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.
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).
|Open-ended questions||Closed-ended questions|
For example, an open-ended question might be: “What do you think of statistical analysis software?” Whereas a closed-ended question would simply be: “Do you use statistical analysis software?”
Open-ended questions afford much more freedom to respondents and can result in deeper and more meaningful insights.
When and why should you use open-ended questions?
Close-ended questions are perfect for affordable market research at scale. They’re quick to develop, deploy and get responses to (as your target audience doesn’t have to think too much about their own responses). That said, as they are often single-word answers, they are considered leading questions as the respondent has no real flexibility in their response.
Open-ended questions, however, are great for getting a better understanding of your customers and their needs. When it comes to delivering value and products, services and/or solutions that are meaningful, context is everything. Better yet, combine open-ended surveys with closed-ended surveys to truly understand the big picture.
Open-ended questions can also help you to learn things you didn’t expect, especially as they encourage creativity, and get adequate answers to slightly more complex issues.
You might use open-ended questions when you want to study a small population or carry out preliminary research to validate a product idea. Or perhaps you want to understand a bit more about your target audience and use a small, but representative, sample size to assess your market at scale.
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.
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.
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. 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 analyze.
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 responses with minimal human intervention.
For example, you could use automated coding via artificial intelligence to look into buckets of responses 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.
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.
For example, 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. And the best part? It’s completely free to get started with.