Computation Variable

In survey design, making real-time decisions and classifications can enhance the quality of data collected and streamline the respondent’s journey. Q-Fi offers a powerful tool for this purpose: Computation Variables. This variable type operates behind the scenes to manage essential calculations, classifications, and logic paths.

What Are Computation Variables?

Computation variables are hidden variables that perform real-time calculations or classifications based on respondents’ answers. While they are invisible to survey participants, their outputs can play a vital role in survey logic, quotas, and respondent categorization.

How Computation Variables Are Used

1. Classifications: They can categorize respondents into different groups based on their answers to previous questions, allowing for dynamic segmentation in real-time.

2. Calculations: Computation variables are designed to perform complex calculations, such as summing up scores from different questions, calculating averages, or computing derived metrics that can help guide the next steps in the survey.

3. Skip Logic: The output from a computation variable can dictate which questions or sections a respondent should be shown next. This makes the survey experience more personalized and relevant by skipping unnecessary questions.

4. Quota Checks: For surveys that need to meet specific quotas, computation variables can help track the classification of respondents to ensure quotas are met in real time.

5. Real-Time Insights for Data Analysis: With computation variables, respondent classifications and calculations can be saved and analyzed during or after the survey. This streamlines the data analysis process, as the required calculations have already been processed.

Example Use Cases

1. Scoring for Surveys: You can use a computation variable to calculate a score based on multiple responses, which can then be used to classify the respondent into a category or determine which questions they should be asked next.

2. Demographic Grouping: If you’re collecting age and location data, a computation variable can group respondents into demographic categories (e.g., “Millennial from Ontario”) for further analysis or quota management.

3. Real-Time Classification: If your survey is designed to classify respondents based on their behavior or preferences, a computation variable can help identify and track these classifications in real time, making it easier to analyze data by segments.

Why Use Computation Variables?

By using computation variables, you can create smarter, more flexible surveys that adapt to respondents’ answers in real-time. They provide a way to streamline survey logic, ensure quota fulfillment, and ultimately produce more actionable data.

Computation variables are essential for surveys that require complex logic, calculations, and respondent segmentation, helping ensure that the survey experience remains relevant, while also giving researchers valuable insights for analysis.