Core Insights - The article emphasizes the importance of understanding the algorithms used in satisfaction surveys, as different methods can yield vastly different results [1] Summary by Categories Satisfaction Measurement Algorithms - **Simple Average Method**: This traditional method sums all scores and divides by the number of responses, which can be misleading due to equal weight given to extreme values, potentially distorting the overall picture [1] - **Satisfaction Rate Method**: This method calculates the percentage of respondents who rate their satisfaction as 8 or above, which may overlook "neutral" customers who are neither satisfied nor dissatisfied, leading to overly optimistic results [3] - **Weighted Average Method**: This approach considers the importance of different metrics, allowing for a more accurate representation of satisfaction if weights are scientifically validated; however, subjective weighting can obscure real issues [4] - **Satisfaction Index Method**: This is the most scientific approach, using statistical analysis to determine the impact of various dimensions on overall satisfaction, thus revealing key drivers of satisfaction [5] - **NPS (Net Promoter Score) Method**: This method focuses on future loyalty by measuring the likelihood of customers recommending the service, with a higher NPS indicating greater customer loyalty and correlation with renewal rates and word-of-mouth [7]