Even pre-pandemic, retailers were keenly aware of intensifying pressures on their businesses.
These included once-loyal customers growing restless, increased price transparency amidst heightened competition, and the accelerating pace of changes in shopper, market and competitor behaviors – all of which pointed to the need for agile, focused pricing and promotions.
Fast forward a year into the pandemic, and the landscape has grown even more precarious for chain retailers. With lockdowns, long lines and fear of contagion top of mind, shoppers fled stores for online channels in unprecedented numbers. And now that the genie is out of the bottle, it’s not going back in.
A recent global shopper study found that while 77% of shoppers always or often shopped in-store pre-COVID, that has fallen sharply to 43% during the pandemic, and only 54% of shoppers say they will return to always or often shopping in-store after the pandemic.
The shift to online gives shoppers instant access to alternative offerings from competitors, and shoppers are more receptive than ever: a recent Forrester study found that 53% of U.S. online adults are willing to try out emerging brands and products. This also carries opportunities for retailers – shoppers report that they are now more likely to buy a retailer’s private label offerings over national brands, with the Forrester study revealing that 43% buy private-label now vs. 37% pre-COVID-19.
Retailers need to create thoughtful strategies and pricing for their private-label items, which can generate greater market share and more attractive margins.
Today’s shoppers are both incredibly agile and demanding; they want their products right here, right now and at the right price. In order to survive, retailers must be equally agile, offering the items, prices and promotions that shoppers expect. This means leveraging science-based technology and automating formerly manual processes to keep pace with shoppers.
Modern price and promotion optimization technology makes highly accurate predictions based on evaluating billions of possibilities for prices and promotions, factoring in real-time shopper demand signals, cross-item cannibalization and halo effects, and competitive elasticity. The models’ predictions in turn drive prioritized price and promotion recommendations down to the store-item level, enabling retailers to offer relevant, engaging prices and offers where they matter most.
These proven capabilities have grown even more robust as they gained real-world experience and the machine-learning science remains tuned to changing retail realities.
The ability to understand your shoppers and meet them where they are at this moment is now a must-have, with the pandemic rapidly accelerating shopper behavior shifts. Today 60% of retailers say they are focused on putting AI-powered pricing in place, and 70% are willing to take humans out of key processes and rely on AI-powered automation and dynamic pricing.
Capitalize on change
Pandemic-era behaviors have even shaken traditionally stable areas of retail, such as those items where shoppers pay most attention to pricing, or the Key Value Items (KVIs). These KVIs disproportionately drive your price image, so it’s critical to know your current KVIs at any given moment.
Traditionally, many retailers were content to revisit KVIs only once or twice a year, in a time-consuming, resource-heavy analytics deep-dive. But KVIs are now shifting rapidly; therefore, retailers must offer competitive prices for KVIs to keep shoppers from defecting to competitors. Fortunately, science-driven real-time monitoring of shopper demand signals and price sensitivity prioritizes price recommendations for KVIs, building those price adjustments into the overall automated flow of price optimization.
Understanding cross-item affinity and cannibalization effects is powerful in both price and promotion science. Knowing what promotions resonate with your customers, including the right vehicle and the right offer, enables retailers to attract shoppers to their destination with targeted, relevant offers.
Carefully targeting prices and promotions to drive halo items that increase overall basket and avoid inadvertently undercutting more margin-rich items with cannibalization, is a fundamental for AI-based price science.
Once again, pricing aggressively on the promoted item is sustainable in the overall context of knowing how to recover margin elsewhere, including affinity items, to meet target business goals. It’s imperative to get this right. Since shoppers are not going to buy at regular price and will instead wait for the right promotional discount, you need to ensure that you deliver the right offer to them before your competitors.
And while historically, shoppers have had a strong preference for dollars-off or percent-off promotions, their current top preference is for Buy-One-Get-One (BOGO): 54% of shoppers prefer BOGO to dollars-off (52%) or percent-off (48%). Retailers can tap promotion optimization software to stay current with shoppers' changing promotional preferences in order to ensure they offer the most relevant promotions and types at the right price, and that will also meet their business goals.
Cheryl Sullivan is president and GM of DemandTec.