Surveys and questionnaires are essential tools for understanding your audience, but crafting the right questions is an art form.  

Close ended questions, with their predefined answer choices, simplifies the response process and ensures consistency in your data.

What is a close ended question?

Close-ended questions are questions that can be answered with a specific, limited set of responses. Unlike open-ended questions, which allow respondents to answer in their own words, close ended questions provide predefined options.

What are the advantages of close ended questions?

Easy to analyze

Close ended questions produce responses that are easy to quantify. This simplicity facilitates statistical analysis, making it straightforward to identify trends, patterns, and correlations in the data. Researchers can use software tools to quickly process large volumes of responses, allowing for efficient data handling and reporting.  

Consistency and comparability

The uniformity of close ended questions ensures that all respondents answer the same set of questions in the same way. This consistency allows for direct comparison between different groups of respondents, enhancing the reliability of the results. Researchers can easily compare data points to draw meaningful conclusions about the population being studied.

Time efficiency

For respondents, close ended questions are quicker and easier to answer. This often results in higher response rates, as the perceived effort to complete the survey is lower. For researchers, the reduced time needed to analyze responses translates to faster turnaround times for data collection and reporting, making the research process more efficient.

Reduction of ambiguity

Close ended questions minimize the risk of misinterpretation. Because the responses are predefined, there is less room for respondents to misunderstand the question or provide irrelevant information. This clarity ensures that the data collected is relevant to the research objectives and maintains a high level of accuracy.

Control over responses

Close ended questions give researchers control over the type of data collected. By specifying the possible answers, researchers can ensure that the responses are aligned with the research goals. This control helps in maintaining the focus of the survey and collecting specific information needed for analysis.

Quantitative data collection

Close ended questions are ideal for gathering quantitative data, which is essential for statistical analysis. Quantitative data allows researchers to measure variables and perform various statistical tests to understand relationships, differences, and trends within the data. This capability is crucial for making data-driven decisions and validating hypotheses.

Scalability

Close ended questions are scalable, meaning they can be effectively used in surveys of any size. Whether the survey is administered to a small focus group or a large population, close ended questions ensure that the data collected is manageable and analyzable. This scalability makes them a versatile tool for researchers in various fields.

Enables automated data collection

Close ended questions are well-suited for automated data collection methods, such as online surveys and digital questionnaires. These platforms can efficiently capture and store responses, reducing the administrative burden on researchers. Automation also enables real-time data analysis and reporting, further enhancing the efficiency of the research process.

Minimized respondent burden

Because close ended questions are easier and quicker to answer, they reduce the cognitive load on respondents. This reduction in effort can lead to higher completion rates and more reliable data, as respondents are less likely to abandon the survey or provide careless answers.

Reduction of response bias

The structured nature of close ended questions can help reduce response bias. Respondents are less likely to provide socially desirable answers or exaggerate their responses when they are limited to predefined options. This reduction in bias contributes to the accuracy and reliability of the data.

When should you ask close ended questions?

When collecting quantitative data

Close ended questions are ideal for gathering data that can be easily quantified and statistically analyzed. This is particularly useful in large-scale surveys where you need to aggregate and compare responses across a broad audience.

When seeking specific information

If you need specific, straightforward answers, close ended questions can provide clear and unambiguous data. For example, when you need to know if a respondent prefers Product A or Product B, a simple multiple-choice question is effective.

For standardized responses

Close ended questions are useful when you need standardized answers that are easy to compare. This consistency is crucial in situations like employee feedback surveys or customer satisfaction surveys, where you want to compare responses over time or across different groups.  

When measuring opinions or attitudes

Close ended questions, such as Likert scale or rating scale questions, are effective for measuring opinions, attitudes, and perceptions. They allow respondents to express the intensity of their feelings on a structured scale.

To identify trends

Close ended questions help in identifying trends and patterns over time. For example, tracking customer satisfaction scores or employee engagement levels periodically can reveal important trends that inform decision-making.

In situations requiring quick decisions

When quick decision-making is needed, such as in market research for product launches, close ended questions can provide fast, actionable insights that help guide strategic choices.

What are the types of close ended questions?

