Analysing the customer responses to the products can yield insight into the importance of the design factors and the relationships between emotional response and design factors. These relationships are the key to the importance of KE to the design process both in guiding design and in providing a broad portfolio of products. The design factors are derived from various sources; including designers and merchandising staff. Data mining and customer segmentation based on recency; frequency and value of purchases can also indicate which design factors are important. KE is expensive to do properly; so it is particularly important to prepare the groundwork carefully. This paper investigates what information can be obtained from data mining sales data as a pre-cursor to Kansei Engineering.
Keywords: Kansei Engineering; data-mining; analysis of means