Your quick guide to open-ended survey questions

When you want to get more comprehensive responses to a survey – answers beyond just yes or no – you’ll want to consider open-ended questions.

But what are open-ended questions? In this guide, we’ll go through what open-ended questions are, including how they can help gather information and provide greater context to your research findings.

What are open-ended questions?

Free-form and not governed by simple one-word answers (e.g. yes or no responses), open-ended questions allow respondents to answer in open-text format, giving them the freedom and space to answer in as much (or as little) detail as they like.

Open-ended questions help you to see things from the respondent’s perspective, as you get feedback in their own words instead of stock answers. Also, as you’re getting more meaningful answers and accurate responses, you can better analyse sentiment amongst your audience.

Also, depending on the scale of your survey or market research, you could analyse your open-ended responses at scale, using spreadsheets or automated tools to capture and understand open-text.

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Open-ended versus closed-ended questions

Open-ended questions provide more qualitative research data; contextual insights that accentuate quantitative information. With open-ended questions, you get more meaningful user research data.

Closed-ended questions, on the other hand, provide quantitative data; limited insight but easy to analyse and compile into reports. Market researchers often add commentary to this kind of data to provide readers with background and further food for thought.

Here are the main differences between open and closed-ended questions (and some examples).

For example, an open-ended question might be: “What do you think of statistical analysis software?”.

Whereas closed-ended questions would simply be: “Do you use statistical analysis software?” or “Have you used statistical analysis software in the past?”.

Open-ended questions afford much more freedom to respondents and can result in deeper and more meaningful insights. A closed question can be useful and fast, but doesn’t provide much context. Open-ended questions are helpful for understanding the “why”.

When and why should you use open-ended questions?

Open-ended questions are great for going more in-depth on a topic. Closed-ended questions may tell you the “what,” but open-ended questions will tell you the “why.”

Another benefit of open-ended questions is that they allow you to get answers from your respondents in their words. For example, it can help to know the language that customers use to describe a product of feature, so that the company can match the language in their product description to increase discoverability.

Open-ended questions can also help you to learn things you didn’t expect, especially as they encourage creativity, and get answers to slightly more complex issues. For example, you could ask the question “What are the main reasons you canceled your subscription?” as a closed-ended question by providing a list of reasons (too expensive, don’t use it anymore). However, you are limited only to reasons that you can think of. But if you don’t know why people are canceling, then it might be better to ask as an open-ended question.

You might ask open-ended questions when you are doing a pilot out preliminary research to validate a product idea. You can then use that information to generate closed-ended questions for a larger follow-up study.

However, it can be wise to limit the overall number of open-ended questions in a survey because they are burdensome.

In terms of what provides more valuable information, only you can decide that based on the requirements of your research study. You also have to take into account variables such as the cost and scale of your research study, as well as when you need the information. Open-ended questions can provide you with more context, but they’re also more information to sift through, whereas closed-ended questions provide you with a tidy, finite response.

If you still prefer the invaluable responses and data from open-ended questions, using software like Qualtrics Text IQ can automate this complicated process. Through AI technology Text IQ can understand sentiment and articulate thousands of open-ended responses into simplified dashboards.

Examples of open-ended questions

While there are no set rules to the questions you can ask (and of course you want to ask questions that correlate with your research objective), here are a few examples of good open-ended survey questions related to your product:

• What do you like most about this product?
• What do you like least about this product?
• How does our product compare to competitor products?
• If someone asked you about our product, what would you say to them?
• How can we improve our product?

You could even supplement closed-ended questions with an open-ended question to get more detail, e.g. “How often do you use our product?” — with options such as “Frequently”, “Sometimes”, “Never” — and if a respondent answers “Never”, you could follow with: “If you have never used our product, why not?”. This is a really easy way to understand why potential customers don’t use your product.

Also, incorporating open-ended questions into your surveys can provide useful information for salespeople throughout the sales process. For example, you might uncover insights that help your salespeople to reposition your products or improve the way they sell to new customers based on what existing customers feel.

It doesn’t need to be complicated, it can be as simple as what you see below. The survey doesn’t need to speak for itself, let your survey respondents say everything.

Asking open-ended questions: Crafting question that generate the best insights 

Open responses can be difficult to quantify. Framing them correctly is key to getting useful data from your answers. Below are some open ended questions examples of what to avoid.

1. Avoid questions that are too broad or vague

Example:  “What changes has your company made in the last five years due to external events?” 

Problem: There are too many potential responses to this query, which means you’ll get too broad a range of answers. What kind of changes are being referred to, economic, strategic, personnel etc.? What external events are useful to know about? Don’t overwhelm your respondent with an overly broadquestion – ask the right questions and get precise answers. 

Solution: Target your questions with a specific clarification of what you want. For example, “What policy changes has your company made about working from home in the last 6 months as a result of the COVID-19 pandemic?”. Alternatively, use a close-ended question, or offer examples to give respondents something to work from.

2. Make sure that the purpose of the question is clear

Example:  “Why did you buy our product?” 

Problem: This type of unclear-purpose question can lead to short, unhelpful answers. “Because I needed it” or “I fancied it” don’t necessarily give you data to work with. 

Solution: Make it clear what you actually want to know. “When you bought our product, how did you intend to use it?” or “What are the main reasons you purchased [Our Brand] instead of another brand?” might be two alternatives that provide more context. 

3. Keep questions simple and quick to answer

Example:  “Please explain the required process that your brand uses to manage its contact centre (i.e. technical software stack, approval process, employee review, data security, management, compliance management etc.). Please be as detailed as possible.”

