Online returns: the change of course in Retail

Returns, particularly free returns, have been a problem to solve for Retail companies for some time. Let’s take a look at some of the solutions that have been adopted

It was late 2022 when, for the first time, we dealt with the future of returns in Retail: a practice put into question both on an economic and environmental level. Now, the issue is back in the spotlight, with various companies that have started to implement solutions to the problem.

The huge weight of online returns

The issue of returns, particularly free returns, has become a real problem to solve for many Retail companies, especially those in Fast Fashion. There are garments that, inside sealed and labelled packages, carry out roundtrip intercontinental journeys: this is a phenomenon known as “bracketing”, the tendency to buy many products that are the same, or similar (perhaps in different sizes), with the knowledge that one, or even all, can be returned.

In fact, among the various studies conducted on the topic, it turns out that the global value of online returns today would amount to USD 550 billion (equivalent to EUR 509 billion): a cost that not only weighs heavily on the industry, but that is also a symbol of significant environmental damage. Retail return rates are in fact increasing by 63% yearly; In Italy, the category with the highest percentage is clothing (25.14%), followed by footwear (15.30%) and accessories (10.14%).

The commitment of companies for a change of course

Some brands are nonetheless attempting a change of course to at least limit compulsive purchases, applying for example a charge for the return. Some add charges only on returns for their e-shop and only in some markets; others call for an amount that will be deducted from the total refund and still others have established a minimum order to qualify for free options.

Among the solutions presented there is that of implementing CRM capabilities and databases, also through artificial intelligence, evaluating individual requests and examining who makes them and their history over time. For example, in the case of a loyal customer with a history that includes a reasonable number of requests, it is possible to act in one way, while in the case of a buyer who has returned an empty box or a copy of the original it would then be possible to act in another way. These analyses would allow for managing the returns policy differently, discouraging at the same time behaviors which are harmful to the environment.

It is precisely in the area of technological implementation that a company like Bizeta can make its contribution to this important change: surely with solutions based on data-mining, such as Retail Profit Protection, but also with other software developed for Retail.