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Conditional logic, also known as “conditional branching” or “skip logic”, is a feature of survey design that changes what question or page a respondent sees next based on how they answer the current question. Using conditional logic, you can create a custom path for each respondent, depending on their response to a specific question. This is a powerful tool for researchers, empowering them to create custom rules and get the right responses without confusing respondents or wasting their time.
How does it work?
To properly explain conditional logic, let’s use an example:
A brand can ask a group of consumers whether they have purchased one of their products before. If the answer is yes, the survey will jump to a question like “Please rate the quality of this product”. If the answer is no, the survey will jump to a question such as “Why haven’t you purchased X product?” with response options like “Haven’t needed it”, “Didn’t know it existed”, “Was too expensive” and “Other”. After these questions, the survey flow could reconnect, so all respondents will get the same questions or the survey paths will remain separate.
On the Bounce dashboard, the implementation of conditional logic is aided by a clever ‘Map View’ where you can segment respondents, add conditional logic, and design surveys without complication. You can learn more about the scripting features on the Bounce dashboard here. Conditional logic can be used for any research project, whether you’re gathering research for a new advertising campaign, assessing customer satisfaction, or developing a new product.
Advantages of Conditional Logic
- Better survey flow: Survey flow is an important consideration in survey design. Having a consistent structure makes answering questions a lot easier on respondents, as questions follow some theme or logic that respondents can follow easily. Additionally, respondents expect surveys to be interactive and conditional logic is one of the best tools for creating that interaction.
- Shorter survey time: With conditional logic, respondents automatically skip any questions that aren’t relevant. As a respondent only sees the questions that are relevant to them, they don’t waste their time on needless or confusing questions. A researcher should always strive to make their surveys shorter, as respondents don’t like long surveys.
- Higher response rates: A key metric that researchers should keep in mind is the response rate, that is how many respondents actually complete the survey and don’t drop out. When surveys contain questions that don’t apply to them, respondents are more likely to get irritated and leave the survey.
- Higher quality: With higher response rates as well as responses that are more applicable to the survey questions, researchers can expect higher quality research. Often when respondents see questions that don’t apply to them, their response will be a random pick, thus skewing the data. Conditional logic avoids that.
Bottom line, adding conditional logic makes surveys quicker and smoother for your respondents. Conditional logic is a valuable tool in improving survey design and respondent experience, though you should make sense it is well thought out and tested. Better respondent experience produces better research, which should be the goal for every researcher.