According to a recent report by the return logistics company ZigZag and Retail Economics, serial returners—those who habitually purchase goods intending to return a significant portion—are set to send back £6.6bn worth of online purchases in the UK this year. While constituting just 11% of shoppers, this group is responsible for almost a quarter of all returns.
At a time when retailers are struggling with thin margins and heightened competition, the financial drain caused by high-return customers cannot be ignored. As highlighted by The Guardian, more than a fifth of non-food purchases made online in the UK are now returned to the retailer. High return rates not only decrease profitability but also create logistical headaches, as delays in goods being returned can make it difficult for retailers to manage stock levels. In some cases, returned items may need to be discarded if they are no longer in saleable condition, further adding to waste and cost.
Retailers are now at a crossroads, needing to devise strategies that mitigate the financial impact of serial returners without alienating their broader customer base. One potential solution could be to implement a dynamic postage fee structure that targets repeat offenders, by charging higher return postage fees to customers who consistently return a disproportionate amount of their purchases.
This approach leverages data analytics to identify patterns in customer behaviour. Retailers can set thresholds—for instance, flagging accounts that return more than 50% of their purchases over a certain period and charging increased postage fees or restocking charges, incentivising more mindful purchasing decisions.
Whilst this strategy aims to maintain fairness by not penalising genuine customers who make occasional returns, implementing such a system does come with challenges. There is the risk of negative customer perception, where individuals may feel unfairly targeted or penalised. To mitigate this, clear communication is essential; retailers must be transparent about their return policies and associated fees, and inform customers when they are nearing the threshold of being classified as ‘frequent returners’.
Aside from potential negative perception, there are a number of other key considerations: Changes to return policies must comply with regulations regarding consumer rights and data protection, therefore consulting legal experts to navigate these waters is imperative. Operational complexity is another consideration, adjusting existing systems to accommodate a tiered postage fee structure requires investment in technology and staff training. Retailers should consider a phased rollout of this strategy, starting with a pilot programme to assess effectiveness and make any adjustments before full implementation.
The potential benefits of this targeted approach are significant. By addressing the root cause—habitual returners who disproportionately impact operations—retailers can reduce costs associated with processing returns, restocking, and inventory management. This is particularly crucial in the current economic climate, where every saved pound contributes to a retailer’s ability to remain competitive and invest in growth opportunities.
Furthermore, this strategy addresses the environmental implications of excessive returns. Processing and discarding unsellable returned items contribute to waste and carbon emissions; by discouraging unnecessary over-ordering, retailers can promote more sustainable consumer behaviour.
As online shopping continues to grow, innovative solutions that leverage data analytics to create fair and effective policies will be crucial. Retailers that navigate this challenge successfully will not only protect their bottom line but also enhance their reputation as environmentally conscious businesses.
The goal is not to punish consumers but to foster a more responsible and sustainable retail ecosystem that benefits both shoppers and retailers alike.
About the Author:
Adam Hadley CBE is the CEO of QuantSpark, a strategic consultancy focused on transformation through analytics and AI. Leading an entrepreneurial team of data scientists, analysts, and engineers, he orchestrates initiatives to optimise high-value, complex processes to enhance operational efficiency and bolster profitability. QuantSpark's impact extends across multiple diverse industries, including Retail.