiences, and higher net revenue.
Leverage Direct Signals From Customer Feedback
The most obvious signals come from customer feedback. Whether in the form of testimonials or star-based ratings, this information comes directly from your customers and, as such, can be immensely valuable.
When customers submit testimonials that speak directly to size and fit, this information can be taken into account when developing strategies to reduce returns. However, while it would be great if customers gave precise feedback on how a product did or didn’t fit them, this can sometimes require a bit of creative problem-solving.
For example, while you may think that negative reviews are always a bad thing, they can be an information goldmine. Imagine a customer submits a negative testimonial about how they returned a pair of slacks that fit perfectly in the waist but were ultimately too short due to their 5’9” height.
In this instance, there’s not necessarily anything wrong with the product since a shorter customer would likely find it the perfect fit. What it does tell us, however, is that the product page needs to have more information about pant length. This will help customers make the right sizing decisions during the first transaction.
Instead of painstakingly combing through this information one review at a time, the right returns management platform can quickly analyze both rating-based and unstructured review data to develop automated insights.
Analyze Customer Signals From Size-Related Retail Bracketing Returns
Unlike wardrobing, customers who engage in retail bracketing genuinely want to find the right product. To do so, they purchase a product in a range of sizes or variations. This allows them to find the product that best suits their needs or preferences without waiting for an additional purchase. Once they find their desired product, they’ll return the rest.
While that may sound negative, bracketing transactions related to things like color can have a surprisingly high keep rate. Unfortunately, customers who bracket for size are much more likely to make returns. Returns from size-related bracketing, however, still contain important customer signals.
If a retailer notices that certain brands or styles are often bracketed for size, it’s a clear indication that customers don’t have enough information to make confident purchasing decisions. If there had been adequate information about fit or length, for example, they wouldn’t have needed to bracket. On top of that, cross-referencing returns data across channels can help businesses pinpoint the precise details that led to specific sizes being kept or returned.
Analyze Returns from Influencer Sales for Product Feature Insights
While influencer marketing used to involve partnering with individuals with massive followings, today, it’s more about individuals with niche followings that have high engagement. In addition to the increased likelihood that their audience will make a purchase, their audience is likely already segmented in some capacity.
This can be beneficial in several ways. For example, imagine that a product has a high return rate on other channels but a low return rate from size-specific influencers. Reviewing their ad campaigns can reveal specific product details that may not have been explained thoroughly enough on other channels.
Perhaps the influencer explains that the material is very stretchy and it’s best to size down or that a garment may only be comfortable within certain bust sizes. Adding this information to other channels can reduce those return rates, lead to fewer negative experiences, and ultimately higher net revenue.
Conversely, businesses that partner with a variety of influencers can gather product feature insights by comparing return rates. For example, imagine a retailer has recently begun offering a new brand of footwear. While it initially had impressive top-line sales, it’s clear that sales from athletic influencers have a high return rate.
In this instance, customers who have specific needs regarding footwear performance are signaling that the product didn’t meet their expectations. Analyzing these returns can help the business uncover the return reasons (width, heel height, cushion, etc.) so they can improve product information across channels.
Operationalize Insights with the Returnalyze Intelligence Platform
Finding missing product details is just the start. Fortunately, the customer signals found in your returns data can also help you discover which solutions are going to have the biggest impact.
Do your product pages need more dynamic images? Do you need to describe the activities a shoe is intended for more thoroughly? The Returnalyze Intelligent Dashboard can uncover all of that and so much more.
In addition to the granular data you’ll have access to, a partnership with Returnalyze means you won’t have to figure it out all by yourself. Expert data analysts will be by your side every step of the way to help interpret insights and develop data-driven solutions.
Schedule a demo or contact our team today.
