At last, Ms. Consumer finds the perfect product at your website. It fits all her specs, she can receive it fast and the shipping cost is a bargain. This has all the earmarks of a potentially long and mutually beneficial relationship. The likelihood of a product return is the farthest thing from her mind.But then it arrives. The materials aren’t quite the quality she thought. The measurement is a little off. Or it’s not even the product she ordered.No matter what you do next to save the sale, the honeymoon is already over. She might buy from you again, but then again, she may not. The next site down in the Google results looks promising…
Product returns cause customer churn.
When products don’t live up to consumer expectations, the odds of a new customer becoming a lifetime customer drop precipitously. That can be extremely damaging. According to Adobe Digital Index Report, engaged, repeat customers account for 40% of a retailer’s total revenue and drive three to seven times the revenue per visit compared to one-time buyers. For each one percent of shoppers who return for a subsequent visit, the report says, overall revenue will rise by about 10%.
So making sure products live up to expectations is critical. But most retailers collect little information on how customers feel about their products. No returns = the product was good. Returned = it was bad. But why? Until recently, it was a guessing game. Insights into what customers think of products is hiding in plain sight: product returns. By collecting more and better data about product condition and consumers’ own comments about the items they’re sending back, and then applying analytics, retailers can quickly identify the root cause of product returns and make changes to prevent them, whether it’s asking vendors to improve quality control, fixing a warehouse mis-slotting or avoiding a disliked fabric in future orders.
According to Retail Systems Research’s Advanced Analytics: Retailers Fixate on the Customer, “Retailers know they have to glean information about customer preferences as early as possible to enable more agile responses to current market conditions,” and making better merchandising decisions is among retailers’ primary goals.
Applying advanced analytics to product returns, then using that knowledge to make better products, adds up to happier customers who become the repeat buyers every retailer values.