Consumer Decision Trees provide a deeper understanding of your shopper’s behavior and motivations. While traditional decision tree methods are primarily product-focused and based on historical data, Decision Insight’s proprietary approach is forward-looking and shopper-focused.
Decision Insight’s unique CDT methodology brings the context of the store into the exercise, measures substitutability, and allows for the inclusion of next generation innovations. Shoppers develop their own definition of brand/product relationships, thus allowing DI to delve directly into the core of their decision making process. DI’s CDT results indicate what factors most influence shopper choices; how shoppers define the overall category; and what trade-offs shoppers will make when shopping the category.
DI Consumer Decision Trees provide:
- Specific learnings on how to structure or restructure a category
- A blueprint for store planograms and aisle adjacencies
- Meaningful insights into merchandising
- Identification of potential assortment gaps and whitespace opportunities
A Consumer Decision Tree from Decision Insight will provide the foundational knowledge necessary to develop educated hypotheses for a shopper-preferred aisle profile. Potential solutions are then tested in a proprietary virtual shopping study to better understand optimal strategies for maximizing sales for your brand – and the retailer.