Assortment optimization and the new rules of retail growth

Assortment optimization has been fundamental to retail success since retail began. Even the earliest merchants understood this millennia ago when they sought to offer the optimal mix of products with the highest probability of producing profitable sales growth.

The goal is the same today, but advances in technology and adoption of AI have transformed how retailers leverage increasing volumes of data to make precise assortment optimization decisions that increase the productivity of selling space. This ability means retailers can think differently about growth opportunities, store sizes, results-oriented remodeling activities, and the allocation of space in stores. When it is possible to optimize assortments and improve productivity, a wide range of other growth-related decisions are affected.

For example, it is why some retailers can profitably operate stores of a size that might not seem adequate to generate the volume needed to cover occupancy costs and produce a profit. Meanwhile, other retailers can remodel stores and reduce overall shelf space to make room for alternative uses or service offerings because the productivity of the remaining shelf space has been increased.

Assortment optimization isn’t easy

We’ve already noted that assortment optimization is not a new concept in retail. What is new is how retailers achieving it are successfully using AI-powered technology to cope with the increased complexity that comes with scale, data volumes, and the realities of a dynamic competitive environment. Retailers must balance factors such as data complexity, rapidly shifting shopper preferences, space limitations, supply chain considerations and supplier relationships, and competitive realities. 

Doing so requires leveraging the most advanced AI-powered technologies that can streamline all the insights and processes required to deliver localized, customer-centric, and space-aware assortments. The use of AI-powered solutions also helps retailers understand new item incrementality, transferable demand, and store clustering opportunities to make optimal merchandising decisions.

Intuition, manual processes, and spreadsheets are no match for the complexity of the modern retail environment and the financial imperative to improve selling space productivity.

The new age of format flexibility

There are many levers retailers can pull to drive growth as was evident in recent years. Retailers pushed through price increases from suppliers and drove impressive topline growth even though unit volumes were flat or declined. More recently, data monetization has become a hot topic along with retail media networks that help retailers generate alternative revenue streams.

Ultimately, retail success is determined by who achieves the greatest sales volumes at a rate of profit that allows for reinvestment in the business. Traditionally, retailers often relied on a blend of new store expansion and remodeling activity to increase the amount and productivity of selling space. Prior to AI-powered assortment optimization, it was also common to see retailers stick with a standard prototype or a few variations, potentially passing on real estate with promising potential due to special circumstances in a unique market.

However, store expansion for many retailers has slowed, particularly as online buying continues to increase, and the emphasis has shifted to remodeling efforts. This fact highlights the need to optimize assortments and increase sales from what may be a reduced amount of space. When retailers do open stores, assortment optimization makes it possible to pursue opportunistic expansion opportunities in unconventional spaces previously thought to be unsuitable because financial assumptions were based on limited understanding of how optimizing assortments can produce needed financial results to make the math work on a lease. Likewise, a retailer may be able to extend the life of an underperforming store through assortment optimization.

From Montana to Manhattan

Recent actions of Whole Foods Market highlight how assortment optimization and space planning enable retailers to pursue format flexible growth opportunities. During the first quarter of 2023, Whole Foods Market opened a 32,000-square-foot store in Bozeman, Montana, a city with fewer than 60,000 residents in a state that is one of the least populated in the US. Conversely, Whole Foods also opened a 42,000-square-foot, multi-level store in a luxury high-rise in the financial district of lower Manhattan, a neighborhood with 60,000 residents in one of America’s most densely populated cities.

It would be hard to find two locations where the trading area, shopper preferences, and patterns are more different. Whole Foods is a destination in Bozeman that attracts shoppers from throughout the city, virtually all of whom drive to the store. The new location in Manhattan, the 14th Whole Foods in the city, serves shoppers who are more likely to arrive on foot or ride an elevator down from one of the building’s 566 residences.

The Whole Foods Market example is extreme, but it highlights a situation retailers face daily – providing shoppers with the ideal assortment that has the highest probability of achieving profitable sales growth. The odds of achieving that goal improve dramatically by relying on AI-powered solutions to create optimal assortments.