1. Failing to validate and analyze the customer reasons for return is a very common mistake in handling product returns.
There's approximately $351 billion worth of merchandise returned by customers in 2017. That dollar amount is a whopping 10% of total sales, says National Retail Federation. Ten percent of returns is a really high number, considering that the number one findings in those returns is the infamouse "NFF" (No Fault Found), aka "NDF" or "NTF" ('No Defect Found', 'No Trouble Found' respectively).
A vendor should properly identify the accurate reason why the customer is requesting to return a product. This means that offering a drop down list of possible reasons is not enough. You must request the customer to enter the reason for his request on a free field text area. As you collect those custom-written descriptions you will eventually find a pattern. Analyzing that pattern of product returns may help you uncover real and deeper undestanding of why customers return some of your products.
2. Failing to to establish a good rule for rejecting returns is common mistake that is usually taken for granted.
U.S. retailers lose between $9.6 billion and $14.8 billion annually from return fraud, according to research by the National Retail Federation (NRF) and the Loss Prevention Research Council.
Unless youre selling very special types of products, do not allow your customers to send products back without your prior authorization. That practice leads to abuse. A very basic rule of a good product returns system is a way to enforce at least a basic gate keeping. The goal of this gate keeping is simply to validate if the customer has a valid reason for returning the item. It is fair to require customers to provide a valid reason for returning an item, not just because he the customer can request it. Ever heard of the expression "just because you can does not mean you should"? If a vendor fails to validate the customer's reason for return then he can expect a quick rise in customer returns; resulting in loss of revenue.
3. Poor customer or user interface in accepting product returns is an unacceptable mistake.
If your product returns portal comes with a 100 page user manual then it is way too complicated! A good returns portal should be intuitive enough to be self-explanatory and not relying on many pages of How To's and Instructions.
4. Poor end-to-end customer experience after submitting a valid returns request.
Some customer returns portal just allow you to submit request for returns but do not provide confirmation info (usually in the form of an email) to the customer, leaving the customer wondering if his request actually went through. This lack of confirmation may prompt some customers to resubmit the return request, thereby causing more confusion and bad data to the vendor.
A half-baked product returns automation system especially on the customers' side of will only hurt your brand, rather than improve it.
5. Making the returns process ridiculously too easy is probably the most surprising mistake when accepting product returns by customer.
Last but not least, some vendors blindly implement a product returns process that is very susceptible to abuse and ignoring the fact that the "Law Of Diminishing Returns" (no pun intended) may also apply to a returns process that is overly simple.
What do I mean by this? By making the returns process too easy and thinking that it is good for sales, it will reach a point when the benefits actually diminish.
If you customers return items without properly validating the reason for return then you are inviting trouble that will hurt your bottom line profitability. There are vendors that even allow customer to generate their own pre-approved RMA number on-the-fly, ship the items back with PRE-PAID shipping label.
Sadly, almost 50% of the most common findings for these returns fall under the NFF (No Fault Found) category. Not only does a vendor loss profit, but it also skews the reliability statistics of the products that have been marked as returned item. It just generates a domino effect of bad data, and bad experience.