Retailers Turn to AI-Driven Data Exchanges to Solve Merchandising Inefficiencies
At big-box stores across the country, prices are changing fast.
While inflation pushs costs up, lagging customer demand has retailers instituting deep discounts and other promotions meant to keep prices low. Supply is now exceeding demand, particularly in the apparel sector, where some retailers are overstocked by as much as 30%.
The struggle is leading a push within the retail industry to rely more heavily on machine-driven tools, including AI-driven data exchanges, to coordinate merchandising needs in-store, online, and throughout the supply chain.
With inventory changes readily available, decisions regarding promotions can be made in a split second, and displays can be adjusted quickly to account for fluctuations in prices and consumer demand.
“AI-driven dynamic pricing and inventory management can help retailers master both supply and demand,” says Michael Jaszczyk, CEO, GK Americas. “This is increasingly important as supply chain disruptions have impacted available inventory and inflation has threatened customer demand.”
Understanding price sensitivity and consumer demand for specific products can help retailers more effectively manage promotions. However, as is so often the case, the devil is in the details.
To ensure the latest inventory data is accessible in real-time, and then coordinate merchandising needs with associates in-store, Jaszczyk says retailers need access to AI-driven data exchanges and inventory management tools. Only with those tools in place can retailers begin to automate the ideal price adjustments to optimize inventory based on defined pricing rules that reflect changes in the market and relevant internal factors.
“I’ve seen some really innovative approaches in the grocery space, where retailers are using dynamic pricing on perishable items to reduce food waste. Even better, when these products are sold at competitive prices, customers are enticed to shop with the retailer,” Jaszczyk says. “For example, dynamic pricing can optimize prices according to internal and external demand factors, as well as the target ‘best-before’ date … AI can predict when avocados will begin to turn dark green and establish the optimal price day by day, as expiration dates draw nearer.”
What makes dynamic pricing interesting in the grocery store context is the elasticity of the items, Jaszczyk says. Robust inventory data and AI-driven dynamic pricing can detect cross-sell opportunities with perishable items and items with longer shelf lives. For example, a low price on fresh garlic bread might incite consumers to purchase pasta, spaghetti sauce, or a frozen lasagna. Instead of manual calculation, dynamic pricing leads to increased accuracy and predictability around price and inventory, which reduces overstock and food waste.
Dynamic pricing can analyze external market factors, as well, taking into account complexities like material costs, competition, price sensitivities — and even the weather. That’s more important than ever as 2023 draws closer, with inflation top of mind for many consumers.
Grocery isn’t the only industry that’s benefitting from the technology. Apparel retailers are seeing prices rising across the value chain, from commodities to transport and labor. As a result, Jaszczyk says retailers must effectively manage these cost increases and make strategic pricing decisions quickly.
“Market conditions can shift day by day,” he says. “By establishing ideal prices in real time, retailers can retain loyal customers without risking the bottom line or selling through inventory too quickly.”