The success of any survey doesn’t only depend on the questions you ask but also on how you ask them. How questions are presented can shape the quality of feedback you get or the data you want to get, so choosing the right question types really matters.

Quick overview of how survey design impacts data quality and response rates:
The way a survey is designed and the way questions in the survey are framed or structured directly impact the response rate,the quality and validity of your date. The accuarcay of your data is also affected, as poorly designed surveys leads to biased responses & survey fatigue resulting in a high abandon rate.

Importance of choosing the right question format for your goals
Choosing the right question format depends on what your goals are. If you are measuring satisfaction, gathering ideas or tracking trends overtime, there are appropriate  questions suited to various types of survey goals. type. Selecting the wrong question format can confuse your respondent or make it hard to interpret data. So your question format should always match your intent.

What Is a Likert Scale?

A Likert scale is a type of scale that is used to measure the attitude of people, their opinions or their views with a variety of fixed responses. Likert scales basically ask people to show their level of agreement or disagreement with a statement.

An example is: 

“The interface is easy to navigate”

• Strongly agree
• Agree
• Neutral
• Disagree
• Strongly disagree

Types of Likert Scales (And When to Use Each)

There are different types of likert scale but the most used ones are the 5-point scale and the 7-point scale.

The 5-point scale: The 5-point scale is simple and faster to complete. They are ideally used for general surveys with diverse audiences, while

The 7-point scale: they have more variation and are better suited for detailed feedback and more analytically driven research.    

Odd vs. even number of options: Odd number option includes the neutral middle option the “Neutral” option while even number options forces a choice which can reduce indecision but may skew the result if neutrality is legitimate.

Some examples of Likert-style questions are:

• “I feel confident using this product”
• “Customer support resolved my issue efficiently
• “I would recommend this service to others”

Pros of Using Likert Scales

• They are easy for the respondent to understand
• They quantify subjective opinions
• They are ideal for tracking changes over time.

Cons of Likert Scales And When to Avoid Them

• Risk of bias (central tendency, acquiescence)

Central Tendency: Respondents may avoid extreme answers and stick to the middle options.
Acquiescence: People may agree with statements regardless of content, especially if unsure or trying to be agreeable.

• They are not good for factual or open-ended data
• They may not give deep insight into complex topics

When to avoid Likert scale:

• Likert scale should be avoided when factual or objective information is needed.
• When qualitative insights are more valuable than numerical trends, the Likert scale should not be used. 
• When explaining complex or sensitive issues that require detailed responses.
• In small samples where biases may significantly affect the results.

Overview of Other Common Survey Question Types

• Multichoice: they are good for factual data or categorical analysis

• Open-ended: this is ideal for in-depth responses, comments, or suggestions from respondents.

• Ranking responses:  they ask respondents to order their preferences or priorities.

• Yes/No Binary questions: they are simple and quick answers for clear decisions.

• Dropdown and checkboxes: these are good for a long list of options or multiple selections.

Likert vs. Other Question Types: 

Likert scale captures the opinion of respondents, specifically to the extent to which they agree or disagree while the other types of questions like open-ended question, closed ended question, multiple choice, rating question, ranking question, matrix question, demographic questions, dichotomous questions, hypothetical questions and follow-up questions are used for different purposes. 

Open-ended questions

These are those types of questions that invite a person to answer some questions using their own words, thereby opening up a conversation and getting better details, by providing more information than a simple yes or no answer that respondents usually give. Open-ended questions are great for qualitative research, and also when used in a questionnaire, they are typically answered using text boxes.

An example of an open-ended question is: “How do you like to spend your free time?”

Closed-ended questions

This gives the respondent a small amount of options to choose from, often leading to them using one-word answers. They are best for collecting quantitative data and they are popular in surveys, as quantitative data is easier to analyze than qualitative data. There are a few types or versions of close-ended questions, which range from dichotomous (e.g. yes or no) to multiple-choice, with each having advantages and best use cases.

An example of a close-ended question: “Did you achieve what you came here to do today?”

Multiple choice

Multiple choices are one of the most essential or basic question types in a questionnaire, they present the respondents with either a single select option or multi select option (where more than one answer can be chosen from a list). Age range would be an example of a single select option while picking from a list of foods might be a multi-select option, that is if there is more than one response.. 

Example of multiple choice questions: How many devices do you use to browse the internet? 1, 2  or 3+

Rating questions

These are used to enable the comparison of different research items such as product or service features using a consistent scale. respondents might be asked to rate a series of choices on a rating scale let’s say between 1 to 5, where 1 is Not at all important and 5 is Very important.

There are a variety of scales that these questions can use such as numbers, frequency (daily to annually, never to always), comparative weighting, stars and other types.. 

An example of rating questions: Out of 5, how would you rate our delivery service?

Ranking questions

Ranking questions ask respondents to choose their preferences between a list of research options such as product attributes, packaging designs, or even holiday destinations, to identify which are the most and least favored. As few as two choices might be presented, while a neutral or don’t know the answer may or may not be included.

Ranking questions are useful for finding out what customers want, and work well in conjunction with rating scale questions. 

Example of ranking questions: Which of the following bolt-ons would be the most influential in your choice of service provider?

Matrix questions

These are closed ended or have a limited set of answers and present respondents with a number of questions laid out in rows but using the same selection of column choices.

Checkboxes are typically used, with the respondent selecting one option in a row, for example a rating scale from “very poor” to “excellent”, with each row using that same scale. 

