We’ve put together a guide to help you better understand how different types of survey logic work and how to best apply them to your next project.
What is Survey Logic and How Does it Work?
When you design a survey, you might find that not all of the questions you’ve developed would apply to your entire respondent pool. Survey logic allows you to create a path through your survey for respondents based on their answers to your questions. This allows for a streamlined user experience, ensuring that every respondent is only presented with the question or answer options that apply to them.
Types of Logic
There are many different types of survey logic you can apply to your project’s design. Some of the most popular include:
Conditional Display: Conditional display logic works by hiding or displaying specific questions or answer options based on a respondent's previous answers. This allows you to better personalize the survey for your respondents by only showing the question and answer options that apply to them. For example, if you asked your respondents whether they prefer coffee or tea, you might want to only display coffee-related follow-up questions to the group that selects coffee and tea-related questions to those that selected tea.
Multi-Question Logic:Similar to conditional display, multi-question logic allows you to route respondents to specific questions based on their responses to multiple questions. For example, if you only wanted respondents who made over $150k a year AND were the primary grocery shopper in their household, you could screen out anyone who did not provide those two answers.
Question Skip Logic: Skip logic allows you to route respondents around specific questions that do not apply to them. For example, if a respondent says they have never used one of the products you’ve asked about, you would want them to skip the following question about their satisfaction with that product.
Page Skip Logic: Just like the skip logic above, page skip allows you to route respondents around entire pages that do not apply to them. For example, if a respondent says they have never used one of the products in your survey, you would want them to skip the following page with follow-up questions about their experience with said product.
Question Looping Logic: Much like the name would imply, looping logic is used to ask respondents the same question, or set of questions, multiple times based on their previous responses. For example, if you had respondents choose the specific products they had recently bought, you may then want to “loop” them through a set of questions asking them for more information on each.
Question and Answer Piping Logic:Piping logic is used to “pipe”, or insert, a respondent's answer choice into a question later in the survey. For example, if your respondent had chosen “Nike”, “Adidas”, and “New Balance” as shoe brands they recently purchased, you would want to “pipe” those answer choices into the follow-up questions regarding their purchase experience with the shoes.
Disqualification Logic: Disqualification logic uses screening questions to disqualify respondents that do not meet the requirements of your quota. These respondents would not be counted towards your quota, and their answers would not be included in the data analysis. For example, if you only wanted feedback from respondents between the ages of 25-35 that lived in urban settings, you would use screening questions at the beginning of your survey to weed out those respondents who did not meet your qualifications. Those that do, count towards the overall response limit that you set
Numeric Logic: Numeric logic is the ability to set logic based on numeric questions in relation to each other. For example, if a respondent gives an answer in Question 2 that is greater than their answer to Question 3, you could skip them to another area of your project.
End of Survey Logic: As the name would suggest, end of survey logic allows you to route a respondent to the end of a survey. However, this is different from disqualification logic, as the respondent's answers will be included and they will be counted towards your total.
(BONUS)Quotas: Only because we mentioned them above, survey quotes represent the number of respondents needed to meet your specific requirements- like the number of women or people in a specific age group. For example, if you want a sample representative of the general population of the United States, you would need your respondent gender breakdown to be: 49% females, 49% male, and 2% non-binary. To accomplish this, you would use the quotas system and specify those percentages.
(BONUS) Nested Quotas: Nested Quotas add another layer of complexity to your quotas by including a specific breakdown of percentiles not just across one variable ( like sex), but by nesting multiple variables like age groups, income, etc.
Designing More Effective Surveys with SightX
The SightX platform is the next generation of consumer insights tools: a single, unified solution for engagement, understanding, advanced analysis, and reporting. While it's powerful enough for insights teams at leading companies, it's user-friendly interface makes it simple for anyone to start, optimize, and scale their research.
Utilize SightX's survey building tools to engage your audience at any point in the consumer journey and get answers on your pressing product, messaging, brand, or market questions. Design surveys as simple or complex as your use case requires, with all of the flexibility you could ever need. Build projects, distribute your surveys, and analyze the results all in a single, simple-to-use platform.