Closed-ended survey questions: Types, examples, and when to use them

The quality of your user research comes down to the quality of your questions. In market and brand research, even tiny choices like the words you use, the way you structure a question or the options you give, can completely change the results you get.

Close ended survey questions are one of the best ways to collect quantitative data that is both clean and scalable. They’re often dismissed as “basic,” but they’re anything but. When designed thoughtfully, they create the structured insights that make brand tracking, ad testing and customer segmentation possible. When designed poorly, they quietly sabotage your research.

In this guide, we’ll break down the different types of close ended survey questions, explain when to use each, and show how specific formats shape the depth of insight you’ll get. 

We’ll also share examples, common mistakes to avoid, and tips for balancing closed and open-ended questions so you don’t miss the context behind the data.

TL;DR: Closed-ended survey questions explained

What is a closed-ended survey question?

A closed-ended survey question gives respondents a fixed list of answers to choose from, making responses easy to analyze. They’re ideal for gathering structured, measurable data quickly. For example: “Did the product meet your expectations?” Yes / No

What is the difference between closed-ended vs open-ended survey questions? 

• Closed-ended survey questions provide structured response options that are easy to quantify.
• Open-ended survey questions allow for more detailed, free-form answers in the respondent’s own words.
  
  Example:
  
• Closed: “How often do you shop online?” Daily / Weekly / Rarely
• Open: “Describe your last online shopping experience.”

What is a close ended question?

A closed-ended question is a survey question type that gives people a fixed set of responses to choose from. Instead of writing their own response, participants select the option that best fits their opinion or experience. You’ll see these in formats like:

• Single or multiple choice questions
• Yes/no
• Rating scales
• Ranking questions

The big advantage of this setup is structure. Because everyone is answering within the same framework, the quantitative data you collect is clean, consistent, and ready for analysis. 

You can quickly tally percentages, compare groups, or track changes over time without sifting through pages of free-text answers. That’s why closed-ended questions are so popular in large-scale surveys like brand trackers or customer profiling studies – because they deliver standardized results that are easy to interpret and share.

Also, closed ended questions are also faster for respondents to answer. Choosing from a list is less effort than typing out a full explanation. This  often means higher survey completion rates and more reliable data.

That doesn’t mean closed-ended questions are always the best choice. Sometimes you need richer, more nuanced feedback; the kind that comes from open-ended questions where people can write in their own words. But when your goal is measurable, closed-ended questions give you the clarity and efficiency you need.

Close ended vs open ended questions

When designing a survey, one of the biggest choices you’ll make is whether to use closed-ended or open-ended questions. Both play important roles, but they work in very different ways. Below, we’ll discuss the differences in more detail below. 

Closed-ended questions give respondents a predefined set of responses (e.g., yes/no, multiple choice questions, rating scales). 

Open-ended questions, on the other hand, leave the response entirely up to the participant. Instead of picking from a list, they provide an answer in their own words. This provides richer qualitative data like context, motivations and nuance that quantitative responses can’t capture.

Here’s a side-by-side look:

Feature	Closed-ended questions	Open-ended questions
Format	Respondents select from predefined options (e.g., yes/no, multiple choice questions, scales).	Respondents provide answers in their own words, with no restrictions.
Depth of insight	Broad but shallow. You learn “what” people think or do, but not always “why.”	Rich and detailed, reveals motivations, reasoning, and nuance.
Ease of analysis	Easy. Results are standardized, quantifiable, and simple to chart or compare.	Harder. Requires text analysis, coding, or manual review to extract patterns.
Respondent effort	Low. Quick clicks or selections keep surveys short and accessible.	Higher. Requires time and thought, which can lead to fatigue or drop-off.
When to use	Tracking metrics, segmentation, large-scale studies, benchmarking.	Explore new ideas, uncover unmet needs and understand reasoning behind choices.
Example	“Was our support team able to resolve your issue? Yes/No”	“How would you describe your experience with our support team?”

When should you use close ended questions?

Close-ended questions really shine when you need structure, consistency, and scale. Because everyone responds using the same predefined options, you can easily compare results across thousands of respondents without drowning in unstructured text. That makes them a go-to for surveys where statistical analysis, reliability and trend tracking matter most.

