Analyze Satisfaction Survey Questions with Scoring

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Use the Scoring ability in Snap Survey Software to analyze satisfaction survey questions

If you have a satisfaction survey question in your online survey, or other question where survey respondents are asked to rate a subject using an scale, you can convert respondent data into useful mean values by analyzing the responses using a score. You can then view data as a summary of the satisfaction value of all the data.

Scores are a way of manipulating survey data for analysis. Scores allow you to assign a value to each code, including a no response value (respondent did not answer the question). In advanced online survey software, you can assign a score to each survey question code, and then calculate analyses using the score instead of the code. This method is generally used for scoring satisfaction surveys, so that positive ratings are given positive values and negative ratings are given negative values. You can then summarize the whole satisfaction by calculating the mean of all survey cases, so you know whether survey respondents are generally satisfied or not, by how high or low the mean score is.

Keep in mind, if survey respondents have marked a question as “Don’t know” or “No opinion,” this has different effects on mean values, according to whether it has a value assigned to it or not (even if that value is 0). For example, if you have four respondents to a survey, who have given the following satisfaction values (from a range of -2 to +2).

Person 1: -1

Person 2: +1

Person 3: +2

Person 4: +2

Person 5: Don’t know

To calculate the mean score, you sum the values and divide by the number of survey cases. If you are scoring “Don’t know” as 0, your mean would be (-1 + 1 + 2 + 2 + 0) / 5 or 4/5. If you discard the Don’t Know, your mean would be (-1 + 1 + 2 + 2 )/4 or 4/4. It’s obviously quite important to decide what you do with your “Don’t know” values in terms of judging the satisfaction of your respondents. By using a score you can choose to score them as a neutral value, or discard them from the calculation.

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