Understanding Likert Scales: Definition, Examples, and Best Practices

Questionnaires are a great way to gather and understand people's experiences, feelings, and ideas regarding their job satisfaction, product/service satisfaction, and other relevant topics.

To quantify such opinions, researchers often use the Likert scale. This scale was designed to let respondents rate their level of agreement, for example, from "strongly disagree" to "strongly agree" with a given statement. 

Used in everything from customer satisfaction questionnaires to employee satisfaction and market research surveys, Likert scales can indicate varying degrees of agreement, disagreement, satisfaction, or preference. As a result, researchers obtain more nuanced and valuable data.

In this guide, you'll learn about Likert scale's meaning, its use in real-life scenarios, and how to write good, effective questions that prompt respondents to choose a response from a predefined scale. You will also learn how to work through responses, how to take raw opinions, and transform them into data for better decision-making.

What is a Likert scale?

This scale, named after the American psychologist Rensis Likert, is a common way to measure people's attitudes or opinions on a questionnaire. The scale usually presents a range of answers (choices) reflecting varying levels of agreement or disagreement with a statement. This statement can be presented either as a direct question or as a declarative sentence (more often).

Let's say a question was: "I am satisfied with the customer service."

Respondents then select an option along a scale such as: Strongly disagree, Disagree, Neutral, Agree, and Strongly agree.

The Likert scale not only enables researchers to know if people like or dislike something, but also how much they like or dislike it. This scale enables the quantification of opinions, facilitates trend analysis, allows comparison between groups, and informs decision-making based on facts.

When should you use a Likert scale?

Likert scales are very effective in most types of surveys because they capture subtle opinions. Use a Likert scale when:

• You are going to be measuring sentiment or attitude (how customers feel towards your product or service).
• You are going to be comparing groups (comparing satisfaction between new and returning customers).
• You require responses beyond yes or no (Likert scales allow nuances of opinion, ranging from strong agreement to strong disagreement).
• You want to get data that is easy to analyze (because Likert scales result in formatted answers, it's simpler to summarize and compare answers).

Timing and circumstances

• After an encounter or experience: For instance, immediately after a customer service call or after purchasing, to gauge satisfaction.
• During planned follow-up: Such as quarterly employee attitude tests or ongoing customer satisfaction tracking.
• While tracking change over time: Likert scales help measure changes in opinion or attitude between consecutive waves of surveys.
• Before & after change: To observe the impact a change in product feature or policy has on user attitudes.

Best practices 

1. Employ straightforward, plain statements that are easy to understand for respondents.
2. Do not employ double negatives or ambiguity. (Instead of saying "I don't disagree that the product isn't effective," say "The product is effective.")
3. Choose an adequate number of response options based on your need (more described in the examples section).
4. Ensure your scale is balanced and has an equal number of positive and negative ones.
5. Apply Likert scales when you want quantitative opinion data, but not when you require rich accounts or stories.

Top 10 Likert scale question examples

Likert scales also come in various forms depending on the number of response options given. The choice of form depends on what kind of feedback you're trying to capture and how complex you want that answer to be.

Before giving examples, let's first describe where exactly these types of questions are used most extensively. 

In commercial settings, two of the most widely used survey formats that use Likert-type questions are Customer Satisfaction Score (CSAT) and the Net Promoter Score (NPS) surveys.

CSAT surveys typically measure how satisfied a customer is with an experience, service, or product. NPS surveys measure customer loyalty by asking how likely they would be to suggest your company or product to others.

In most cases, both CSAT and NPS rely on Likert-type scales to transform subjective opinions into structured, actionable data. 

So, what are the main different Likert scale formats, why are they used, and what questions suit each best?

The format of Likert scales is flexible. The number of points (generally 4, 5, or 7) determines the degree of detail that the respondent can provide.

• A 5-point scale has a middle option that is neutral, providing the respondent with a "no opinion" or "neutral" option. This is the most widely used scale.
• A 4-point scale usually forces people to take sides, with no middle choice. Suitable if you want to have clear-cut opinions.
• A 7-point scale provides greater subtlety, enabling slight differences of opinion.

Each type of scale may be more appropriate depending on the context. For example, market research, healthcare, or psychology studies may require different levels of detail or sensitivity.

In the next section, we'll explore examples of how each scale can be applied in different cases.

5-point Likert scale examples

This format is widely used in CSAT and NPS surveys because it balances simplicity and depth. Respondents can express satisfaction levels or agreement clearly without feeling overwhelmed. 

Let's look at an example to better understand what the Likert scale is in action.

CSAT: "How satisfied are you with our service?"

• Very dissatisfied
• Somewhat dissatisfied
• Neutral
• Somewhat satisfied
• Very satisfied

NPS follow-up: "I would recommend this product to others."

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

By the way, the 5-point Likert scale was the initial version of this scale, and it reaches respondents more easily without losing valid data.

4-point Likert scale examples

Сhoose these scales when you do not want to allow neutral responses and require the respondent to make a choice between agreement and disagreement:

Example: "The website is easy to use."

• Strongly disagree
• Disagree
• Agree
• Strongly agree

Example: "How would you rate the training session?"

• Poor
• Fair
• Good
• Excellent

7-point Likert scale examples

These are best employed where there is a need for greater detail of feedback and research that must be sensitive.

Example: "How much do you agree with the following statement: 'The product quality meets my expectations.'"

• Strongly disagree
• Disagree
• Somewhat disagree
• Neither agree nor disagree
• Somewhat agree
• Agree
• Strongly agree

Likert scale examples for psychology

In psychology, a Likert-type scale tends to measure attitudes, personality traits, or behavior. 

