Although the e-commerce sector has been growing for years and has even received an additional boost during the pandemic, online shopping has not been spared from the economic downturn. With potential savings in terms of costs and time, but also in terms of effort on the part of employees, there is a lot to be said for automation in e-commerce. However, these incentives go hand in hand with a feeling of pressure as soon as the economy shrinks. Additionally, with the recent quantum leap in artificial intelligence through large language models such as ChatGPT, the catalog of processes that can be automated is growing. ChatGPT and the like are particularly promising in customer service, because never before has a conversation with an AI been as fluid as it is now. Although customer service itself will not necessarily be replaced by AI, the sheer mass of customer concerns could initially be handled by an AI in the future, which takes care of minor issues by itself while it forwards more complex cases to the right employees. This potential creates peer pressure to move forward with automation in e-commerce: the new technical possibilities and the associated savings coming together with the shrinking of the economy. This is largely because some competitors that are already well positioned in all things automation and are already cutting costs in many areas through utilizing it. And a high degree of efficiency is often the buffer that gets companies safely through a recession.

In order to save time and streamline work processes, automation measures have already been implemented in almost every online store. For example, shipping or order confirmations are automatically sent to the customers via email after the order has been placed. However, what is often overlooked when retailers use e-commerce software such as Shopify or Spryker to automate processes are the processes situated downstream of the purchase: the after-sales services. It is understandable that retailers focus primarily on generating sales. Although all automation measures are initially investments, rudimentary after-sales services are certainly not a highlight from the customer's perspective and some aspects even trigger hidden costs. Automating parts of an online store only to implement similar measures for after-sales-services years later is not at all in the spirit of efficiency, which may well be the straw that breaks the camel’s back during economic drought.

The Dilemma: Shouldering it all yourself, or outsourcing it entirely

Most general software solutions for e-commerce only have limited options for processing returns. It often is just a typical returns slip, that is printed out by an employee via the software – which oftentimes is not even automatically filled out by the software! To avoid this, many stores use fulfillment service providers such as Amazon. Fulfillment service providers then take care of everything ranging from shipping and logistics to returns, depending on the agreement. Some even take care of customer service. E-commerce companies are therefore spoiled for choice: either take matters into their own hands and make use of the potential automating after-sales services holds by themselves – which comes at a cost in terms of time and money, while also needing to be evaluated based on existing conditions and needs. Or, alternatively, outsource it all to a fulfillment service provider. Customer service, logistics, and goods and returns shipping represent a significant part of business which is handed over to a third party, leading to a decrease in flexibility.

Secondary costs should also be kept in mind, if returns and logistics are handled by a fulfillment service provider, they will make the call on whether returned goods are resalable. This check is usually carried out more thoroughly by a company's own employees than by a third party, who carry out this type of check for a huge range of products. Anything that is categorized as not resalable triggers additional costs: storage costs, labor costs due to processing, and possibly other costs in terms of transporting the resale goods or even destroying them. These downstream costs are also difficult to anticipate due to their unpredictability and make returns management without a strategy a potential pitfall in terms of cost. However, processing returns inhouse makes noticing these types of hidden costs easier. If there additionally is a production surplus, the company's own resale goods must be sold in another market, as they would otherwise compete with the product. In these cases, product labels often have to be removed. The rat tail of problems can be almost endless if you are not prepared for them. And in the worst case, destroying resale goods is more profitable, even if the damage to a company’s reputation for this decision can be enormous.

Can the Efficiency Revolution through Automation in E-Commerce also be realized in Returns Management?

And thus, retailers find themselves in a real bind: In order to realize time savings and the associated cost savings through automation not only in day-to-day business but also in returns management, either employees with solid expertise must develop and establish these processes, or the entire area is handed over to a fulfillment service provider. A third option however would be a dedicated service and returns portal that is set up together with a partner. These are usually SaaS models such as Trusted Returns.

But ultimately, retailers have to decide for themselves what they feel more comfortable with: developing everything inhouse while bearing the cost of development, outsourcing everything at a loss of power and oversight, or having a third party develop a customized solution that is then managed inhouse. Whatever a retailer decides to do, it is certain that data collection in the returns process can reduce return rates in the long term and that a well-positioned customer service improves customer satisfaction. At the same time, it is necessary to take a targeted approach to returns management and develop a strategy to eliminate the risk of returns triggering secondary and hidden costs. Understanding the returns process as an additional touchpoint to the customer also makes it possible to collect completely different data than before. And especially if the new possibilities of generative AI such as ChatGPT can be leveraged in customer service – a chat bot in combination with a self-service portal doesn’t sound too far off – the importance of customer data of all kinds will grow. Today, it is important for gaining insights into one's own business, which can then be leveraged to make informed decisions. With generative AI, however, this data could be important tomorrow in order to be able to use generative AI at all, since the more accurate and better the prompt, the better the AI-generated content.