How COVID-19 has accelerated a new digitized normal for retailers
World events are accelerating change in the retail industry.
As retailers operate through a global pandemic, many are rethinking all aspects of their businesses in order to prepare for the “new normal.” Will consumers’ massive shift to online channels stick? If so, do existing investments in technology and IT infrastructure take into account what will be needed for retailers to successfully engage consumers? And, just as important, how can retailers identify cost efficiencies across their organizations while simultaneously doubling down on innovation?
As retailers work to recover revenue and attract new shoppers, they need to quickly drive costs out of the business. Cloud technologies will be the key enabler for companies here, whether that’s to reinvent legacy applications for new value, drive efficiencies into the supply chain, or enable differentiated customer experiences regardless of channel.
Cloud migration significantly cuts costs for retailers, enabling them to reallocate those funds to experiments. Retailers can then reinvest that newfound budget into new initiatives such as machine learning (ML) projects that identify counterintuitive insights about their business and shoppers.
This results not only in operational efficiencies, but also in uncovering new ways to delight shoppers based on new habits formed during lockdown. Because of the cloud’s agility, we’re seeing many projects that once took years to get done being accomplished in just weeks, and those that took weeks now completed within days. For example, during the onset of COVID-19, our retail customers were able to set up call centers in less than two days for remote workers. That’s cloud agility in action.
Here are just a few ways our customers are innovating during these uncertain times as they accelerate the migration of core applications to the cloud:
- Using machine learning to identify counterintuitive insights that can deliver significant business impact.
Retailers are moving beyond traditional data analytics to apply machine learning (ML) to get counterintuitive and previously unseen insights that help them respond to business trends in near-real-time during the pandemic. An industry that is benefitting from these insights is grocery. At the outset of the pandemic, grocers nationwide saw product shortages as consumers rushed to stock up on items like paper towels, toilet paper, and sanitizers. As the supply chain begins to recalibrate, grocers now need better insights for SKU rationalization, as well as demand forecasting and allocation.
- Accelerating digital transformation across the entire organization.
As stores begin to reopen, shoppers want as many contactless experiences as possible – from contactless mobile payments and cashier-less shopping to safe and easy curb-side pickup. Buy-online-pickup-in-store (BOPIS) is rapidly moving toward a buy-online-pickup-at-curb (BOPAC) model. In order for BOPAC to be successful, retailers must remove friction in the pickup experience.
For example, when Prime members in Seattle arrive at an Amazon Fresh building to pick up their online grocery orders, technology automatically identifies their license plate and parking spot, alerting an associate to load the order without the member ever having to call the store or leave their car.
Inside stores, retailers are using machine vision technology to better understand store traffic patterns and redesign store layouts to naturally encourage social distancing. Being able to identify areas of shopper density enables retailers to redirect traffic patterns to adhere to social distancing guidelines without having store associates monitor and enforce distancing rules during their shifts.
- Managing in-store inventory in new ways.
As curbside pickup becomes an increasingly popular option for shoppers, stores are becoming micro-fulfillment centers. This creates new challenges and opportunities for retailers to adapt stores to make employees more efficient, including facilitating new tech-driven processes for multi-order picking.
It’s also critical that retailers understand which stores have an item in stock and how many units are available in each location. When a retailer fails to understand inventory in real-time, the customer experience falls apart, placing customer loyalty in jeopardy. Computer vision and IoT sensors such as RFID are efficient ways for retailers to track what items are on store shelves at all times and what needs to be replenished so consumers are never disappointed with the click-and-collect experience.
Reinventing the retail store experience will take time. It will require looking at how voice, machine vision, robotics, IoT, and other technologies can make stores safer and provide shoppers with a better experience. Change won’t happen overnight, but it’s necessary for retailers to protect themselves from future unexpected events and disruptions by creating efficient ways to experiment and deploy new customer engagement approaches and internal operations as they reimagine the future of retail.
Tom Litchford is global head – retail & wholesale trade at Amazon Web Services.
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