A data analyst is helping the product team create a survey to measure customer satisfaction with a new feature in their mobile application. The primary goal is to collect quantitative data that can be used to calculate an average satisfaction score and monitor trends over time. Which of the following question types would be the MOST appropriate to include in the survey to meet this specific requirement?
A multiple-choice question, such as 'Which of the following best describes your experience with the new feature?' with options like 'Easy to use', 'Buggy', and 'Helpful'.
An open-ended question, such as 'What are your thoughts on the new feature?'.
A dichotomous question, such as 'Did you find the new feature useful?' with 'Yes' or 'No' answers.
A 5-point Likert scale question, such as 'How satisfied are you with the new feature?' with options from 'Very Dissatisfied' to 'Very Satisfied'.
The correct answer is the 5-point Likert scale question. This type of question asks respondents to rate their level of agreement or satisfaction on a scale, which generates ordinal data. This data is commonly treated as interval data in business analytics, allowing for the calculation of an average (mean) score. This directly meets the project's goal of calculating an average satisfaction score to track over time.
The multiple-choice option provides nominal (categorical) data. It is not possible to calculate a meaningful average from non-ordered categories like 'Easy to use' or 'Buggy'. An open-ended question generates qualitative (text) data, which is valuable for deep insights but cannot be used to calculate a numerical average without significant extra processing like sentiment analysis or manual coding. A dichotomous question provides binary ('Yes'/'No') data. While you can calculate the percentage of 'Yes' responses, it does not provide a granular score that can be averaged to show varying levels of satisfaction.
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