Black Friday used to mean 24-hours of in-store sales that kicked off the holiday shopping season and sent bargain hunters into a frenzy. In recent years, however, the COVID-19 pandemic, rise of online shopping, and an economy marked by high inflation have fundamentally changed the way consumers buy everyday goods and holiday gifts alike. As a result, seasonal bargains are no longer limited to just the day after Thanksgiving.
Instead, shoppers now have more say in how, where, and for how much they’ll purchase presents in 2022. While bargain hunters of the past once had to strategize and wait in lines to scoop up scarce inventory at specific locations, today’s shoppers can now make side-by-side comparisons while they shop and preview items with just a few clicks on their phones—not to mention leverage services like curbside pickup that fully blur the line between online and physical retail.
As a result, the weekend after Thanksgiving this year—traditionally bookended by Black Friday mayhem in stores and Cyber Monday flash sales online—marked the start of what experts are calling the first truly omnichannel holiday shopping season.
Sales are up in-store, online and everywhere in between
According to numerous sources, spending was up across online marketplaces and physical retailers the last weekend of November 2022. In total, 196.7 million shoppers made purchases from Thanksgiving Day through Cyber Monday, according to the National Retail Federation (NRF), which was a significant jump from last year’s turnout of 179 million.
What’s most interesting, however, is that the sales gains were spread pretty evenly between online and physical retailers over the weekend. Mastercard SpendingPulse, which tracks both brick-and-mortar and eCommerce sales, said in-store purchases were up 12 percent year-over-year, while online sales rose 14 percent.
Perhaps the most surprising stat comes from Sensormatic Solutions, which tracks in-store foot traffic for retailers, and clocked a 2.9 percent jump in shoppers on Black Friday specifically compared to 2021. With fewer Covid restrictions in 2022 compared to last year, a rise for in-person purchases may have seemed inevitable, but when comparing foot traffic to actual dollars spent over the period, a different picture emerges.
For Black Friday specifically, in-person sales only rose 0.1 percent from 2021, despite the boost in actual feet on the ground at stores. While the evidence is largely anecdotal, this indicates that shoppers are less concerned about meeting sales deadlines and are instead using the in-person experience to “window shop” before ultimately buying a product online or in stores at a later date.
New shopping trends call for new retail solutions
This confluence of trends presents new opportunities and challenges for retailers, who need to synchronize their physical and digital footprints to support omnichannel shopper tastes. In the current scenario, the footprint for customer engagement has never been greater for retailers, while the potential for missed opportunities (and revenue) has grown in tandem.
To ensure retailers aren’t missing out on every opportunity to engage and satisfy customers—and ultimately ensure sales—they need to leverage new solutions that can bridge physical and digital environments while meeting customers on their terms.
Computer vision strategies are already being deployed to help retailers both improve customer engagement while also streamlining their operations. By automating certain functions and analyzing visual data to optimize everything from store layout to customer dwell time, vision AI strategies can be a boon for retailers as they navigate the new omnichannel shopping reality.
For instance, when foot traffic is up but in-store purchases aren’t rising in kind, computer vision has the potential to accurately detect and track “window shopping” habits. Computer vision models can inform retailers about exactly which items get the most shoppers’ attention, and with dwell time analysis, tell staff when and where merchandise displays were most effective in provoking an actual purchase.
In that same vein, computer vision models can be trained to verify planogram compliance, identify shelf gaps, as well as misplaced, mislabeled, or damaged products across store locations. Computer vision-powered space monitoring and tracking models provide powerful insights into shopper volume and flow, purchasing trends, product demand, and dwell times across store locations and help to promote sales and service excellence.
When it comes to bridging the omnichannel divide, computer vision can be an incredibly effective tool for facilitating online order fulfillment while aiding in the delivery of a satisfying shopping experience. For instance, computer vision-driven product lookup and matching for online research and recommendations can connect the digital and physical shopping experience to help retailers capture interest (and purchases) in the moment. By coordinating online shops with brick-and-mortar inventory levels and warehouse tracking, for instance, computer vision can increase the accuracy and efficiency of online orders to better satisfy at-home shoppers and diversify services.
Plainsight’s solutions for retailers and shoppers offer new ways to connect, engage and inform with real-time visual guidance, product verification, and real-time support for selection, correction, and validation. With models created to obtain, analyze, and share visual data insights, retailers improve store flow, merchandising, decision making, trends tracking, and predictive planning.
