We use an example to illustrate how an online retailer in the fashion industry could use the return cost calculator and show the results and their interpretation below: Assume that this online retailer would like to consider various scenarios of shipping and return policies in order to choose one of the scenarios that are aligned with the latest changes on the EU-Directive. The online retailer knows from previous experience that his average return rate is 50%, that his average margin per order is 20€, and that he spends 3€ to acquire an order. Moreover, he knows that the processing costs associated with a returned order are about 5€ in average. The online retailer pays another 2€ to a logistics service provider for shipping the orders. Currently, the online retailer offers free shipping and also free returns to his customers. He would like to compute the financial consequences of all possible alternative scenarios to get an overview before making a decision.
Thus, the online retailer provides the calculator with the following numbers and obtains the corresponding results:
|Scenario||Profit per order after return costs||Necessary order increase or maximal order decrease to achieve same profit as current scenario|
|Current: Shipping free, Return free||1.50 €||0%|
|Scenario A: Shipping fee, Return free||2.50 €||-40%|
|Scenario B: Shipping free, Return fee||2.50 €||-40%|
|Scenario C: Shipping fee, Return fee||3.50 €||-57%|
In the current scenario, the retailer obtains a profit after return costs of 1.50€ per order. If the retailer introduces return fees that the customers have to pay when returning an order, keeping a free shipping policy (Scenario B), his profit after return cost per order would increase to 2.50€. Within this scenario, the retailer could bear a decrease of 40% in the number of purchased orders, until the achieved profit per order becomes inferior to the profit per order under his current scenario.
If the retailer decides to make customers pay for shipping, but not for returning orders (Scenario A), he could tolerate a decrease of 40% in the number of purchased orders, until the achieved profit per order becomes inferior to the profit per order under his current scenario. His profit after return costs per order in this scenario would then be 2.50€.
The third scenario, the retailer lets customers pay for both shipping and returning orders to the online retailer. Within this scenario, the retailer could achieve 3.50€ profit after return costs per order and hence tolerate a decrease of 57% in the number of purchased orders, until the achieved profit per order becomes inferior to the profit per order under his current scenario.
Did you know that for the online retailer in our illustration, a 1% -decrease of his return rate to 49% would increase his profit after return costs by 18%, if costs remained the same ?
To get an idea about the impact of product returns on profit, the online retailer in our illustration also gets the information that, if he could achieve a decrease of his return rate from 50% to 49%, then he would increase his profit after return cost by impressive 18%, assuming constant costs.
Prof. Dr. Bernd Skiera
Bernd Skiera is chaired professor of electronic commerce at Goethe-University in Frankfurt, Germany.
Siham El Kihal
Siham El Kihal is part of the PhD program in quantitative marketing and is a research assistant at the E-Finance Lab
Prof. Dr. Christian Schulze
Since March 2012, Christian Schulze is an Assistant Professor in Marketing at the Frankfurt School of Finance & Management.