Obtaining the accurate final importance of each customer attribute (CA) is very important in the house of quality(HOQ), because it is deployed to the quality of the final product or service through the quality function deployment(QFD). The final importance is often calculated by the multiplication of the relative importance rate and the competitive priority rate. Traditionally, the sample mean is used for estimating two rates but the dispersion is ignored. This paper proposes a new approach that incorporates statistical significance to consider the dispersion of rates in determining the final importance of CA. The approach is illustrated with a design of car door for each case of crisp and fuzzy numbers.