Customer surveys are efficient tools for measuring customer satisfaction. A great attention has been given to techniques for analyzing customer feedback in recent years since customer satisfaction plays a major role in an organizations success. Indeed, customer feedback analysis is a challenging task and few guidelines have been provided on the dynamic validation of the instrument used. In addition, many experts and researchers have different opinions on the definitions of quality and customer satisfaction, and there is an agreement that only the customer has the right to judge the quality of products used or services provided. A typical survey consists of quantitative and qualitative questions. Respondents to quantitative questions are limited to answer questions without further explanations whereas qualitative questions allow respondents to add any comments and reflect customers' perceptions and expectation toward product used and service provided. The customer's responses to open-ended questions are complex to analyze due to difficult measurements of responses, meaning and variations in respondents concepts. A singular qualitative data analysis is widely used in several researches. Moreover, there is a lack of explanation of different methods of qualitative data analysis and how to use them with computer software. Three techniques to analyze customer feedbacks were used, including Critical Incident (CI), Concept Mapping (CM), and Cluster Analysis (CA). Additionally, advanced statistical and qualitative data analysis software was utilized to analyze data obtained from customers. This study is aimed at the development of a dynamic validation technique that can be used to update survey items based on customer response to open ended questions. An illustration of the proposed customer feedbacks technique is provided through a case study involving applications of several qualitative and quantitative data analysis techniques. The results supported the need for dynamic validation and indicated its ability to identify new requirements and emerging patterns of customers' expectations.