Today’s merchandise management teams simply cannot keep up with the demands of modern retail. Too many stores (both digital and physical), store plans and products — each with unique characteristics — leave no room to make quick adjustments as shoppers’ tastes continue to rapidly change. With a plethora of information, opportunities and competitors in the market, retailers need to be able to predict the unpredictable and respond far quicker in order to better meet consumer demand.
How AI Can Help
Using artificial intelligence (AI) for merchandising can improve management of stores on an individual level, simultaneously and holistically. However, in a recent study we conducted, just 16 percent of retailers have deployed AI to support merchandise management, with many of these adopters being retail giants such as Amazon.com and Walmart.
AI is capable of analyzing data in order to drive assortment plans that are customer specific for stores with the right space, price and promotion plans for each individual location. This allows companies to make smarter decisions and compete in a complex and difficult retail environment. As retailers begin using AI engines in merchandise management, the study revealed that a majority say the two top strategic goals they look to achieve are improving sell-through of inventory and improving margins.
When it comes to new fads, or events such as religious holidays, to make better predictions and anticipate sales, AI analyzes past patterns with current data to make prescriptive recommendations on the best actions to take. Forecasting accuracy is the basis for all actions taken by the merchandise management team, and if forecasting is inaccurate, every subsequent decision will be as well.
Store Planning at an Individual Level
It’s impossible for a retailer to expect that a category manager can tune the specific assortments, space plans, pricing and promotions strategies for individual stores or individual products without substantial help from technology. With AI, managers can weigh the value of economies of scale against personalized assortments to identify the most profitable decisions for each store, while still catering to customer needs.
For example, a retailer might discover that there's a gym located directly across the street from one of its store locations. As a result, shoppers are looking for healthier, grab-and-go food options after a workout, as opposed to a store in a more suburban area that offers a wider assortment of meals that cater to larger families. Retailers must be able to quickly react to the slightest changes in customer behavior across each individual store in order to ensure loyalty.
The Future IS AI-Driven Merchandising
Today’s merchandise management teams simply cannot keep up with the speed of consumers by using manual methods. Retailers with no plans to implement AI technology will continue to suffer across the business as competitors improve their financial targets and make continued investments in streamlining their operations. AI enables managers, especially those at larger chains, to identify meaningful patterns in critical areas such as customer demand, price sensitivity and omnichannel complexity, both quickly and effectively. The time for investing in AI is now. While the future is unpredictable, AI-driven merchandise management can help retailers quickly analyze data to provide insights and improve their current decision-making processes to better prepare for and react to whatever changes come their way.
Kevin Sterneckert is chief marketing officer at Symphony RetailAI, a global leader in AI-enabled decision platforms, solutions and insights for driving profitable revenue growth for retailers and CPG manufacturers.
Related story: Eliminating Category Duplication Through the Power of AI
Kevin Sterneckert is chief marketing officer at Symphony RetailAI, a global leader in AI-enabled decision platforms, solutions and insights for driving profitable revenue growth for retailers and CPG manufacturers – from customer intelligence to merchandising, personalized marketing to supply chain.
He has more than 25 years of comprehensive industry experience, bringing a keen understanding of retail, manufacturing and logistics challenges. Kevin’s industry experience includes serving as chief information officer, supply chain executive, development of innovative technology solutions, inventor, and store operations development for both physical and digital retail.