Alternative Statistical and Psychological Methods for Interpreting Large-scale Seat Comfort Surveys

Commercially available large-scale consumer surveys such as JD Power and Associates (JDPA) APPEAL Survey are often used to assess the success or failure of seat comfort design. Because access to the raw data from these surveys is limited, mean values are often the sole basis for analysis and comparison. Mean values alone, however, incompletely describe customer ratings that often lead to incorrect interpretation of the data. This can result in organizations expending capital to fix problems that do not exist. Since most companies have limited access to the raw data, this paper examines statistical and psychological factors that affect consumer survey results and describes methods for using these relationships to better interpret results of large scale, industry surveys.