<aside> ⭐ Qualitative surveys ask open-ended questions to find out more, sometimes in preparation for doing quantitative surveys. They are the quick and relatively easy way to get data about your users and potential users. Test surveys to eliminate problems.

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Qualitative surveys ask open-ended questions to find out more, sometimes in preparation for doing quantitative surveys. They are the quick and relatively easy way to get data about your users and potential users. Test surveys to eliminate problems.

To develop products in the right direction, we all need to research the experience of our users, discover their needs and unpack the insights. That’s how we build and design solutions and the user plays a lead role in this fascinating movie.

Sooner or later, most UX professionals will need to conduct a survey. Survey science from the quantitative side can be intimidating because it’s a specialized realm full of statistics, random selection, and scary stories of people going wrong with confidence. Don’t be afraid of doing qualitative surveys, though. Sure, it’s important to learn from survey experts, but you don’t have to be a survey specialist to get actionable data. You do have to find and fix the bugs in your questions first, however.

As product managers, designers, and researchers we have a large toolset to discover what our users want and how it corresponds with the business needs. We are like the screenwriters of the next hit blockbuster who are creating characters, writing their stories, and developing the parts that users play in our products. But how should we figure out what matters the most? This is where a thoughtful UX survey can come in handy.

Surveys are an effective way of gathering feedback on a live product, exploring a company’s USP, Contextual inquiry, refining a new feature, and lowering the risk of a poor solution.

Surveys consist of majorly two types of questions:

Closed Questions: These questions get quantitative data from the users. It doesn’t tell us about the context, the motivation, or the cause of the response. These questions are accompanied by the checkbox and radio buttons. The data obtained can be easily visualized with the help of graphical representations.

Open Questions: Open Questions are the qualitative data about a user’s behavior and action. It tells us how the user thinks about a problem. These questions required a text box to explain the cause. The Qualitative responses tend to take a lot longer to analyze.

Tips for Qualitative Surveys

Unordered lists can be more time-consuming to look through than lists that have an obvious ordering principle, but unordered lists seem to yield better answers, especially if you can sort the list differently for different respondents.

1. Test your survey. Here’s the procedure that we recommend:
   1. Draft questions and get feedback from colleagues.
   2. Draft survey and get colleagues to attempt to answer the questions. Ask for comments after each question to help you revise questions toward more clarity and usefulness.
   3. Revise survey and test iteratively on paper. We typically do 4 rounds of testing, with 1 respondent per round. At this stage, don’t rely on colleagues, but recruit participants from the target audience. Revise between each round. Run these tests as think-aloud studies; do not send out the survey and rely on written comments — they will never be the same as a realtime stream of commentary.
   4. Randomize some sections and questions of the survey to help ensure that (1) people quitting partway through don’t affect the overall balance of data being collected, and (2) the question or section ordering doesn’t bias people’s responses.
   5. Test the survey-system format with a small set of testers from the target audience, again collecting comments on each page.
   6. Examine the output from the test survey to ensure the data gathered is in an analyzable, useful format.
   7. Revise the survey one more time.
2. Don’t make your own tool for surveys if you can avoid it. Many solid survey platforms exist, and they can save you lots of time and money.
3. Decide up front what the survey learning goals are. What do you want to report about? What kind of graphs and tables will you want to deliver?
4. Write neutral questions that don’t imply particular answers or give away your expectations.
5. Open vs. closed answers: Asking open-ended questions is the best approach, but it’s easy to get into the weeds in data analysis when every answer is a paragraph or two of prose. Plus, users quickly tire of answering many open-ended questions, which usually require a lot of typing and explanation. That being said, it’s best to ask open-ended questions during survey testing. The variability of the answers to these questions during the testing phase can help you decide whether the question should be open-ended in the final survey or could be replaced with a closed-ended question that would be easier to answer and analyze.
6. Carefully consider how you will analyze and act on the data. The type of questions you ask will have everything to do with the kind of analysis you can make: multiple answers, single answers, open or closed sets, optional and required questions, ratings, rankings, and free-form answer fields are some of the choices open to you when deciding what kinds of answers to accept. (If you won’t act on the data, don’t ask that question. See guideline #12.)
7. Multiple vs. single answers: Often multiple-answer questions are better than single-answer ones because people usually want to be accurate, and often several answers apply to them. Survey testing on paper can help you find multiple-answer questions, because people will mark several answers even when you ask them to mark only one (and they will complain about it). If you are counting answers, consider not only how many responses each answer got, but also how many choices people made.