That being said, keep in mind that close-ended questions are powerful, but they’re not the full story. On their own, they risk oversimplifying people’s experiences. That’s why many researchers combine them with open-ended questions, using close-ended for the scale, and open-ended for the “why” behind the data.

Here’s where close ended questions are most impactful:

Customer feedback forms

If you want to measure satisfaction after a purchase or service interaction, a rating scale or yes/no question cuts straight to the point. 

For example, asking “How satisfied were you with your recent purchase?” on a 1–5 scale makes it easy to calculate averages and track shifts over time. This structured approach also makes it easier to compare feedback across different products, locations, or time periods.

NPS and CSAT surveys

Net Promoter Score (NPS), which measures customer loyalty, and Customer Satisfaction (CSAT) surveys, which track how happy customers are with a product or service, both rely on standardised formats to deliver clean, benchmarkable results. Without a fixed scale, you couldn’t measure loyalty or satisfaction consistently across large samples or multiple time periods. 

Standardized answer choices make it possible to spot trends, identify outliers and create meaningful reports that stakeholders can act on.

Market research at scale

When you conduct market research and need to test ad concepts or gauge brand awareness. Close-ended questions help you collect valuable insights across your target  population in a way that can be segmented by demographics. 

For example, asking “Which of these brands have you heard of?” provides quantifiable awareness data you can break down by age, location, or other attributes.

You can then segment responses to give a clear picture of which audiences are familiar with your brand and which may need more targeted messaging.

Demographic profiling

Structured formats are essential for profiling. Demographic profiling, which involves collecting information like age, gender, location, or purchasing habits, helps researchers understand who their respondents are and how different groups behave. 

Questions like “Which age range do you fall into?” or “How often do you purchase online?” only work if the answers are pre-defined. This structure allows researchers to group and compare respondents effectively, uncover patterns across different segments, and ensure that subsequent analysis is consistent and actionable.

Types of close ended questions

There are several common closed-ended question formats, and each one serves a different research job. 

Pick the right format and you get clean, segmentable numbers; pick the wrong one and you force people into answers that don’t reflect reality. Here are the main types that’ll help you collect survey responses, along with examples of open-ended survey questions.

Dichotomous (Yes / No, True / False)

This is the simplest version of a closed-ended question: two possible answers with nothing in between. It’s often used when you just need to confirm or deny something.

ℹ️ Example: “Did you complete checkout successfully? Yes / No.”

Because the format is so binary, it’s great for quick diagnostics or funnel analysis: did someone convert, or not? Are they aware of a brand, or not? It’s also handy for splitting your target audience into clear groups for follow-up analysis.

But simplicity comes at a cost. People’s experiences aren’t always black and white, so a yes/no format can feel limiting. When in doubt, give respondents an escape hatch like Not sure or Not applicable to avoid muddying your data collection.

Multiple choice questions (Single-select and Multi-select)

Multiple choice questions are  important in survey design. Respondents choose from a list of multiple options you provide. It can be either one option (single-select) or several (multi-select).

ℹ️ Examples:

• Single-select: “Which feature is most valuable to you? A / B / C / D.”
• Multi-select: “Which channels do you use to learn about products? Email; Social; Search; Friends (select all that apply).”

This format of multiple choice questions is ideal when you want to understand customer preferences, behaviors or usage. Single-select questions give you clean, mutually exclusive data, while multi-select shows overlaps and patterns (e.g., customers who use both social and email).

The catch is that your answer list needs to be carefully written. Overlap or missing options can frustrate respondents and skew your results. Keep lists short and balanced, and always include an Other if the universe of answers is broad.

Rating scales (Likert, star ratings, sliders)

Sometimes you don’t just want to know what people think, but you want to measure how strongly they feel it. This is where rating scales help.

ℹ️ Example: “How satisfied were you with the support you received? 1 (Very dissatisfied) to 5 (Very satisfied).”

Likert scales (from “Strongly disagree” to “Strongly agree”), star ratings or sliders allow  you to track sentiment and intensity over time. They’re especially useful for metrics like customer satisfaction or brand perception, because they generate quantitative data to benchmark and trend.

