Business analysts have called 2020 a breakthrough year for the e-commerce industry – and with good reason. Online sales have been growing exponentially since the start of the pandemic. Jeff Bezos’ Amazon just had its best haul ever – notching up $386 billion in net sales

In fact, retail stores are now starting online stores of their own to avoid falling behind in the race for market dominance. Slowly but surely, a new hybrid retail model is starting to emerge. However, there’s one area where traditional brick and mortar stores still have the upper hand over their e-commerce counterparts – product returns.

During the peak season, up to 30% of all online sales are returned. The price tag is $50 billion a year. In comparison, the return rate for in-store purchases was a mere  8%

The reasons vary from poor fit to incorrect/ defective items shipped- some legitimate, others frivolous. Ecommerce brands are evaluating the ‘try before you buy’ concept to address this. However, the cost is prohibitive. The truth is that returns are an inescapable fact of life for e-commerce businesses, and to protect their margins, the focus should be on optimizing returns management.

What is Automated Ecommerce Returns Management?

If you are a small online business, a couple of employees may be all you need to handle returns efficiently. However, as you scale, adding more and more people to the team could impact your operating costs without offering any measurable efficiency benefits. Ultimately, it may take weeks for customers to get their refunds, potentially exposing you to negative customer reviews and complaints. For example, maintaining returns data in Excel spreadsheets may be inexpensive, but manual data entry can increase errors and omissions over a period of time.

These mistakes will inevitably affect your margins, considering the high cost of return shipping, storage, refurbishing returned orders, and even training new employees. Besides, you may not be able to track serial returners if order history data is unavailable effectively.

The solution: eCommerce brands across the spectrum have been investing in a variety of web and mobile apps to streamline the collection, tracking, and processing of returned orders efficiently. These tools are connected to the warehouse and logistics providers, giving company executives a 360-degree view of returned inventory and the ability to reconcile sales with returns seamlessly. 

They also synchronize multiple elements such as logistics, inventory management, and customer service, reducing duplicate entries and shipping costs. Thanks to better visibility, products good enough to be resold can be reconditioned, while those with production defects can be routed back to the manufacturer. 

Automated returns management tools also enable you to make data-driven decisions pertaining to returned stock and extract the most value from it.

How to Completely Automate Ecommerce Returns Management with Conversational AI Chatbot

How-to-Completely-Automate-Ecommerce-Returns-Infograph

To streamline your return processes, it is best to start at the point of origin itself. A clear, easy-to-understand returns policy is a must-have. However, proper categorization of return requests is just as important. There are multiple scenarios where accurate classification at the initial stage can obviate the need for a pick-up in the first place. For example, if it can be established that a product is damaged beyond repair, the customer can be told to dispose of it himself. This will save the cost incurred on shipping the item back to the distribution center, only to be scrapped.

Most online returns management software is not equipped to identify the extent of the damage correctly. This is where conversational AI chatbots can make a difference. They not only respond to customer queries instantly but also act as a gatekeeper when accepting return requests. The result: accelerated collection and processing of returned items.

Here is how automated AI chatbots can be used at various stages of a typical returns management workflow to boost efficiency and deliver a positive customer experience:

1. Return Request Stage:

When a customer clicks on the return request option, the helpdesk chatbot should display their recent order history upfront and allow them to choose the items they want to return. If there is more than one item to be returned, the customer should be given the option to do so in one go. However, if the items in question are being returned for different reasons, they can be entered individually. If the customer has the order ID number handy, the chatbot can bring up the order details on-screen and prompt them to enter the reason for return. 

What-is-Automated-Ecommerce-Returns-Management

2. Authorization Stage:

This is a crucial stage with many cost and efficiency implications for an e-commerce business. Here, the conversational AI chatbot is required to verify whether or not the return request meets the company’s terms and conditions. For example, products with a broken seal or missing tags may not be eligible for a refund. 

The AI chatbot verifies this by prompting the customer to take a picture of the package and then scanning it. Depending on the returns policy, it can also make exceptions. For example, if the item received was not what the customer originally ordered, a return request for an unboxed item may still be approved.

In case the item was damaged on arrival, the chatbot will use its algorithms to scan the image, assess the damage, process the return, and give the customer a confirmation number. If no damage was detected, it could route the customer to an agent for further assistance. If the product is damaged beyond repair, the customer can be asked to dispose of it, and the refund may be approved, subject to the applicable terms and conditions. 

When a return request is declined for any reason, the conversational chatbot will need to explain the reasons for the same to the customer.  

3. Collection Stage:

Collection-Stage

At this stage, the customer can be given a menu of pick-up or drop-off options to return the product in question. For example, the customer should be able to choose whether they want a doorstep pick-up or would rather drop it off themselves at a nearby store or collection point. 

In addition, the customer should be able to select a convenient time slot in case of pickup based on their preference. In either case, the helpdesk chatbot should provide a complete list of shipping carrier services and store locations, respectively. It must also generate a Return Merchandise Authorization (RMA) for the customer, which sets the refund process in motion.

4. Processing Refund:

Ecommerce companies usually provide two options to customers returning orders- a refund or replacement under warranty. Although they are a staple with retail stores, exchange offers, store credit, or gift cards may also be available during the holiday season. A refund is applied to customers’ checking accounts or credit cards as soon as the RMA is generated. The logistics provider will continue to update the delivery status on the back-end until the package arrives at the distribution center.

In the case of in-store drop-off, the refund/credit can be processed instantly as long as the value of the order does not exceed a predetermined amount threshold. This feature is critical from the customer experience point of view and can deter serial returners. According to a study by Narvar, a Customer Experience platform, 38% of customers expect instant refunds on returned items.

5. Replacement Request:

In case the customer asks for a replacement, the helpdesk chatbot can instantly book a new order against the RMA issued earlier. However, it should be integrated on the back-end with the company’s inventory management and accounting system for this to happen. This will allow it to check for product availability and reconcile sales with returns.

Takeaways:

Staying engaged with customers throughout the returns process can be the answer you have been looking for to minimize returns volumes. Conversational AI comes with intent detection algorithms that can help e-commerce brands preempt returns by providing tailored recommendations to customers at checkout. If the customer decides to proceed, it can analyze, approve, and disposition refund requests with minimal intervention from agents. 

The result: reduced call volumes, lower labor costs, and better SLAs.

Take charge of your e-commerce returns volumes with customized conversational AI solutions from Insync AI. Our proven solutions reduce the bottom-line impact from returns and enhance your margins over a while.