Updating Consumer Decision Trees
By Randy Hofbauer
Developing and implementing the right set for a category always has been a dynamic, never-ending process with high stakes. This should come as no surprise, given the numbers: According to retail consultancy Willard Bishop, more than 50 percent of SKUs sell less than one unit per week in a traditional grocery store, with most SKUs in dry grocery, general merchandise and health and beauty care losing money, despite occupying some of the store’s least-expensive real estate. Meanwhile, 40 percent of a store’s SKUs cover 95 percent of demand, which means three-fifths (60 percent) of the SKUs in a store account for just the remaining 5 percent of demand.
The consumer decision tree (CDT), a tool that assists retailers and manufacturers in creating planograms that align with their strategies, is essential for maintaining retail relevancy, according to the March 2016 edition of Willard Bishop’s Competitive Edge, titled “Maintaining Shopper Relevancy at Retail.” It allows trading partners to understand how, why and when shoppers substitute one SKU for another, and provides insights into demand transfers taking place between each pair of SKUs, leading to better variety and product substitution decisions. By developing CDTs, trading partners can identify and rank product attributes based on each attribute’s propensity to influence a purchase decision, with the most common attributes including brand, flavor, form, health, size and price.
Additionally, the publication says, the CDT allows for better assortment decisions, helping category managers understand SKU substitutability and demand transfers, which is particularly helpful for stores creating localized sets. It also provides insights for developing shopper-friendly shelf sets, which could organize products horizontally, vertically or in block groups, depending on how shoppers make purchases within the category.
“It provides insights on how to make the way we merchandise categories more consumer-friendly, e.g., organized based on how they shop,” Paul Weitzel, managing partner with Willard Bishop and author of the piece, told Retail Leader. “It also helps determine where tradeoffs happen, which allows us to determine the right variety for each category; every category is different, and other factors, like operations, will also impact merchandising.”
However, CDTs also need to be kept fresh, especially considering how the escalating rate of in-store purchasing decisions (as high as 80 percent in some categories) and outdated CDTs cause many category sets to become misaligned with shoppers’ purchase behavior today. CDTs allow trading partners to understand how, why and when shoppers substitute one SKU for another, and provide insights into demand transfers taking place between each pair of SKUs, leading to better variety and product substitution decisions.
When updating CDTs, retailers and manufacturers must work to get access to new customer purchase behavior data, Weitzel says. Additionally, they must measure basket purchases over time by household, measure tradeoffs within categories over time, and determine switching and transfer levels.
“By connecting shopper behaviors and true profitability,” the publication reads, “retailers will make their stores more retail-relevant. This will enable them to add authentic and locally produced items that cater to the wants and needs of their targeted shopper. [It also] will build loyalty, and can even improve revenue by increasing the number of store visits.”