How Brick-And-Mortar Stores Can Use Data To Compete With E-Commerce


Anat Shakedd, Co-Founder & CEO of Nexite

Despite much naysaying, the Covid-19 pandemic did not issue a death knell to the brick-and-mortar retail industry. But if businesses can’t or won’t adapt, the current crisis of inflation just might.

As we emerged from the global pandemic, the National Retail Foundation (NRF) said retail was “growing at levels not seen in over 20 years” and forecast that sales would grow by between 6% and 8% in 2022, to more than $4.9 trillion. But record-high inflation is taking nearly all the wind out of those sales: This month, Target reported its biggest drop in shares in 30 years, while Walmart and other big-box retailers pointed to worrying consumer trends—more penny-pinching, much more fat to be trimmed—as families look for any way to save with prices skyrocketing.

What Physical Stores Can Learn From Digital

So how can retailers regain lost momentum and bounce back, particularly after months of extended shutdowns? The Covid-19 pandemic widened the gulf between brick-and-mortar and e-commerce, particularly in terms of impression, engagement and conversion. The pandemic, which brought $244 billion to the U.S. e-commerce industry in 2020 alone, also brought us billions of data points about the efficacy of online shopping and the advantages that web commerce offers retailers in terms of tracking their merchandise, engaging customers and optimizing their sales.

In a physical store, the intricate, granular details that make or break a sale often come down to the interactions shoppers have with minimum-wage salespeople with little long-term commitment to their roles. What shirt goes with these pants? Which bag and shoes can take this outfit from ordinary to extraordinary? In the hands of a capable salesperson, deals are closed and shoppers turn from browsers to buyers.

But retail has always had a problem with turnover among salespeople, even before the “Great Resignation,” in which nearly 44% of workers polled in December 2021 and January 2022 were on the hunt for a new role or planning to look soon. When salespeople exit their jobs, all of the data and insider tips that can make or break a shopping experience will exit with them.

Online retailers have significantly more control. Algorithms can offer online shoppers related items to peruse, while data tracking keeps tabs on the entire customer journey, as well as merchandising and inventory, down to the details of what sells best where and to whom.

How Brick-And-Mortar Stores Can Compete

For brick-and-mortar retail to truly compete against e-commerce, the post-pandemic shopping experience is going to have to be radically different. Technology can serve as a bulwark against high employee turnover, ensuring that even in the face of staffing shortages or multiple resignations, the in-person shopping experience can become more consistent and streamlined.

Salespeople end up with a monopoly on the vital data that drives a brand’s business. But far too often, they don’t have the long-term commitment or loyalty to a brand to handle that data with care. And when they do, they are not offered ways to share that data with headquarters or even properly transmit it to the workers who take over for them when their shift is finished, or they decide to move on to other jobs. That data includes:

• Where are people walking in your store?

• Are they engaging with or trying on products?

• Did they ultimately purchase the items they engaged with?

• Did a specific style see high engagement but little purchase?

• Were there specific items that sold better when placed together?

Right now, the in-person sales experience comes down almost entirely to the interactions between shoppers and employees. Retailers have no automated way to collect the data on the customer journey and merchandise lifecycle that we see in e-commerce. Instead, they rely on staff who are tasked to sell, stock, service and fulfill online orders—staff who are in many cases too busy or unequipped to do all these things simultaneously. This does a disservice both to brands and their employees.

Shared Data Is The Key

But what if data observed in the store by employees could be automatically collected, filtered and sent back to headquarters to help drive decision making at the C-level? What if the salesperson who moves a certain style of sweater to a different location and notices that sweater starting to fly off the shelves could apply that knowledge to stores across the brand’s entire network? Merchandising would be improved, allocation would be more specific to remove overstock and stockouts and store displays would shift from ad-hoc to entirely strategic. Optimization, in real time, would become data-based and seamless. (Full disclosure: My company offers these data insights via an in-store tech platform for retail businesses.)

It’s time to use technology to unlock this data from individual salespeople and put it into a broader system. The data needs to be automated and disseminated to workers across the company, collecting meaningful, actionable insights to send back to headquarters in real time so that brick-and-mortar stores can be optimized on the fly. And using that data, retailers can offer customers an in-person, experiential way to shop that is more personalized and tangible than e-commerce.

According to a recent report by McKinsey, fashion companies are looking to double investment in technologies by 2030 to keep up with digital natives and gain a competitive edge. Solutions that can harness data in the store and feed it back in real time will offer shoppers more connected experiences, retailers more opportunities for sales and efficiencies and will ultimately change the face of physical retail.


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