Abstarct: Understanding the reasons why customers are dissatisfied will help the firm improve its products and its marketing. As organizations strive to improve business performance, it becomes ever more essential for them to manage their relationships with customers. The Net Promoter Score (NPS) is word-of-mouth customer loyalty metric. This approach groups customers into three clusters — Promoters, Passives, and Detractors. It also provides a simple, intuitive scheme that accurately predicts customer behavior. Despite these features, however, it presents a discrete-point descxription of customers’ views. To fill in this gap, this article presents a fuzzy model of measuring customers’ degree of satisfaction by proposing fuzzy net promoter score (FNPS). For a better analysis of FNPS, I proposed two new factors: Retention and attraction factors. In this thesis we discussed NPS and also new FNPS calculation of HA category in IRAN to measure the customers’ degree of loyalty to a specific brand (Samsung and LG). Customers were interviewed about products that they had recently purchased or were currently consuming. The results provide an interesting perspective on the current experiences of Iranian consumers. At first, we computed the NPS of these two brands . The result shows Samsung has the higher likelihood for recommending than LG. In the second phase we calculated FNPS of two aforementioned brands to made it closer to the market facts and also remove some of NPS defects like its rigid spectrum. Here we use fuzzy function and find that again Samsung FNPS is higher that LG and both of these scores is more than their calculated NPS.