For instance: "I often feel anxious in social situations."

• Never
• Rarely
• Sometimes
• Often
• Always

Another example: "I enjoy trying new activities."

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

These scales allow researchers to quantify feelings and traits that are difficult to measure directly.

Other Likert scale question examples

Not only are Likert scales employed in politics and public opinion polls, but also in education, healthcare surveys, employee satisfaction surveys, and market research questionnaires. 

• Education: "The course content was simple and easy to read."
• Healthcare: "I am confident in taking care of myself after this consultation."
• Employee engagement: "I feel appreciated at work."

The flexibility of Likert scales comes in handy in many business fields.

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5 pros and cons of Likert scales

As with any questionnaire tool, Likert scales have both strengths and limitations. 

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According to a 2025 study on ResearchGate, Likert scales remain one of the most popular ways to measure attitudes and opinions in 2025. Still, researchers need to use advanced methods like distinguishing data types, providing context for results, and others. Some of the best tips to write effective Likert scale questions will be discussed in the next section.

Despite all the benefits, there are specific situations where Likert scales may not be the best choice at all.

When not to use Likert scales:

• When you need specific, qualitative information.
• When questions demand facts or yes/no answers.
• When your respondents find it hard to distinguish between near scale points.

Responses gained through the use of a Likert scale questionnaire might sometimes be subject to biases such as central tendency bias. This means the majority of respondents prefer picking the middle answer over an extreme alternative. As mentioned above, 4-point Likert scales can help you prevent this.

Despite these restrictions, Likert scales are nonetheless an effective survey technique when used thoughtfully and interpreted wisely. 

With knowledge of both their pros and cons, you will be able to choose the most appropriate method and gain the most accurate, relevant data.

How to write great Likert scale questions

Writing effective questions is essential to collect useful and valid information. Poorly phrased questions can confuse respondents and yield inaccurate results. 

Make questions simple

Avoid using jargon, large words, or technical terms. Everyone responding to you has to understand the question easily without further explanation.

• Bad: "Our omnichannel support solutions are in line with your expectations."
• Good: "I am satisfied with the help I got."

Ask one thing at a time

There must be one idea per question. Double-barreled questions confuse the respondents.

• Bad: "The product is easy to use and affordable."
• Good: "The product is easy to use."

Use consistent scales

There must be the same number of options and the same type of wording throughout the survey. It is more convenient for respondents and data analysis.

Example: Use the same response labels every time on a 5-point scale (Strongly disagree → Strongly agree).

Offer a balanced set of answers

Make sure your scale offers a range of positive and negative alternatives, and optionally a neutral one. 

This is a standard Likert scale example of responses that works well in most cases:

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

Use the right scale for the question type

Choose the number of points (4, 5, 7) based on how much you need to know. 

Use 4-point scales to force a choice, 5-point scales are better for gathering general feedback, and 7-point scales work best when you require more sensitivity.

Avoid leading or biased questions

Make questions neutral so they won't bias the respondent to one specific response.

• Worse: "How wonderful was our new customer portal?"
• Better: "How satisfied are you with the new customer portal?"

Great Likert scale questions enable you to get honest, consistent answers that reflect what your audience truly thinks.

How to analyze Likert scale data

To get real value out of your Likert scale rating, you also need to interpret the results correctly.

Likert scale responses give you structured, ordered data, but turning that data into insights takes a few simple steps.

1. Numerically code each response

Prior to analysis, convert response options to numbers. This makes it easier to calculate averages, totals, or create charts.

2. Summarize the responses

Start by looking at how many respondents answered each question. You can calculate frequencies (how many respondents answered each option), percentages (what proportion of respondents answered each option), and mean scores (the average score per question). This way, you can easily see overall trends.

3. Visualize the data

Charts render data from Likert scales easier to analyze. Try:

• Bar charts to compare answers between questions
• Stacked bar charts to show positive vs. negative answers
• Heatmaps to compare answers between many questions or groups

All these charts are very useful when reporting to stakeholders or clients.

4. Compare groups or time periods

Want more insights? Compare answers between respondents' groups and detect patterns over time. This is especially useful when analyzing Voice of the Customer questions, when you want to understand how different segments view your product or service.

For example, you can compare: 

• New customers vs. repeat customers
• Different age groups
• Answers pre- and post-product change

5. Don't just look at the numbers

Although Likert data is numerical, there is always context that counts. For example, if there are many users who "Agree" but few who "Strongly agree," it may show growth potential.

And take note of how many users selected Neutral. It may mean they don't know, don't care, or didn't understand the question, so wording your question clearly is key.

Also, be aware that most information gathered with the Likert scale is ordinal, not interval and take care when doing more sophisticated statistical testing like t-tests or correlations. If you are unsure about how to manage your data, turn to a data analyst.

Final thoughts

Now you understand what a Likert scale is, and how it's effective in measuring opinions, attitudes, and satisfaction. These scales are often used to collect employee and customer feedback, as well as in marketing research. They help understand how strongly a person agrees or disagrees with something – from "strongly disagree" to "strongly agree."

By formulating statements clearly and providing balanced response Likert scale options, you'll transform subjective opinions into structured data.

But the real value lies not just in collecting responses, but in how you use them. And that's where choosing the right survey platform comes in.

Want to use Likert scales in your business? Try Checkbox to make smart, professional-quality surveys with a Likert scale template, built-in analysis tools, and full customization to meet your goals. Start your free trial today!

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