COVID-19 has caused seismic shifts across industries. For the retail industry, businesses have seen widely varying effects depending on the kind of service they provide.
Department store and specialty/boutique retailers experienced thousands of store closures and significant business disruption as consumers cut non-essential spending and made the sweeping shift to online shopping.
They’re now left to face the lofty challenge of finding a viable strategy to recover and reset after months of global economic slowdown whilst also planning for an uncertain future of commerce, as some customers may fear returning to stores until the pandemic concludes.
At the same time, grocery and convenience store retailers have seen increased sales and increased demand to serve customers in new ways. Many are offering online shopping apps and various methods of contactless shopping, including home delivery and curb-side pickup — all to ensure customer health and safety is top priority.
Regardless of business type, retailers are facing a tough new reality as they try to plan for the path ahead. But the key to recovery and long-term success post-COVID won’t be about outrageous sales, or influencers, or going completely digital. The secret is something you might not expect: Data.
Historically, data has been a retailer’s pain point. Many lack time, staff, and funds to track, analyze, and utilize it. Yet, it’s the greatest opportunity for sustained business growth due to its ability to help retailers better understand consumer needs, capitalize on digital commerce, and track customer shopping patterns over time. Now is the time for every retailer to make use of their data to drive customer loyalty, trust, engagement, and safety beyond the pandemic.
Much of retailers’ most valuable data lies in the IT infrastructure itself, but the cloud is a critical piece of accessing that data. If retailers have not yet moved to the cloud, now is the time to make the leap. Not only does cloud management simplify tasks and maintenance, improve business operational uptime, and allow retailers to scale up and down depending on demand, it helps retailers unlock the full potential of customer data to advance customer-centric initiatives. Cloud-managed networks deliver big data that can be mined for granular insights and used to enhance in-store customer engagement, create value-added experiences, and most importantly, maintain customer health and safety demands.
Cloud platforms also enable retailers to track real-time and historical customer trends, in-store and online engagements, and the impact of marketing/sales promotions. This is incredibly important now, as every interaction with customers is meaningful, and in-store experiences must be optimized and delivered safely to ensure consumers will return. Additionally, deploying a flexible, scalable cloud infrastructure can help retailers prepare for the online frenzy ahead of this year’s holiday shopping season.
The greatest challenge with data isn’t typically collecting it, it’s using it. Once retailers have a cloud-based infrastructure in place, the key is feeding that data into ML/AI tools to create personalized experiences and predict future spending trends. By using ML/AI, retailers can learn more about their customers – their behaviors, preferences, and how they engage with the brand – both during and post- COVID-19. This data can also ensure retailers uphold customer health and safety protocols across their stores in distributed regions and geographies, which is critical during the pandemic.
Predictive analytics uses ML/AI to sift data and build models that depict consumers’ potential behaviors and product interests. This can assist retailers in several ways, from price optimization to planning for anticipated inventory to even driving new product developments. Because COVID-19 has created shifts in consumer shopping patterns, retailers must home in on this year’s insights when using the predictive model to capture a 360-view of their current consumer.
After retailers target their consumer base at the individual level, predictive analytics can also help them use customer segmentation to group consumers based on their interests and preferences. Retailers can use data analytical tools to segment audiences by demographics, customer lifestyle, and behavioral factors (whether they are a loyal, repeat, or new customer). This enables retailers to gather a clear understanding of their consumer breakdown and how they should market products depending on the segment group, which is beneficial for retailers looking ahead to plan their marketing strategy for a post-COVID retail environment.
Segmentation can also group consumers by their online basket size, the level of frequency in which they shop, and their reason for each store visit. With the pandemic shifting the way consumers shop, the combination of personalization and segmentation can help retailers increase their consumer engagement, drive sales, and retain customers long term.
COVID-19 has shaken the foundation of traditional retail, and only time will determine its long-term implications on the industry’s growth. Retailers’ way forward post-pandemic will hinge on their data and how they use it to brace for rapid disruptions and entice today’s budget-strapped consumer. Developing a customer-centric data strategy that’s built on the cloud should be at the top of every business leaders’ priority list as we head further into the new normal.
This article was originally published to Retail Customer Experience on September 22, 2020.