How Retailers Can Build a Post-COVID Data-Driven Customer Strategy
Hundreds of thousands of people around the world have died from COVID-19 with more than 120,000 of the deaths in the United States alone. Unemployment has soared to the worst levels since the Great Depression. Consumer confidence is at an all-time low. The ripple effect of the pandemic is being felt in nearly every corner of the world – from boardrooms, farms and manufacturers to retailers unsure when a level of normality will return.
With the crisis now nearing its sixth month in the United States, we know that our post-COVID world will look different than it did before the pandemic. Since mid-March, consumers have quickly adopted new behaviors that will likely stick at least until the crisis fully subsides, which may not be until there’s a viable vaccine. On average, it takes 66 days for new behaviors to become automatic. U.S. consumers crossed that milestone in mid-May.
When the stay-at-home orders first took effect in mid-March, many consumers for the first time flocked online to buy groceries, household supplies and over-the-counter medications, which overloaded a number of online retailers as well as their delivery partners. But over the weeks that followed, retailers and delivery services added additional personnel to respond to the customer demand. Before the pandemic, e-commerce hovered around 5% of grocery spend.
According to eMarketer, online grocery shopping (including click-and-collect) jumped at least 200% in March, compared with the same period last year. Market share will likely fall but stabilize higher than pre-COVID levels, once a viable vaccine is ready.
Given these unique circumstances, how are retailers supposed to plan for the future?
Here are some top-of-mind questions for both retailers and manufacturers: Will consumers return to their old routines, or will they keep up their new shopping routines once the pandemic subsides? With close to 40% of all households being at risk, it’s not likely shoppers will return to routine activities until a vaccine is widely available.
Building a Framework
With that in mind, retailers can more easily navigate the uncertain days and months ahead by understanding and maintaining engagement with both new and returning customers. To do this, retailers need to build a customer response model based on customer data and information. The key is to build this model with speed and agility, and to be willing to pivot depending on where the data leads. Here are the steps to get you there:
- Develop a model and framework that will create a hypothesis, focus the organization, and communicate expectations across the business. The customer response model should draw on data and information on all three phases of the crisis: 1) insecurity, 2) transition and 3) recovery. Even though we are now well into the transition phase, it’s important to build out all three stages in the model, since much is still unknown about the future. The framework should examine the following factors for each phase of the crisis: consumers’ behavior, level of COVID activity, economy, food prices, grocery sales, price sensitivity, price and promotions, assortment, and e-commerce.
- Determine how data-driven customer-first strategies will decide who will thrive after the curve. While the majority of consumers are still shopping in stores, they’re making fewer trips, but with larger baskets to stock up. Largely gone for now are the days of shopping in four to six different stores each month to hunt for the lowest prices on particular items. Because there are far fewer opportunities to get shoppers to buy, retailers will need to rethink their strategies.
- Bring customer data and insights together to build the forecast model that helps your organization navigate and plan through uncertainty. So, what does it mean to be “customer first?” It means applying the data and insights to align your organization with the evolving customer. Today, retailers should focus on 1) investing and prioritizing promotions on popular, trip-driving products and whole basket offers; 2) delivering on key customer need states across the store to win stock-up shops; 3) building private brands through self-funded promotions; 4) investing in perishable categories; and 5) improving mobile apps to increase prepared food sales.
The model needs to explain how changes in COVID-19, the economy and grocery prices will affect sales. To accurately gauge the changes in COVID-19, use data from sources such as the IHME and the Worldometer. To track the economy, use data from the government on Food Away From Home (FAFH), the University of Michigan’s Consumer Sentiment surveys, air travel, hotel occupancy and jobless claims. Make sure to employ data from sources like the Federal Reserve and investment bank forecasts. For understanding grocery prices, the model needs to draw on all of the economic data that you’ve collected, including oil prices, the strength or weakness of the U.S. dollar, the Food and Feed PPI, and, of course, your own grocery sale data.
Final note: customer-first strategies aren’t just for grocery giants. Whether you have two stores or 2,000, building a customer response model will give you an incredibly powerful tool to navigate the uncertain days and months ahead. With this model, you’ll be able to quickly pivot your retail strategy based on changing conditions and the deep insights that your data provides. Most of all, you’ll increase your customer engagement, because you’ll be putting your customers first.