Problem: The higher the level of effort, the lower the chances of getting a good range of responses or high quality answers. It’s unlikely that a survey respondent will take the time to give a detailed answer on something that’s not their favourite subject. This results in either short, unhelpful answers, or even worse, the respondent quits the survey and decides not to participate after seeing the length of time and effort required. This can end up causing bias with the type of respondents that answer the survey.

Solution: If you really need the level of detail, there are a few options to try. You can break up the question into multiple questions or share some information on why you really need this insight. You could offer a different way of submitting an answer, such as a voice to text or video recording functionality, or make the question optional to help respondents to keep progressing through the survey. Possibly the best solution is to change from open-ended questions in a survey to a qualitative research method, such as focus groups or one-to-one interviews, where lengthier responses and more effort are expected.

4. Ask only one  question at a time

Example:  “When was the last time you used our product? How was your experience?” 

Problem: Too many queries at once can cause a feeling of mental burden in your respondents, which means you risk losing their interest. Some survey takers might read the first question but miss the second, or forget about it when writing their response. 

Solution: Only ask one thing at a time!

5. Don’t ask for a minimum word count

Example:  “Please provide a summary of why you chose our brand over a competitor brand. [Minimum 50 characters].”

Problem: Even though making a minimum word count might seem like a way to get higher quality responses, this is often not the case. Respondents may well give up, or type gibberish to fill in the word count. Ideally, the responses you gather will be the natural response of the person you’re surveying – mandating a word count impedes this.

Solution: Leave off the word count. If you need to encourage longer responses, you can expand the text box size to fit more words in. Offer speech to text or video recording options to encourage lengthier responses, and explain why you need a detailed answer.

6. Don’t ask an open-ended question when a closed-ended question would be enough

Example:  “Where are you from?”

Problem: It’s harder to control the data you’ll collect when you use an open question when a closed one would work. For example, someone could respond to the above question with “The US”, “The United States” or “America”. 

Solution: To save time and effort on both your side and the participant’s side, use a drop down with standardised responses. 

7. Limit the total number of open-ended questions you ask

Example:  “How do you feel about product 1?” “How do you feel about product 2?” “How do you feel about product 3?”

Problem: An open question requires more thought and effort than a closed one. Respondents can usually answer 4-6 closed questions in the same time as only 1 open one, and prefer to be able to answer quickly. 

Solution: To reduce survey fatigue, lower drop-off rates, and save costs, only ask as many questions as you think you can get an answer for. Limit open-ended questions for ones where you really need context. Unless your respondents are highly motivated, keep it to 5 open-ended questions or fewer. Space them out to keep drop-offs to a minimum. 

8. Don’t force respondents to answer open-ended questions

Example:  “How could your experience today have been improved? Please provide a detailed response.”

Problem: A customer may not have any suggestions for improvements. By requiring an answer, though, the customer is now forced to think of something that can be improved even if it would not make them more likely to use the service again.  Making these respondents answer means you risk bias. It could lead to prioritizing unnecessary improvements. 

Solution: Give respondents the option to say “No” or “Not applicable” or “I don’t know” to queries, or to skip the question entirely. 

How to analyse the results from open-ended questions

Step 1: Collect and structure your responses

Online survey tools can simplify the process of creating and sending questionnaires, as well as gathering responses to open-ended questions. These tools often have simple, customisable templates to make the process much more efficient and tailored to your requirements.

Some solutions offer different targeting variables, from geolocation to customer segments and site behaviour. This allows you to offer customised promotions to drive conversions and gather the right feedback at every stage in the online journey.

Upon receipt, your data should be in a clear, structured format and you can then export it to a CSV or Excel file before automatic analysis. At this point, you’ll want to check the data (spelling, duplication, symbols) so that it’s easier for a machine to process and analyse.

Step 2: Use text analytics

One method that’s increasingly applied to open-ended responses is automation. These new tools make it easy to extract data from open-text question responses with minimal human intervention. It makes an open-ended question response as accessible and easy to analyse as that of a closed question, but with more detail provided.

For example, you could use automated coding via artificial intelligence to look into buckets of responses to your open-ended questions and assign them accordingly for review. This can save a great deal of time, but the accuracy depends on your choice of solution.

Alternatively, you could use sentiment analysis — a form of natural language processing — to systematically identify, extract and quantify information. With sentiment analysis, you can determine whether responses are positive or negative, which can be really useful for unstructured responses or for quick, large-scale reviews.

Some solutions also offer custom programming so you can apply your own code to analyse survey results, giving complete flexibility and accuracy.

Step 3: Visualise your results

With the right data analysis and visualisation tools, you can see your survey results in the format most applicable to you and your stakeholders. For example, C-Suite may want to see information displayed using graphs rather than tables — whereas your research team might want a comprehensive breakdown of responses, including response percentages for each question.

This might be easier for a survey with closed-ended questions, but with the right analysis for open-ended questions’ responses, you can easily collate response data that’s easy to quantify.

With the survey tools that exist today, it’s incredibly easy to import and analyse data at scale to uncover trends and develop actionable insights. You can also apply your own programming code and data visualisation techniques to get the information you need. No matter whether you’re using open-ended questions or getting one-word answers in emojis, you’re able to surface the most useful insights for action.

Ask the right open-ended questions with Qualtrics

With Qualtrics’ survey software, used by more than 13,000 brands and 99 of the top 100 business schools, you can get answers to the most important market, brand, customer, and product questions with ease. Choose from a huge range of multiple-choice questions (both open-ended questions and closed-ended) and tailor your survey to get the most in-depth responses to your queries.

You can build a positive relationship with your respondents and get a deeper understanding of what they think and feel with Qualtrics-powered surveys. The best part? It’s completely free to get started with.