Changing the Narrative: Setting the Stage for Retail Recovery
by Nick Jordan, on August 3, 2020
The impacts of COVID-19 on the retail sector exposed the need for retailers to better plan for future business disruptions. Artificial intelligence and real-time analytics will be the drivers of post-COVID recovery for the retail industry, providing the information needed to restructure inventory and service for an uncertain future.
At the start of 2020, the biggest challenges for the retail industry were issues such as market saturation, finding new ways for old and aging brands to stay relevant, and the impact of new technologies and innovations. No one anticipated the greatest challenge of 2020 — and beyond — would be a pandemic that shut down the world.
According to McKinsey, 80 percent of U.S. retailers shut down at least part of their business operations, and 44 percent closed their doors altogether during stay-at-home orders. Yet many of these respondents anticipate that, when stores reopen to full business, they will return to pre-crisis levels, and perhaps even be stronger. Those that could turn to e-commerce operations did so with some success, and this shift has many in the industry looking at a change in how they’ll do business going forward.
However, because most medical experts expect a second wave of COVID-19 and because they warn of other major public health crises in our future, retailers can’t just plan for the short term in a post-COVID world. They need to plan for survival during long-term shutdowns and stalled operations. The best way to approach this plan is with data-driven solutions.
Data-driven reinvention of retail and the customer experience
While retailers are optimistic about the future, consumers are less so. Only 37 percent think there will be a quick rebound in the economy, and 44 percent said they were delaying purchases through the crisis due to an uncertain financial future.
Retailers can’t survive if consumers aren’t buying, but how do you attract people to make nonessential purchases if they aren’t confident when or if they’ll return to their job?
“Retailers can minimize current and future business impacts by identifying and executing on controllable activities,” Kelsie Marian, senior director analyst with Gartner's CIO Research Group, wrote for Retail Dive. “In the short term, they must identify and optimize existing technologies and business models. In the longer term, the focus should be on evolving business models and enabling transformational change with new and emerging technology.”
The driving factor that makes these technologies successful is how well they utilize data. During the worst of the pandemic’s shutdown orders, essential retailers struggled to meet the supply and demand of items. Toilet paper, cleaning supplies, hand soap and sanitizers, yeast and flour, canned vegetables, meat, and even bottled water have been nearly impossible to find in many locations. Retailers relied on the data of normal customer shopping habits and weren’t able to make the pivot necessary to meet increased consumer needs.
However, it wasn’t just retailers managing this shift; supply chains also had to adapt. As offices and restaurants remain closed, more emphasis will be on individuals making smaller purchases rather than on supplies sent to warehouses waiting for industrial orders. The challenge with data-driven models is that there's no history for this type of data analysis. While you might have been able to predict an increased need for toilet paper, no one anticipated millions of households would begin baking their own bread. With expectations that remote work will remain high and uncertainty around how other industries will recover, retailers can no longer rely on historical data to stock shelves.
Artificial intelligence is key to rebuilding retail business operations
Artificial intelligence (AI) and machine learning, however, could be the key to providing retailers with the tools they need to recover and rebuild their business operations. AI offers the technology needed to make swift adjustments when situations change in a matter of hours. It can quickly detect patterns in the data that separate real-time information from background noise.
“By alerting the retailer of emerging trends that human analysis would miss, AI gives retailers time to change product mixes, merchandising, messaging, etc., to increase sales,” Geoff Watts, CEO of retail technology firm EDITED, told PYMNTS.com.
One thing AI can do is track multiple and disparate sources of data and parse that information into something specific that retailers can use to anticipate what they should have in stores and how consumers are behaving. For example, AI offered glimpses into what was happening in China in the early winter, not just with the virus, but within the supply chain. Similar data could have investigated the buying habits of Europeans, where countries were on strict lockdown. That data could have then been translated for American retailers to anticipate what consumers were buying in person, what they were buying online, and where shortfalls would be in the supply chain.
Real-time data and analytics is crucial
COVID-19 hasn’t been all doom and gloom for the retail industry. Online retailers saw a boom in business in March, with sectors like home goods, athletic supplies, and loungewear seeing record numbers. Shopping online made sense, but why did those particular sectors do so well? They sold products that met the needs of people spending all of their time at home. Not only did they need flour and yeast to make bread, but they also needed the right cookware. With gyms off-limits, consumers wanted workout equipment. And yoga pants are perfect Netflix-binging attire.
“Retailers need to have an agile, real-time focus — this applies to all areas of the business, including but not limited to marketing, cash management, inventory management, and supply chain,” stated Total Retail. “An example of this is using real-time analytics and data to quickly pivot marketing/media dollars to capture demand in the online channel.” Those retail sectors that did well during the shutdown had the items consumers wanted. With the country reopening, those needs will shift, and real-time data and analytics should be advising that yoga pants buyers now need new work clothes.
The challenge isn’t just adjusting to the current consumer mind-set, but also coming up with solutions to stay afloat if customers don’t return to pre-March levels of purchasing or a second wave creates a setback. Here’s where data about consumers can help retailers be creative and stay in business. According to the Harvard Business Review, “Knowledge of your customers has never been more valuable to your business. Marketers need to analyze data about their customers’ behaviors and buying habits on a daily basis to learn what's changing and what's not. What new unmet needs have emerged? What new pain points have surfaced? What new markets are emerging for your company?” Also use that data to create unique opportunities for regular customers that subtly encourage them to make a purchase. Hold an online book discussion and offer that book and corresponding products for sale. Fitness centers are using data to help determine their most popular classes and offering them online to members and potential members.
Retailers have long depended on data to build a loyal customer base. Those strategies, like loyalty programs and sending targeted coupons or product suggestions while shopping, will encourage your customers to return when they can. But retailers thrive when they attract new business. Data will now be the driver for post-COVID recovery, as retailers discover how data and technologies offer the information needed to restructure inventory and service in what promises to be a very unsettled future.