Part one of the series described why retailers offer return policies and how important they are for us as customers. This part addresses the costs and benefits of return policies in more detail.
When thinking about whether or not to offer a return policy we have to think of its costs and benefits. The costs include direct handling costs, financing cost and fraud. The major benefit of return policies is the boost in sales.
The costs associated with returned products are significant. For e-tailers, the average cost of processing a return is $30-$35 or 2-3 times that of an outbound shipment (Stock et al., 2006). According to Petersen & Kumar (2010) companies lose 3,8% in profit due to product returns. Therefore, product returns expose the retailer to higher costs and increased cash-flow uncertainty. Understanding customer’s return behavior is also important for the customer lifetime value calculation. It may make sense to offer different service levels to customers who tend to return more than to their low return peers. The fact that 10% of all customers are responsible for 40% of all return costs further supports this argument (Bundesverband des Deutschen Versandhandels e.V., 2004).
This is why retailers adjust each of the characteristics of a return policy in order to control product returns and protect themselves from abusive customer behavior. Return policies can differ along several dimensions:
- Duration (tight deadlines)
- Easiness to invoke (obligation to show original receipt, return in original package, no visible sign of use)
- Restocking fee (typically 10%-25% – restocking fees allow retailers to make only those customers responsible for the costs of product returns who make use of their right)
- Reimbursement of shipping and handling fees to the customer and, in the case of a return, back to the retailer
- Percentage of the expense reimbursed when returned (coverage)
- Store credit
Each dimension can be used to discourage consumers from exercising their return right. It can make sense to make returns more expensive if there is a high risk of customer moral hazard. If all cost were reimbursed, customers would have a high incentive to buy a product with the intention to return it after using it for a certain period of time. It would be like a free rent. The losses from return fraud and abuse have been estimated to more than $15,5 billion annually in the US (The Loss Prevention Research Council, 2008). Although practitioners are more concerned with the cost generated by the minority of dishonest customers, usually the benefits from guarantees outweigh them. It can be shown that for most products that eliminating opportunistic behaviour actually diminishes retailer profits. On the other hand, partial refunds can also be seen as a risk-sharing measure, as both the retailer and the customers are risk-averse. The problem with making complaints more costly is that dissatisfied customers not only stop doing business with the retailer but, on average, they also complain to 11 further people, thereby generating substantial bad word-of-mouth (great presentation by Kotler and Keller).
The main reason for why return policies have a positive effect on sales is their risk mitigating character as people rather try to avoid mistakes and are guided by the prevention focus (security, protection, safety and loss avoidance). Different product categories have different perceived risk levels (see part 1). The degree of risk perception depends on how much money is at stake, the amount of uncertainty, consumer self-confidence and the familiarity and experience with the product. Also, the risk tolerance is customer specific. In the distance shopping situation consumers perceive risk because they cannot personally examine the product and evaluate its quality (they cannot feel or touch the product), size (sizes vary for different brands) or style. Customers are less likely to purchase a product the higher perceived risk is and the lower individual risk tolerance is.
As offering return policies is standard retail practice nowadays we have think about how to find the optimal policy that maximizes the bottom line in consideration of the up- and downsides of returns. This will be explained in the last part of this series.