Multiple-choice questions

Multiple-choice questions offer respondents a list of options from which they must choose one or more answers.

Dichotomous questions

Dichotomous questions provide only two possible answers, typically "Yes" or "No," or "True" or "False."

Rating scale questions

Rating scale questions ask respondents to rate an item on a scale, usually numerical, and between 0-9 or 1-10.

Likert scale questions

Likert scale questions measure the extent of agreement or disagreement with a statement (ranging from strongly agree to strongly disagree).  

Checklist questions

Checklist questions provide a list of items where respondents can select multiple options.

Ranking questions

Ranking questions ask respondents to rank a list of items in order of preference or importance.

Image choice questions

Image choice questions allow respondents to select an answer from a set of images, useful for visual-based responses.  

Frequency scale questions

Frequency scale questions ask respondents to indicate how often they do something or how frequently they experience something (ranging from very rarely to very often)  

What is the best way to ask close ended questions?

Be clear and specific

Ensure the question is straightforward and easily understood. Avoid using complex language or jargon. Clear and specific questions help prevent misinterpretation and confusion, leading to more accurate responses. For instance, instead of asking "Do you like our product?" you could ask "How satisfied are you with the quality of our product?" This specifies what aspect of the product you are inquiring about.

Limit the scope

Keep questions focused on a single topic or aspect to avoid confusion. When questions are too broad, respondents might struggle to provide an accurate answer. As an example of close ended question examples, instead of asking "Do you find our website and customer service helpful?" split it into two questions: "Do you find our website helpful?" and "Do you find our customer service helpful?" This makes it easier for respondents to answer precisely.

Use simple language

Use plain and concise language to make it easy for respondents to comprehend and answer. Avoiding technical terms and complex sentence structures ensures that respondents from various backgrounds can understand the question. For instance, instead of asking "Do you endorse our product's efficacy?" ask "Do you think our product works well?" Simple language increases the likelihood of receiving clear, accurate responses.

Provide balanced options

Offer a balanced set of response options that cover all possible answers. Avoid leading questions that might bias the responses. For example, if you're asking about customer satisfaction, provide options ranging from "Very Dissatisfied" to "Very Satisfied," including neutral options in between. This balance allows respondents to accurately express their opinions without feeling steered toward a particular answer.

Include mutually exclusive choices

Ensure that the response options do not overlap to avoid confusion. For instance, if you're asking about age ranges, use non-overlapping categories like "18-24," "25-34," "35-44," etc. Overlapping choices can confuse respondents and lead to inaccurate data, as they might not know which option to select if they fall into the overlapping range.

Cover all possible answers

Include an "Other" option with a text box if the provided choices may not cover all possible responses. This ensures that respondents who don't fit into predefined categories can still provide accurate answers. For example, when asking about preferred communication methods, include options like "Email," "Phone," "Text," and "Other (please specify)." This inclusivity improves the comprehensiveness of your data.

Use appropriate scales

When using scales (e.g., Likert scales), make sure they are consistent and logical, with clearly defined endpoints. A typical Likert scale might range from "Strongly Disagree" to "Strongly Agree," with neutral options in the middle. Consistency in scales helps respondents understand how to use them and ensures that their responses accurately reflect their opinions or experiences.

Avoid double-barrelled questions

Ask one thing at a time to ensure respondents can provide a clear and accurate answer. Double-barrelled questions combine two issues into one, leading to confusion. For example, instead of asking "Do you find our website informative and easy to navigate?" split it into "Do you find our website informative?" and "Do you find our website easy to navigate?" This clarity leads to more precise responses.  

Ensure neutrality

Frame questions in a neutral way to avoid influencing the respondent’s answer. Leading questions can bias responses and skew your data. For instance, instead of asking "How much do you love our new feature?" ask "What do you think about our new feature?" Neutral wording encourages honest and unbiased feedback, providing more reliable data.  

Test your questions beforehand

Before deploying the survey, test the questions with a small group to identify any issues or misunderstandings. Pilot testing helps uncover ambiguous or confusing questions and allows you to make necessary adjustments. Gathering feedback from a diverse group ensures that your questions are clear and effective for your target audience, leading to higher-quality responses when the survey is officially launched.  

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