Example of matrix question: Following your recent exhibition visit, please rate your levels of satisfaction with each of these criteria. 

Demographics questions

Demographic questions are those questions that look to categorise the identity of the survey respondent based on factors such as their age, gender, ethnicity, marital status, household income, employment, education level and location.

Getting this information allows a better understanding of how respondents fit into the general population. Some demographic questions can be sensitive, however, and so need to be asked with care. 

Example of a demographic question: What is your highest level of education?

• Less than high school
• High school diploma or equivalent (e.g., GED)
• Some college, no degree
• Associate degree (e.g., AA, AS)
• Bachelor’s degree (e.g., BA, BSC)
• Master’s degree (e.g., MA, MBA)
• Professional degree (e.g., MD, JD)
• Doctorate (e.g., PhD, EdD)
• Prefer not to say

Dichotomous questions

Dichotomous questions are mostly used to point out a Yes or No, Agree or Disagree, or True or False response by offering two possible answers. they are a useful way to clarify opinions and understanding, and to direct respondents to relevant next questions. But they should also be used with care to avoid frustration or compromised results. 

An example of a Dichotomous question: Are you planning a holiday trip in the next few months? Yes, No.

Hypothetical questions

These are questions which are based on an imagined situation rather than facts or actual experience. As such they can be used to point out respondents’ opinions and beliefs about something that hasn’t happened but could possibly happen. The survey must set the parameters or criteria for the scenario being explored.

Hypothetical questions basically assume certain conditions exist such as experience, understanding, opinions or events and so can be problematic. This question is one of the least used types of questions in a questionnaire, hypothetical questions are generally avoided and If used, they should be used with great caution. 

Example of hypothetical questions: How would you approach a task that made you dissatisfied with your job?

Follow up questions

Follow up questions are those questions that are being asked in response to a respondent’s previous answer, asking to clarify or delve deeper into their response. These questions are important for getting more insights that the initial question asked might have not fully clarified. By going further, follow up questions help to show the reasons behind opinions, behaviours, and experiences, providing better and more detailed data.

Follow up questions need careful designing to ensure they are relevant, non leading, and easy for respondents to understand. While they also add significant value by giving deeper insights.  poorly designed follow up questions can lead to survey fatigue, therefore, they should be used thoughtfully and selectively. 

Example of follow-up questions: Can you share with us what led to your dissatisfaction concerning our service and how we can improve?

When to Use What

1st Use case: Customer satisfaction
Suitable question types to use: Likert scale or rating scale

2nd Use case: Product feedback
Suitable question types to use: multiple choice, open-ended, Likert

3rd Use case: Market research
Suitable question types to use: Ranking, multiple choice

5th Use case: Employee engagement
Suitable question types to use: Likert scale or open-ended

5th Use case: Usability testing
Suitable question types to use: Open-ended or rating scale

How to Combine Likert Scales With Other Question Types

1. Use the Likert scale to quantify attitudes in the questions.
2. Then follow up with an open-ended question for context. For example, “Please explain your rating above”. This is a hybrid approach that provides both quantitative (easy to analyze) and qualitative (deep insight) data.
3. Insert factual or multi-choice questions to clarify behavior, as this is used to distinguish between what the respondents are doing to what they are feeling. An example is “Which feature do you use most often”  (a) Chat (b) File upload (c) Analytical dashboard. This is to contextualize responses to the Likert scale attitude.
4. Incorporate ranking questions to prioritize feedback as this lets respondents rank features, problems, or their preference. Combining this with Likert feedback reveals both sentiment and prioritization.

Examples of hybrid question strategies

• “Rate your satisfaction with our product”. This is a likert scale type of question that is used to measure satisfaction. It can be said to be a hybrid question.

• “What influenced your satisfaction score?” 

• “Which product do you use most often?”. This is a multi-choice question that is used to clarify the usage pattern of a respondent. It can be said to be hybrid.

• “Rank the features you’d like improved.”

Building balanced surveys for better insights

• Mix question types to avoid monotony and capture multiple dimensions of data.
• Group related questions together (e.g., satisfaction + reasons + usage).
• Limit the number of Likert questions to 5 to 7 per section.
• Ensure that there is clarity in scales and question phrasing to reduce confusion.

Preventing Survey Fatigue

• Keep surveys concise, there should be no more than 10 to 15 questions if possible.
• Use progress indicators so respondents know how far along they are.
• Use alternate formats (e.g., Likert → multiple choice → open-ended) to maintain engagement.
• Make open-ended questions optional if they are not critical

Tips for Writing Effective Likert-Scale Questions

• Use neutral language to avoid influencing responses.
• Balance your scale (equal positive or negative options).
• Avoid double-barreled statements, e.g., “The app is fast and easy to use.” Break it into two separate questions.

Likert Scales in Form-Building Tools (like Google Form)

Modern form builders simplify the process:

• Drag and drop Likert items into your form.
• Customize a number of points, label wording, and visual style.
• Some tools offer pre-built templates for satisfaction surveys, NPS, and employee feedback.

Real-life example:
“Rate your agreement: ‘I trust the brand behind this product.’”
This question can be stylized with brand colors and aligned with customer journey stages.

Conclusion: 

We have learned the importance of Choosing the Right Question Type for Smarter Surveys.

No single question type fits every purpose. By understanding when and how to use tools like Likert scales with other formats, you can easily build surveys that are not only more enjoyable to take but also deliver better and more accurate insights for smarter decision-making.