Assortment Planning/Optimization

Why Transferable Demand is Essential for Grocery Assortment Planning

Gina Hargrave, Head of Category Planning, Symphony RetailAI

Given the whirlwind of change grocery retail has experienced in 2020, CPGs and grocers are scrambling to gain insights as to how to best cater to shopper preferences in store. Pandemic pressures caused consumers to switch products, increase basket sizes, limit their number of in-store trips and become more price sensitive. As a result, shoppers’ habits emerged as even more of a moving target.

However, CPGs and retailer partners need to be able to enhance space and assortment optimization capabilities in order to respond quickly to changing purchase habits. Traditional practices of using Excel spreadsheets to review sales data and metrics will not help accurately address shopper needs now, or post-COVID-19. Instead, retailers and CPGs alike are using artificial intelligence solutions to identify shopper behavior and help calculate transferable demand faster and more accurately.

Why is transferable demand important to CPGs and retailers?

When retailers review their assortments and look to cut SKUs, understanding the impact of transferable demand is essential to ensure category turnover is maintained and customers are satisfied. This also determines whether or not retailers will keep a manufacturer’s products on their shelves.  

Essentially, transferable demand answers a retailer’s question of, If I remove a specific item, will the demand of that SKU be transferred to other items still on the shelf? However, there’s an endless number of combinations and factors that cannot be considered manually. Artificial intelligence can analyze customer data to understand the products they prefer and ensure those remain on the shelf. Factors for consideration include loyalty toward an item, exclusivity, substitutability and the item’s overall value. If the products shoppers feel strongly about are not on the shelf, they might buy a comparable product from a competitor or leave the store altogether.

Rationalizing SKUs by understanding shopper preferences

When it comes to making the decision about removing or adding items, artificial intelligence can analyze customer data to provide insights into product loyalty. What percent of customers are able to purchase their preferred item? How many shoppers end up substituting items, and which products are they? Not to mention retailers must assure any new items fit within the existing assortment, and don’t jeopardize other products’ stock position. Retailers need to be able to balance fulfilling loyal customers’ needs, but also understand the competitive landscape and add products that attract new customers.

Historically, retailers and CPG manufacturers took a simple approach to determining assortment: the top sellers – and top bidders – received the most shelf space. In the same vein, the process of delisting and adding items was ranked purely by sales data. But these processes don’t dive into understanding which items shoppers prefer, whether a retailer has the products available to fulfill demand and if a shopper is willing to compromise on a specific product. For example, shoppers may be extremely loyal to the type of bread they buy, but are comfortable switching to a different brand of ketchup.

Transferable demand can help retailers understand how to maintain sales and which products to safely eliminate from shelves. And CPGs can prove themselves a useful partner by providing them with critical data insights

Intelligent clustering removes errors behind a “one-size-fits-all” approach

Just as CPGs treat each retailer partner relationship uniquely, based on individual needs, retailers do the same for their stores when looking to streamline assortment. But retailers can’t rely solely on store geography and demographics to make assortment decisions. Only when assortment is analyzed based on demand – at both a category and store level – can retailers find out where it’s appropriate to make compromises. With intelligent clustering, stores that only have small differences in assortment can be grouped together, making stores easier to fulfill. 

Optimizing assortments improves retailer-CPG collaboration  

During the process of analyzing transferable demand, retailers must ensure they serve every type of customer through their assortment offering, while also maintaining or improving sales. What’s more, retailers and manufacturers benefit from collaborating effectively to establish assortments that drive mutual category benefits to customers and each other. Artificial intelligence allows for transferable demand to be calculated faster and with more accuracy. When optimal assortment is achieved on an individual store level, other areas of the business are positively impacted, as well, and both retailers and CPGs can better meet the needs of shoppers.


    Gina Hargrave is a sales and consulting professional with 20 years of experience in FMCG retail, with a focus on category and space management business process and solutions. She serves as Head of Category Planning for Symphony RetailAI.