Predicting the Perceived Worth of Software Product Requirements with Customer Satisfaction

Due to the limitation of resources and the need to manage scare resources, requirements engineers, project and product managers etc. are interested in clues that will enable them efficiently manage the production of software products. An understanding of the worth of software product requirements and features will help in the prioritization of requirements. It will also assist in the preparation and planning for proposed products including their future marketability and receptivity in the market. Customer satisfaction is a driver that propels customer loyalty and increases the odds of an improved customer perception of the quality of a software product. This lifeline is important as it drives the sustainability of the software product market. It promotes a good return on investment and the profitability of a software product. Furthermore, customers appreciate products whose features delight and satisfy them and they place value on such features. This ultimately enhances the perceived worth of the entire product. Capturing the perceived worth of requirements or features for a proposed product from would-be customers who feels satisfied when such requirements are met or such features are included in the design of the product, is helpful in ascertaining how important and of value the intended requirements or features are. In this study, a model is proposed that predicts the perceived requirements worth using the customer satisfaction index of the Kano model. The customer satisfaction is based on how satisfied customers are if the requirements or features of the would-be product are met or fulfilled and how important these satisfying requirements or features are to them. A simple regression analysis was computed and the result reveals that customer satisfaction significantly and positively impacts on the perceived requirement worth, if all things remain equal. Customer satisfaction (based on fulfilled software product requirements) significantly predicts the perceived worth of software product requirements. This model can be useful in prioritizing requirements, planning for future products, and in the marketability of such products etc.