How data streaming can address the returns culture in retail and boost profits
By Lyndon Hedderly Event streaming and Apache Kafka technology should be a critical component of every retailer’s technology stack.
This article appeared in ITProPortal in March '21
The Office for National Statistics recently published an estimate of retail sales across 2020. When compared to 2019, traditional bricks-and-mortar (non-food) retailers reported an annual fall in revenue of 25 percent. That said, it is not all bad news. Online retailing saw a record annual increase of 32 percent, with total values across the year rising by 46 percent - the highest annual growth since 2008.
Unsurprisingly, the retailers who fared better during the pandemic were those who had a head-start in online and state-of-the-art digital capabilities. Many organizations had to pedal hard to catch up. McKinsey & Co. observed “we have vaulted five years forward in consumer and business digital adoption in a matter of around eight weeks.” It became clear very early on that only through digital optimization could retailers survive the impact Covid-19 and lockdowns are having on their businesses.
The acceleration towards a digital-first approach in retail, however, is a double-edged sword. As sales soar, so too does returns culture: consumers buying online, knowing they are likely to send some goods back. This is becoming an increasingly pressing matter for most retailers - a recent study, for example, found that items bought online and returned in the UK were worth £5.2bn annually.
Effectively offering the flexibility customers demand from returns policies while preventing damaging financial losses is a top priority for every online retail organization. Many businesses are turning to event streaming, underpinned by open source Apache Kafka technology, to help navigate this process seamlessly. Here is why.
Why addressing the ‘returns culture’ is so critical
In an industry where margins are increasingly under pressure from rising costs, lower pricing and the need to optimize the digital experience, returns hit retailers in three main ways.
Firstly, returns raise the cost of fulfillment and logistics across the supply-chain. A return often entails a 100 percent refund to customers and the shipping costs double, as the items need to be picked up, often by courier, resulting in a direct net operating loss.
Secondly, a lot of critical data supporting the supply-chain, logistics and the buying and returns process, may be scattered across many different platforms. This includes point-of-sale (POS), e-commerce platforms, enterprise resource planning and supply chain and logistics interfaces. To add to the complexity, legacy systems may run in on-premises data centers while customer-facing apps and interfaces may reside in the cloud. Some retailers are still managing returns through excel spreadsheets. As retailers strive to improve their customer experience, they must focus on improving the overall returns process.
Thirdly, returns impact reported revenue - and are such a problem, they now feature in most retailers annual reports as a key audit matter. Retailers must make provisions for returns in their financial statements, which can account for around 2-3 percent of revenue. As returns are increasing year-on-year, current provisions are proving inadequate and are likely to have to increase.
Event streaming: helping solve part of the returns challenge
So, what can retailers do in the face of the rising returns shopping culture? Just as investments in digital helped during the pandemic, so too can they help address the problem of returns.
An event streaming platform helps retailers streamline the returns process by ensuring all the data sources across the value chain are directly speaking to one another, and that every ‘event’ triggered in the returns process is shared in real-time. The technology is the instant link between all of a retailer’s footprints, from e-commerce tools such as content management systems, supply chain and logistics technology and in-store technology (when shops open again).
Connecting these disparate data sources is beneficial on three fronts:
The importance of streaming analytics and capturing insights for real-time business decision making
By simplifying the data integration across different systems - from production to POS, and beyond - the retailer is able to track the delivered item, the returns request online and the courier company pick-up to receivables at the warehouse. They might even track new data sources, such as the social media sentiment analysis once the return and refund has been processed. This significantly reduces data integration complexity and allows the retailer not only to build the best experience for the customer, but also drive efficiency and reduce costs.
An event streaming platform provides a real-time accurate view of stock, as it ’s returned to the warehouse and potentially re-offered for sale. This helps the retailers update their inventory, in real-time, maximizing on warehouse space and the supply of high-demand items.
Finally, implementing an event streaming platform, retailers can provide the foundations for running a modern business. The traditional spaghetti mess of data integration across legacy systems can be replaced with a modern ‘central nervous system’. This makes it easier for retailers to build a real-time business. The retailer can get more specific insight into their financial position, based on real-time events during the returns process.
A fresh way of thinking
The pandemic has only accelerated what we already knew: customer behaviors are evolving and online shopping is rapidly becoming the status quo. To keep up and meet heightened consumer demands, it is important that retailers address the returns problem – and fast.
This requires a fresh way of thinking about connecting data sources across the business, which is why a growing number of retailers are taking advantage of event streaming platforms. Put simply, event streaming and, in turn, Apache Kafka, should be a critical component of every retailer’s technology stack.
Lyndon Hedderly, director, customer solutions, Confluent