Over the past 18 months, shoppers have become increasingly comfortable buying items online that were previously most likely to be purchased in person. The popularity of online shopping has been accelerated rapidly, with US eCommerce brands seeing 44% growth in 2020. This has forced retailers to adapt quickly to provide consumers with the best possible online shopping experience to maximize profits during these disruptive times.
The fallout from such a seismic shift in retail shopping trends is that merchants are now also handling a mountain of product returns without the proper infrastructure in place to handle the volume in a profitable way. Managing returns is driving up costs and becoming a growing concern for business leaders.
As such, it’s never been more important for retailers to solve the reverse logistics puzzle. In today’s reverse logistics ecosystem, customer experience is increasingly reliant on high-quality processing and the nature of returns is far more complex. Returns have become a critical part of the service being provided, and consumers are expecting an omni-channel retail experience, and reverse logistics is a huge part of the overall customer experience.
Businesses require a provider that can drive real value and partnership in developing an efficient, customer-friendly process while remaining cost-effective and maximizing the value of each returned item. Effective reverse logistics can lead to better customer satisfaction, and as a result, improve the bottom line. It also ensures that, whenever possible, products are re-used rather than wasted or thrown away. This goes a long way to benefit the supply chain, the circular economy, and the environment.
There are a multitude of options for how to handle returns – from return to stock, re-manufacturing or liquidation, to resale through a secondary channel. But the speed at which these decisions must be taken makes it difficult for leaders to be sure they are not missing opportunities.
This is why an increasing number of businesses are looking instead to leverage cutting-edge technology to pinpoint these opportunities and extract the maximum possible value from every return.
Simply put, data can unlock strategic insights and inform real-time decision-making. Ideally, retailers, eCommerce sellers and others will use Artificial Intelligence (AI) to decide whether it makes economic sense to process a return or to determine the optimum disposition– even before induction. By analyzing the available data and using analytics to dynamically evaluate a variety of market factors impacting resale potential; upstream decisions can be made that reduce touches and costs and increase net recovery.
According to Shopify, 58% of shoppers say they are “not satisfied” with the ease of making returns. Poor returns processes and a lack of transparency about the returns policy can cause customers to permanently abandon a brand. Moreover, 72% of shoppers are willing to spend more per order and order more frequently, from online stores with a customer-friendly returns process.
Much like free shipping, cheap and easy returns have become a critical piece of marketing for ecommerce retailers; flexible return policies are a primary reason why consumers are willing to take a risk and buy an item they have not had the opportunity to see in person in the first place.
Online sellers need to make sure they have the technology platform and operations in place to drive a great customer experience — even through a potential return.
Consumers don’t transact with a brand or make a purchase expecting to later deal with a complicated or cumbersome returns process. So, retailers can’t expect their customers to expend tons of energy jumping through hoops to facilitate a return. Making the process simple and straightforward is therefore the key to a great customer returns experience. And to achieve this requires one thing: flexibility.
To support an outstanding customer experience for returns, you need a flexible technology platform that allows you to provide convenient return options that cater to varying customer preferences. Customers must be enabled to begin the returns process in whatever way that suits them – whether through an online portal, on the phone, or across a physical network of stores. Today, retailers require software solutions to help ensure flexibility and facilitate a streamlined returns process.
But these varying customer preferences also create a problem: how do you achieve the flexibility customers demand within a cost-effective system?
The key is to find patterns in consumer preferences and optimize your system based on this information. Understanding the patterns of your customers’ return requests, along with the patterns of those products on how frequently each item or SKU is returned, will allow you to start uncovering opportunities to drive continuous improvement across the reverse logistics ecosystem.
Today, all of that can be achieved with technology. With limited acquisition costs and very low capital investment, today’s technology is typically a cloud-based, software as a service (SaaS) platform that can be deployed across your entire physical network, enabling consistency, adding value, and providing the backbone for a great customer experience by analyzing consumer behavior.
Ultimately, aggregating the information on your returns enables you to start building the data model required to optimize your disposition decisions in real time. And once that model is built, you can start leveraging machine learning (ML) to optimize return dispositioning and eventually automate the process for even greater marginal efficiency gains.
Such gains, however, are not the only benefit analytics can offer. Though financial efficiency is important, for many businesses an equally valuable application of recovery analytics relates to saving the planet.
Sustainability is considered among the most urgent issues of our time. And for businesses both big and small, there is a clear mandate to become as environmentally friendly as possible.
According to recent surveys, 62% of consumers want companies to take a stand on sustainability, while 75% of consumers will refuse to purchase a product if they find out the company supplying it supports an issue contrary to their beliefs.
Through better returns management, businesses can disposition and recover items so that they stay out of landfills and garbage dumps. Analytics can help find ways to ensure items are repurposed wherever possible, ultimately reducing the carbon footprint while increasing profitability.
Discover how G2 Reverse Logistics uses data analytics to solve the reverse logistics puzzle and optimize your consumer brand experience. For information and resources check out g2rl.com or reach out to