Other things being equal, a theory with fewer constructs is preferable over others. In exploratory factor analysis, a common method used in theory development, the most popular factor retention criterion used in marketing is the eigenvalue greater than one rule. Its use often results in over extraction, which leads to the development of less than parsimonious theories. Even the use of confirmatory factor analysis fails to detect the presence of these superfluous constructs. Although several more accurate criteria exist, they are not discussed in major marketing research texts, journals, and popular statistical software packages. In this paper, we appraise popular factor retention practices in marketing, demonstrate how they may lead to the development of inefficient theories, draw attention to a number of resources for choosing appropriate retention criteria, and develop an easy-to-use Web-based engine to effortlessly implement one such method, parallel analysis.