Machine Learning Is the Backbone of Next Generation Retail Applications

This is the third and final installment of our series on customer experience and how retailers can keep pace with customer decisions and deliver a true omnichannel customer experience.

Customer Experience, Omnichannel, Retail, Machine Learning Algorithms, Replenishment, Pricing

In our last blog article we’ve established that while the personalized promotions, assortments and multi-channel fulfillment are commonplace, retailers’ ability to meet their brand promise has been curtailed by lack of investment in the supply chain. This has left retailers on the back-foot and unable to keep pace with the decision-making speeds of an increasingly fickle customer, where price and experience are no longer just nice-to-haves.

However, retailers have underestimated the challenge of delivering a seamless customer experience across their portfolio. This has left a canyon between promise and performance and retailers will be in danger of alienating their customers if they can’t deliver in the right timeframes, at the right price. Retailers that have failed to invest in their supply chain are letting their customers down and failing to deliver on brand promises of convenience, availability and pricing.

So what can retailers do to deliver on their strategic vision and operationalize a seamless customer experience across the retail organization. Many retailers’ legacy business-critical merchandising and supply chain systems are rooted in slow and inflexible planning, replenishment, inventory management and pricing processes. These architectures are simply no longer fit-for-purpose in the age of the customer, where margins and inventory are lost and won with every interaction and transaction.

That said, you don’t need to throw the baby out with the bathwater. The answer lies in creating marginal gains within your existing technology infrastructure by implementing advanced machine learning algorithms, delivered through the cloud, that can slot into your existing infrastructure without having to change everything. By working with some of Europe’s largest retailers, we’ve seen first-hand that by using advanced machine learning algorithms retailers are able fulfill the new requirement of speed in decision-making.

Retail has always been about processing large amounts of data and there are growing lakes and streams of data ready to be analyzed for insights to enhance and accelerate decision-making. Advanced machine learning algorithms are key, as they will help the retailer to use this data to predict and automate replenishment and pricing decisions to match the speed of customer.

Machine learning is playing a pivotal role in redefining the economics of retail by optimizing replenishment and pricing. Indeed, it is one of the key elements in providing the experience customers have come to expect in the age of the digital, agile, innovative e-commerce behemoths. More than this, machine learning algorithms deliver against specific KPIs (margins versus mark-downs versus volume) and learn from patterns to predict demand, automate decisions and deliver profitability.

Without machine learning algorithms, retailers will be unable to adjust their value chain adequately and will either fail to deliver at the right experience or fail to deliver the right margins. Either way, retailers who do not adopt the right innovative approach to technology will languish against their competitors.

To find out more about how we’ve helped retailers with their customer experience challenges with advanced machine learning algorithms, please get in touch.

Learn more in our customer references.

Matt Hopkins Matt Hopkins

is a Retail Industry Principal at Blue Yonder. Matt has spent over 20 years in the Retail Industry, working in Supply Chain & Merchandising roles before joining JDA, Oracle Retail, Salesforce and SAP in senior leadership roles.