Closed-Ended Questions: 50+ Examples for Surveys & Research

Closed-ended questions are survey questions that provide respondents with a fixed set of answer options. The respondent cannot provide a response outside these predefined choices.

This structure makes closed-ended questions ideal for:

• Quantitative analysis — responses can be easily coded and statistically analyzed
• Benchmarking — consistent options allow comparison across time periods or segments
• Large samples — faster to complete and analyze than open-ended alternatives
• Reducing bias — standardized options minimize interpretation differences

Closed-ended questions come in several formats:

1. Dichotomous (Yes/No) Questions

The simplest form with only two options. Use for binary decisions or screening.

2. Multiple Choice Questions

Offer 3-7 options where respondents select one answer. Best for categorical data.

3. Checkbox (Multi-Select) Questions

Allow respondents to select multiple options using "select all that apply" format.

4. Rating Scale Questions

Numeric scales (1-5, 1-10) for measuring intensity, satisfaction, or likelihood.

5. Likert Scale Questions

Agreement scales from "Strongly Disagree" to "Strongly Agree" for attitude measurement.

6. Ranking Questions

Ask respondents to order options by preference or importance.

Dichotomous questions are perfect for screening, filtering, and establishing binary facts:

• "Have you purchased from our company in the past 12 months?" (Yes / No)
• "Do you currently use a project management tool?" (Yes / No)
• "Would you recommend this product to a friend?" (Yes / No)
• "Are you the primary decision-maker for software purchases?" (Yes / No)
• "Did you find the information you were looking for?" (Yes / No)
• "Do you have a budget allocated for this solution?" (Yes / No)

Best practice: Use yes/no questions for screening or routing logic, then follow up with detailed questions.

Multiple choice questions work best when options are mutually exclusive and exhaustive:

• "How did you first hear about us?" (Search engine / Social media / Friend referral / Advertisement / Other)
• "What is your primary role?" (Executive / Manager / Individual contributor / Consultant / Student)
• "How often do you use our product?" (Daily / Weekly / Monthly / Rarely / Never)
• "What is your company size?" (1-10 / 11-50 / 51-200 / 201-1000 / 1000+)
• "Which pricing tier are you most interested in?" (Starter / Professional / Enterprise / Not sure yet)
• "What is your preferred contact method?" (Email / Phone / Chat / In-person meeting)

Best practice: Include "Other" with a text field when you cannot anticipate all possible responses.

Rating scales quantify subjective experiences on a numeric continuum:

• "On a scale of 1-10, how likely are you to recommend us?" (NPS)
• "Rate your overall satisfaction with our service" (1-5 stars)
• "How would you rate the quality of customer support?" (1 = Very Poor, 5 = Excellent)
• "How easy was it to complete your purchase?" (1 = Very Difficult, 7 = Very Easy)
• "Rate your confidence in using this feature" (1-10)
• "How important is price in your purchasing decision?" (1 = Not Important, 5 = Extremely Important)

Best practice: Always label scale endpoints clearly. Consider odd scales (with neutral midpoint) or even scales (forcing a lean).

Likert scales measure agreement, frequency, or quality with balanced response options:

Agreement scales:

• "The onboarding process was easy to follow" (Strongly Disagree → Strongly Agree)
• "I feel confident using the product's advanced features" (Strongly Disagree → Strongly Agree)
• "Customer support resolved my issue effectively" (Strongly Disagree → Strongly Agree)

Frequency scales:

• "I encounter bugs or errors when using the product" (Never / Rarely / Sometimes / Often / Always)

Quality scales:

• "How would you rate the accuracy of our recommendations?" (Very Poor / Poor / Fair / Good / Excellent)

Choose closed-ended questions when:

• You need quantitative data — Statistics, percentages, and trends require structured responses
• Sample size is large — Analyzing thousands of free-text responses is impractical
• You know the possible answers — Prior research has identified the relevant options
• Comparison is important — Benchmarking requires consistent metrics
• Time is limited — Closed questions are faster to answer and analyze
• You need filtering logic — Routing respondents requires discrete options

Avoid closed-ended questions when exploring new topics or when the answer space is genuinely unknown.

Follow these guidelines:

• Make options mutually exclusive — Respondents should clearly fit into one category
• Make options exhaustive — Cover all reasonable possibilities; add "Other" if needed
• Use balanced scales — Equal positive and negative options prevent bias
• Keep lists manageable — 5-7 options is ideal; more creates fatigue
• Randomize when appropriate — Prevent order bias in multiple choice questions
• Avoid leading language — "How satisfied were you?" not "How satisfied were you with our excellent service?"
• Test your questions — Pilot with a small group to catch confusing wording

The choice depends on your research goals:

Closed-Ended Advantages:

• Quantitative, statistical analysis
• Fast to complete and analyze
• Handles large samples easily
• Consistent data for comparison

Open-Ended Advantages:

• Captures nuance and context
• Uncovers unexpected insights
• Explores complex topics in depth

Best approach: Combine both types. Use closed-ended for measurement and open-ended for explanation.