Skip to main content
Multiple choice questions are the most common question type. They’re easy for participants to answer and provide structured data that’s simple to analyze.

​
Two Types of Multiple Choice

​
Single Select

Participants choose one option from the list. Use when:
  • Answers are mutually exclusive
  • You need a single preference or choice
  • Asking about primary behavior or opinion
Example:
“What is your primary reason for choosing this product?”
  • Price
  • Quality
  • Brand reputation
  • Convenience
  • Recommendation from others

​
Multiple Select (Select All That Apply)

Participants can choose multiple options. Use when:
  • Multiple answers can be true
  • Asking about behaviors or experiences that overlap
  • Wanting to capture all relevant factors
Example:
“Which of the following features do you use regularly? (Select all that apply)”
  • Online ordering
  • Mobile app
  • In-store pickup
  • Home delivery
  • Loyalty rewards

​
Creating Multiple Choice Questions

1

Add the Question

Use AI chat (“Add a multiple choice question about…”) or add manually from the question menu.
2

Write the Question Text

Make the question clear and specific.
3

Add Answer Options

Enter each option. Click “Add Option” for more.
4

Set Single or Multi-Select

Choose whether participants can select one or multiple options.
5

Configure Additional Settings

Add “Other” option, require answer, or randomize order.

​
Writing Good Options

​
Be Comprehensive

Include all reasonable options. A participant should be able to find an answer that fits.
Include an “Other (please specify)” option if you’re not certain you’ve covered all possibilities.

​
Be Mutually Exclusive (for Single Select)

Options shouldn’t overlap. A participant should clearly fit in one category. Bad: Age ranges that overlap
  • 18-25
  • 25-35 ❌ (where does 25 go?)
Good: Clear boundaries
  • 18-24
  • 25-34
  • 35-44

​
Keep Options Balanced

Avoid bias by balancing positive and negative options. Balanced scale example:
  • Extremely satisfied
  • Somewhat satisfied
  • Neither satisfied nor dissatisfied
  • Somewhat dissatisfied
  • Extremely dissatisfied

​
Use Parallel Structure

Options should follow the same grammatical pattern. Before (inconsistent):
  • Price is good
  • Quality
  • Like the brand
  • It’s convenient
After (parallel):
  • Good price
  • High quality
  • Strong brand reputation
  • Convenient location

​
Common Multiple Choice Patterns

​
Likert Scales (Agreement)

“How much do you agree with the following statement?”
  • Strongly agree
  • Somewhat agree
  • Neither agree nor disagree
  • Somewhat disagree
  • Strongly disagree

​
Satisfaction Scales

“How satisfied are you with…?”
  • Very satisfied
  • Somewhat satisfied
  • Neutral
  • Somewhat dissatisfied
  • Very dissatisfied

​
Frequency Scales

“How often do you…?”
  • Daily
  • Several times a week
  • Once a week
  • A few times a month
  • Once a month or less
  • Never

​
Likelihood Scales

“How likely are you to…?”
  • Extremely likely
  • Very likely
  • Somewhat likely
  • Not very likely
  • Not at all likely

​
Option Settings

​
Adding “None of the Above”

Include this option when participants may not identify with any choice. This is especially important for single-select questions.

​
Adding “Other (Please Specify)”

When you want to capture options you may have missed:
  1. Add an “Other” option
  2. Enable the text field for custom responses
  3. Participants who select “Other” can type their answer

​
Option Randomization

Randomize option order to reduce position bias (people tend to choose early options more often).
When randomizing, you may want to keep certain options fixed (like “None” or “Other”) at the end.

​
Required vs. Optional

Decide whether participants must answer before continuing:
  • Required: Essential questions that must be answered
  • Optional: Questions where “no answer” is acceptable

​
Best Practices

5-7 options is ideal. More options can overwhelm participants. Fewer may not capture enough variation.
Put easy options first. Start with the most common or expected answers to help participants orient.
Test your options. Have someone outside your team review to check for clarity and completeness.
Avoid leading options. Don’t use language that suggests a “right” answer.

​
Analyzing Multiple Choice Data

Multiple choice questions produce structured data:
  • Single select: Percentages for each option
  • Multi-select: Percentage of respondents who selected each option (totals over 100%)
Your analysis reports will automatically show:
  • Response distributions
  • Charts and visualizations
  • Comparisons across segments

​
Common Mistakes

Long lists fatigue participants. Consider using ranking or grouping if you have many items.
Review your options for overlap. Each participant should fit clearly in one category.
If many participants choose “Other,” you may be missing important options. Consider updating the question.
Having more positive than negative options (or vice versa) biases results.

​
Next Steps

Matrix Questions

Rate multiple items on the same scale

Conditional Logic

Show follow-ups based on selections