The path to completing a survey isn’t always linear. Sometimes there are hidden passages, trap doors, and secret rooms that only a few respondents need to access.
When you want to make sure your respondents only see questions that are relevant to them without cutting vital questions out of your survey, you need skip logic.
Generally logic involves setting up conditions that will change how your survey behaves based on the answers that a respondent gives. Skip logic in particular will skip your respondent from one place to another based on their behavior.
There are five typical uses of skip logic, and we’ll cover each of these in turn:
- Disqualify respondents who fall outside of your desired demographics.
- Marking responses as complete even if they skip certain sections that aren’t relevant to them.
- Allowing respondents to skip an irrelevant page of the survey.
- Offering an onsite reward for completion of particular fields.
- Redirecting respondents to a secondary site and/or survey.
We’re going to take a look at how a fictional restaurant, Bot’s Bistro, could use skip logic in all five of these ways when surveying its customers about new menu options.
Best Practices for Skip Logic
Before we jump into the nuts and bolts, let’s start with some basic best practices for using logic.
Very simply, skip logic is best kept to a minimum. Its primary use is to shorten and simplify the survey taking process so that respondents only see the parts that are relevant to them and skip the rest.
If you have a larger survey that conditionally shows or hides information many times, then page or question logic is where you should probably be looking.
And now, popular uses of skip logic.
Use #1: Disqualifying Respondents
Bot’s Bistro is conducting a survey about what new menu items they should add. They’re only interested in feedback from their highest value customers, which are people over the age of 18.
Therefore, they want to disqualify any responses from customers who are under 18.
To do this, they can ask people to put their age into the appropriate category on their first page:
Under 18
18-25
26-35
36-45
46-55
55+
Anyone who chooses the radio button indicating that they are under 18 can then skip the entire survey. All they will see is a “Thank You” page (whose content you should be able to customize); this page will let them know that you appreciate their time but they don’t meet your criteria.
It’s also a good idea to make sure that this response is flagged as “Disqualified” in your results so that they aren’t inadvertently included in your aggregate results.
Being able to quickly and easily see how many potential respondents were outside their criteria could also help Bot’s Bistro distribute their next survey to a more carefully targeted audience if they’re getting too many disqualifications.
Use #2: Marking Responses as Complete (Even if They Aren’t)
Let’s say Bot’s Bistro has decided to let their respondents be anonymous if they want, but to also give them the option to provide contact details.
In order to do this, they’ll follow their required NPS (Net Promoter Score) ranking question with an optional contact details fields on page two.
But they still want to mark the response as “complete” even if the respondent skips page two, which includes the contact fields.
For that, they need skip logic.
Without skip logic, when respondents choose not to continue the survey after page one their response will be marked as partial rather than complete.
By using skip logic, the responses will appear as complete regardless of whether the respondent completed the contact fields on page two or not.
Use #3: Skipping an Irrelevant Page
Bot’s Bistro is continuing to expand their survey, now adding another question to page one that asks whether a customer dined in or carried their dinner out.
If they dined in, they would like the respondent to see a page rating their interactions with their server. However, if they ordered carry out, they would like to send them straight to the page collecting their contact information.
Once again, skip logic comes into play.
When people indicate that they dined at the restaurant, that response will cause the survey to continue in its linear fashion. The next questions they’ll see will be about their interaction with the server.
However if their answer was “Carry out,” skip logic will jump them completely over the server-related questions and send them to the optional contact details page. This kind of responsive survey design helps dramatically decrease the survey fatigue your respondents might otherwise experience.
Use #4: Redirecting to an Onsite Reward Offer
In order to collect more contact information while keeping the contact field optional, Bot’s Bistro has decided that they want to offer an incentive for people who do provide them.
That incentive is a 50% off coupon that is hosted on their website, which should only be offered to those who fill out the contact fields.
In this case, skip logic once again comes into play, but this time it will direct a respondent who completes the contact fields out of the survey and onto the Bot’s Bistro website.
Those people who choose not to fill out the contact fields would just get the standard thank you page.
Logic also allows Bot’s Bistro to mark both sets of responses as complete, while still customizing the experience based on the responses given.
Use #5: Sending Respondents to a New Survey
This advanced use of skip logic can unlock a lot of possibilities for your surveys. For the Bot’s Bistro survey, they could use the initial survey as a screening mechanism for their customers.
For example, they might want those who answer their NPS (Net Promoter Score) question very positively to be sent to a second survey asking if they want to sign up for a loyalty program.
Detractors who answer negatively could be sent to a “How Can We Improve?” survey instead.
For some extra personalization, you can also pass data in the form of URL variables to the second survey. This data could pre-populate fields in the new survey, greet the respondent by name, etc.
The Power of Logic
Survey logic is a great way to increase your response rate by keeping the questions relevant and reducing fatigue. Logic also gives you cleaner data to act on by eliminating questions that do not apply to the respondent.