3 Tips for Using Returns and Exchange Data to Build a Better Post-Purchase Experience

Everyone loves to say that “data is king,” pointing to Amazon.com and its “data-driven decision making.” In most cases, these well-intended but divisive statements create insecurities in most organizations. And if they’re actioned too hastily, they will slow down decision making while company leaders wait for data to give them a perfect answer.

To its credit, Amazon was able to grow into the largest online retailer by being extremely data-driven. But even Jeff Bezos values high-velocity decision making, following the primary principle “don’t wait for all the information before acting.” So, how do those of us without Amazon’s scale, resources and distribution capabilities make high-velocity, data-driven decisions?

In short, we don’t. And I’ll advocate that we never make data-driven decisions. Rather, I suggest we make gut-driven, data-informed decisions. Decisions made at a high velocity that are right most of the time are what create successful companies. “Perfect” decision making kills companies because they’ll inevitably move too slowly.

To put it simply, data-driven means that you let data tell you what to do, while data-informed decision making uses data to allow you to move more confidently with your own decisions.

Being data-driven helps retail leaders make decisions in focus areas such as price, convenience, and breadth of selection.

Instead of replicating their tactics, today's successful brands are using data to inform decisions that help deepen the connection with their customers.

Because we believe so strongly in the importance of the post-purchase experience, finding tangible ways to leverage data collected through returns and exchanges to improve your customers’ experiences and strengthen the bond between your customers and your brand is key. Here are some tips to help you accomplish that: 

1. Use exchange data to create better product descriptions.

When a customer exchanges a product, it’s often because they grabbed the wrong size, or the color wasn’t what s/he was expecting. When you collect data on why the customer exchanged the product, it allows you to tailor the description of that product to help future customers make the best decision possible.

For example, if you sell a pair of shoes that is continually being exchanged for a size larger than what was bought, you can add that information to the product description page with verbiage like: “These shoes fit snug. It's always best to grab one size bigger than what you would usually wear.”

2. Use refund data to improve the quality of your products.

“Returns” and “refunds” may be thought of interchangeably, but there's a big difference between the two. A return can go one of two ways — it can strengthen or weaken the relationship. When a return results in a refund, the relationship has been weakened. Exploring the return-to-refund ratio on specific products in your catalog ought to provoke serious consideration into the value of that product

A highly refunded product may be appealing enough to be purchased, but it’s consistently missing your customers’ expectations and delivering a poor post-purchase experience. Return reasons offer key insights for merchants looking to intimately understand their customers.

3. Curate your shopping catalog with best-selling products.

A key feature of Loop is that it allows customers to exchange for any product, not just a variant of what they already chose (size/color), allowing merchants to provide disappointed customers with optionality and a way to rebuild trust with a customer who’s been disappointed by the product they purchased. S/he can return a sweater for a jacket or pair of pants, facilitating discovery and encouraging a deeper dive into the brand.

Jonathan Poma is president of Loop, an e-commerce application that turns the return process from a point of friction into an experience. One that encourages customers to find the right product for them rather than a refund.