The design details matter, though. Decide if you want a neutral midpoint (like a 3-point, 5-point, or 7-point scale). Also, keep your scales consistent throughout the survey. Flipping between “1 = good” and “1 = bad” is a guaranteed way to confuse people and results in messy data.

Ranking (Order of preference)

When you need respondents to prioritize, ranking questions do the job. Instead of just saying what they like, people put options in order of importance.

ℹ️ Example: “Rank the following feature ideas from most to least useful: A, B, C, D.”

When users rank features by preference, it guides roadmap decisions and product design by forcing trade-offs. You see not only what matters to your customers but also what matters most. Still, ranking questions can be cognitively demanding, especially with long lists. Keep it to 5–7 items max, or consider a top-3 ranking if you need to cover more ground without overwhelming people.

Drop-down / Select

Sometimes the difference between question types is about design, and not data. Drop-downs work like single-select multiple choice questions, but they hide the full list until someone clicks.

ℹ️ Example: “Select your industry: [drop-down list].”

This is most useful when you have long lists (like countries or industries) or limited space on the survey page. It keeps things tidy, especially on mobile.

However, since not all options are visible at once, less common answers can get overlooked. If you’re using a drop-down, consider adding a search function and always include an Other or Prefer not to say to cover gaps.

The advantages and disadvantages of closed ended questions

It’s tempting to treat closed-ended questions as the “safe bet” for survey design. After all, they’re quick to answer and even quicker to analyze. But like any tool, they work best in the right context and can fall flat in the wrong one. That’s why it’s crucial to know both what they do brilliantly, and where they might leave you with blind spots.

Benefits of close ended questions

• They’re quick to answer: Clicking an option or moving a slider takes seconds. Survey respondents are more likely to finish your survey instead of dropping off halfway, which is especially important for longer surveys or mobile users.
• They give you clean, crunchable quantitative data: You get data that’s easy to chart, compare, and analyze because everyone answers in the same format.
• They make comparisons simple: Standardized answers mean you can benchmark over time, across regions or between customer segments. You can see trends at a glance and confidently track shifts in opinion or behavior.
• They reduce confusion: Predefined options make it clear what you’re asking. Survey respondents don’t have to guess how to answer, and you avoid ambiguous responses that are hard to interpret.
• They let you filter results: Structured answers make it easy to slice data by demographics, behaviors or other key variables. You can uncover patterns and differences between groups without having to wade through endless text responses.

Limitations of closed-ended questions

• They can miss nuance: While closed-ended questions are great for structured quantitative data, they rarely capture the subtleties of opinion that qualitative data reveals. Pairing the two ensures you don’t miss valuable insights that could inform strategy or reveal unexpected patterns.
• They offer limited answer options: If the predefined choices in open-ended questions don’t fully capture respondents’ perspectives, people can feel constrained or frustrated. This can lead to skipped questions, inaccurate answers or overuse of “Other” options.
• They can introduce bias: Poorly worded or leading answer choices in open-ended questions may unintentionally steer responses. Even small wording differences can shift results, so careful phrasing and balanced options are essential for reliable, quantitative data.
• They work best when paired with open-ended questions: Closed-ended questions excel at structure, trends, and segmentation, but they rarely tell the whole story on their own. Pairing them with targeted open-ended follow-ups adds depth and context to your findings.

Why mastering closed-ended questions pays off

Closed-ended questions are the backbone of structured survey research and they provide clarity, consistency and scalability. This gives you individual responses that you can turn into data you can analyze, compare and act on. Plus, closed-ended questions give you clean, reliable numbers that reveal trends and highlight differences across groups, whether you’re tracking customer satisfaction, measuring brand perception or segmenting audiences.

The true strength of closed-ended questions emerges when paired with open-ended questions: quantitative data shows what is happening, and qualitative data reveals why. Together, they create a balanced approach that captures both scale and nuance, so that researchers can extract helpful insights from the data with confidence.

In the end, the goal is simple: to turn survey responses into understanding, and understanding into action. Closed-ended questions, when wielded with precision and paired with complementary open-ended responses, give researchers the clarity, scale and direct insight they need to draw meaningful conclusions. The more proficient you become at crafting them, the more your surveys will evolve from a routine exercise into a powerful engine for informed decisions; the kind that drives strategy, innovation and growth.