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How can retailers protect profits and keep customers happy?

Wed, 24th Jul 2024

Returning an online purchase is often seen as a hassle for customers, especially when unexpected return fees are involved.  

When British fashion brand PrettyLittleThing (PLT) announced changes to its return policies in the UK, it sparked a frenzy among both customers and the media. Under the updated policy, UK customers will have a return fee deducted from their refund, with no exceptions. Just two weeks after this announcement, PLT attracted even more attention by banning customer accounts with unusually high returns activity. 

While PLT received significant backlash, they are not the first retailer to update their return policies, and they certainly won't be the last. Many well-known brands, such as Zara, Boohoo and Next, already charge fees for online returns. As highlighted by the heightened emotions around this specific policy change, retailers are facing a challenging dilemma. While it is essential to provide generous policies and promotions to attract customers, these same offerings can lead to significant policy abuse and loss of otherwise loyal customers. Balancing customer satisfaction with protection against exploitation is crucial for sustaining both business goals and customer loyalty. 

Fraudulent returns, misuse of promotion codes and discounts as well as other types of policy abuse drive substantial financial loss and have already contributed to a staggering £30 million in losses due to retail fraud in the past year. The real challenge at the heart of this issue lies in distinguishing which claims are policy abuse and then determining whether it is being committed by professional fraudsters or innocent/ genuine customers. 

Unravelling policy abuse  
Policy abuse, where customers deliberately exploit a retailer's terms and conditions, manifests in various ways. It includes exploiting return and refund policies, making false item-not-received claims, misusing promotional codes, and reselling goods. Compared to traditional fraud, policy abuse is often harder to manage as it can involve customers with a seemingly good track record. 

Levels of policy abuse started to soar during the Covid-19 pandemic, and it has since escalated into a multi-million-pound problem for online retailers. Recent research revealed that nearly one in five (18%) UK consumers are more likely to engage in policy abuse behaviours during the summer, driven by increased financial pressures at this time of year.  

While online shopping has kept many retailers afloat, it has often come at the expense of the profitability of brick-and-mortar stores. Many retailers are grappling with both, yet the customer behaviour and shopping experience can look very different. The same research reveals that nearly 50% of UK consumers have purchased multiple sizes or colours of an item online with the intention of returning most of them. As more consumers are shopping online with the explicit intention to return some of their purchases, it significantly increases the level of risk for retailers. 

Differentiating between loyal customers and professional fraudsters 
On the figurative policy abuse scale, return and refund abuse can range from relatively unsophisticated offences, such as making a false claim for a missing product, to more calculated schemes discussed in online forums on the dark web. This is where policy abuse becomes more powerful, with dedicated online communities frequently sharing tips and tricks on how to abuse different merchant policies.  

Without a clear strategy to differentiate between policy abuse committed by loyal customers and that committed by professional fraudsters, it is extremely difficult for merchants to strike the right balance between protecting profits and preserving a great experience for desirable customers. A customer might make ten purchases and only abuse the return policy once. However, when many customers do the same, these seemingly minor instances accumulate, resulting in thousands of pounds in lost revenue for retailers annually. 

It can also lead to some bizarre and surprising situations. There are many industry anecdotes, especially in the luxury sector, of retailers receiving alternate or counterfeit items as part of policy abuse. One retailer found a bag of apples in the return box instead of the designer handbag originally purchased. Or customers may return empty boxes filled with unrelated items like old newspapers or random household objects.
 
Striking a balance  
Recent research revealed that policy abuse has created over $100 billion in losses for ecommerce merchants worldwide. Online brands like PLT, where there is already an expectation for consumers to make returns, are often a prime target. The merchant must decide if a customer has a good enough history to process the return or if they want to challenge it. The wrong decision can cost them valuable future revenue and, in some cases, a loyal customer. 

As policy abuse affects all retailers in the ecosystem, advanced solutions can identify fraudulent behaviour patterns to benefit multiple organisations in the network. Artificial intelligence (AI) enables retailers to visualise customer identities and behaviours, tailor the customer experience, and customise policy decisions. By conducting real-time risk assessments with AI, merchants can implement more flexible policies tailored to individual customers. For instance, a loyal customer might receive free and flexible return options, while a customer with suspicious behaviour could be required to pay a fee. By identifying these patterns, retailers are empowered to prevent abuse without frustrating loyal customers. 

Achieving customer satisfaction and protecting revenue requires the right technology and strategy. An effective policy abuse strategy boosts ecommerce sales by reducing friction, ensuring greater product availability for reliable customers, and enhancing the overall customer experience. Put simply, retailers must choose their approach to policy abuse wisely to balance customer satisfaction with revenue protection.

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