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Surveys and Skip Logic

What you will learn:

In this article, we are here to give advice on when to create multiple surveys and when to use skip logic. Knowing the difference can ensure improved relevance, alignment to indicators, efficiency of data collection, decrease survey abandonment and avoid survey fatigue. It can also improve data quality and disqualify unrelated respondents.

Let’s start with the basics, what is skip logic?

What is Skip Logic?

Skip Logic, also called branching or logical flow, is when a condition is built into a chosen answer of a particular question that allows the survey flow to skip one or more questions. This directs respondents to the next logical question based on their previous answer and skips non-relevant questions.

Compared to regular survey flow, where questions are presented one after the other and are the same for all respondents, skip logic allows you to tailor which questions are visible based on certain answers selected.

Example 1: You ask respondents how satisfied they were with a training and you want to have more details from those who respond with “not satisfied”. You can use skip logic to add a follow-up question that is hidden from respondents who answered with “very satisfied” or “somewhat satisfied”.

Skip Logic can also be used to end a survey if a respondent chooses a particular response. Perhaps they do not fit the type of respondent you are looking for or they do not consent to continue the survey.

Example 2: You want to end the survey for respondents who do not consent to continue.

With skip logic you can branch your survey with multiple pathways depending on a respondents chosen answers. The possibilities are endless so you may wonder when it is best to use skip logic vs creating a whole new survey.

Tip: Avoid Overuse – When using skip logic, consider if you are using too many skips and making the survey overly complex and confusing for those administering it or responding.

Skip Logic vs. New Survey

Because of the endless possibilities, it may be hard to determine when you should utilize skip logic and when you should create a new survey.

Consider the following aspects of your survey:

  • Respondent Population/Audience Segmentation – Are the respondent target groups similar in nature or do they have vastly different characteristics?
  • Sampling Methodology – How are you determining the respondent target population? What is the scale of your sampling?
  • Frequency of Survey – Are you interested in gathering information on all question with the same timing/frequency?
  • Topics – Are you covering multiple distinct topics?
  • Analysis – What are the results you are analyzing? If this was broken into multiple surveys, would the results need to be integrated together again?

 

How these aspects interact and overlap will help you determine if it is best to create one survey or multiple surveys.

Examples:

  • If there is are 2 different respondent populations which each have a different survey topic and frequency of survey, you should use multiple surveys (perhaps each will have its own skip logic).
  • If you have multiple respondent populations but are asking them questions about the same topic and using the same frequency, you likely only need 1 survey.

Best Practices

  • The analysis of an individual indicator should come from one survey rather than multiple surveys.   
  • Be mindful that creating multiple surveys adds additional administrative burden and can create survey fatigue if multiple surveys are administered to the same respondents.
  • Whenever you are creating a survey, you should conduct tests to identify issues and this is particularly true when using skip logic! Ensure that you test all possible branches and response answers on questions that utilize skip logic to ensure the survey is working smoothly and as intended.

 

Ultimately, the decision to use skip logic or separate surveys depends on the specific needs of your monitoring and evaluation project and the characteristics of your target audience.

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