As the internet has democratized data, consumers have become accustomed to instant answers and the multitude of options offered through digital marketplaces. Shoppers now expect more regular product refreshes, up-to-date information on availability, a wider variety of tailored products, and the ability to shop anywhere, at any time. Additionally, viral social media posts are legendary for creating buying frenzies – or the opposite: squashing demand quickly.
This environment is vastly different from the pre-digital era, where information in the marketplace was fragmented and worked to the retailer’s advantage. Comparison shopping required significantly more time and effort than scrolling through options online. This imbalance also allowed retailers to push products to the consumer, a model that was cyclical and relatively predictable. Consumers’ expectations matched the slower pace of new product creation, and comparatively long lead times in the supply chain were acceptable.
Today, however, complex globalized retail supply chains run by legacy systems are feeling the pains of this faster pace and the need for a broader range of choices. How can retail supply chains increase their responsiveness and meet consumers’ expectations?
Understanding the consumer in detail – to be able to better forecast product and inventory needs – is one key to success. Artificial intelligence (AI), with its business intelligence and analytics applications and cognitive services, can help retailers achieve more specificity in data. It allows them to analyze consumer behavior with more granularity than ever – potentially to the level of consumer segments of one. AI also can be used to target consumers more accurately with personalized offers – necessary to compete in an era of mass personalization – which can lead to better conversion and more predictable sales.
Another key to success is responsiveness. When viral trends or other unanticipated events create spikes in demand, machine learning draws real-time insights and recommends actions, based on evidence, faster than any human. It takes data-driven decision making to a new level, one that is crucial to support a nimble supply chain in an ever-changing marketplace.
At Microsoft, we understand the challenges of retail transformation and can help you leverage the capabilities of AI and machine learning to improve the responsiveness of your supply chain.
For more of our perspective on retail supply chain optimization, read The Anywhere, Anytime Consumer: Adapting the Retail Supply Chain, an e-book written by retail strategy and technology experts from Microsoft Services.