Likert scale: Meaning, Questions, Examples & More [2025]

Great! You’re interested in creating a survey using the Likert scale.

You’ve nailed your product, your website is converting, and your customers are raving fans. But how do you quantify that customer love? Enter the Likert scale, SurveySlack. This simple yet powerful tool lets you measure attitudes and opinions, giving you data-driven insights to take your business to the next level. Whether you’re a seasoned marketer or just starting out, understanding the Likert scale is essential for success.

Let’s break down what a Likert scale is, how to use it, what are likert scale examples, and why it’s so valuable. You’ll be decoding insights like a pro in no time.

Table of content

• What is a Likert scale?
• Why are Likert scales important?
• What are the limitations of Likert scales?
• How to Create a Likert Scale Survey?
• What are Likert scale questions and examples?
• What to do with your Likert scale results?

What is a Likert Scale Definition?

A Likert scale is a five-point or seven-point question. Social psychologist Rensis Likert developed it in 1932. It allows survey makers to measure people’s opinions and levels of agreement. 

Likert scales are a way to scale attitudes. They let respondents show agreement, disagreement, or neutrality. 

They are widely used in fields like psychology, sociology, and market research. They use numbers to measure non-numeric data well.

Likert scales are a good way to measure customer sentiment. They cover attitudes, opinions, and perceptions. These affect how much a customer likes a product or service.

A Statista study, says Likert scales usually consist of 5, 7, or 11 attributes.

They are crucial for understanding customer sentiment. Surveys are them to gauge opinions and attitudes.

Also, Read:

• The Future of Branding is Here: The Ultimate Guide to Branded Surveys

Why are Likert Scales Important?

Likert scales are important because they are one of the most reliable ways to measure opinions, perceptions, and behaviors. They are easy to design and can be used for a variety of topics and surveys.

Likert scales allow researchers to collect more detailed information about a topic than binary questions (questions that have only two answers). For example, a binary question might ask, “Do you like our product?”. A Likert scale question might ask, “How much do you like our product?” with answer choices ranging from “not at all” to “a lot”.

Using the same Likert scales in recurring surveys allows researchers to track changes in attitudes over time. For Likert scale examples, you could send a quarterly survey to assess customer loyalty to your brand and compare the results to see how customer loyalty has changed from quarter to quarter.

What are the Limitations of Likert Scales?

While Likert scales are useful for measuring opinions and attitudes, they have some limitations. The fixed nature of response options may not capture the full complexity of attitudes or feelings.

Also, individuals may interpret the scale points differently. For Likert scale examples, what one person considers “agree” another might consider “strongly agree“.

Additionally, the interval between scale points is not always equal, making statistical analysis less reliable.

Here are some other limitations to consider:

• Central Tendency Bias: Respondents may avoid expressing extreme opinions and choose neutral or middle options.

• Social Desirability Bias: Individuals may not respond truthfully to present themselves in a positive light. For example, survey respondents may lean toward more socially acceptable answers when asked difficult questions, especially if they know they can be identified. They may also opt for undecided or neutral options instead of stating their true preferences.

• Acquiescence Response Bias: Survey takers may tend to select positive response options more often, regardless of the content.

Respondents may fall into a pattern of answering questions in a particular way, especially if the survey is long or switches between topics frequently.

Likert scales do not provide insights into why a respondent feels a certain way. For instance, Likert scales can reveal that customers are dissatisfied with a company’s mobile app, but not what needs to be improved.

To address this, it’s helpful to combine Likert scales with open-ended questions that ask respondents to elaborate on their answers. Researchers can use a variety of techniques to mitigate the impact of these limitations. For example, they can:

• Use clear and concise language in their questions and response options.
• Carefully consider the number of scale points to use.
• Include both positive and negative statements in their surveys.
• Randomize the order of questions.

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• Upgrade Your Surveys Now: Top 10 SurveyMonkey Alternatives for 2024

How to Create a Likert Scale Survey?

Creating a Likert Scale survey involves a systematic process to effectively measure opinions and attitudes. Here’s a breakdown of how to create one:

1. Define your goal: What information are you trying to gather? What do you want to learn from the survey? Having a clear objective will guide the rest of the process.

2. Craft your statements: Respondents will react to these questions or statements. Keep them clear, concise, and focused on your objective.

3. Design the scale: This is the heart of a Likert scale. You’ll present a range of response options. They are usually on a bipolar dimension. This means they go from positive to negative or agree to disagree. Here are some aspects to consider:

• Many choose 5 points: For example, Strongly Agree, Agree, Neutral, Disagree, and Strongly Disagree. Less common is a 7-point scale which can provide more granularity in responses.

• Wording: Use clear and easy-to-understand labels for each point on the scale. Tailor the wording to your specific topic (e.g., Satisfied/Dissatisfied, Likely/Unlikely).

• Neutral midpoint: Decide whether to include a neutral option in the middle. This can be useful if you want to capture indifference or uncertainty.

4. Pilot test: Test your survey with a small group before deploying it. Look for any ambiguities or areas for improvement. Here are some additional tips:

• Maintain consistency: Use the same scale format throughout the survey.

• Avoid double negatives: Phrase your statements clearly to avoid confusion.

• Limit bias: Avoid leading questions that nudge respondents towards a particular answer.

Also, Read:

• SurveyMonkey vs Jotform: Which Survey Tool Should I Use?

What are Likert Scale Questions and Examples?

A Likert scale questionnaire is a popular method used to measure attitudes, opinions, or behaviors. It involves Likert scale questions examples where respondents rate their level of agreement or disagreement with statements on a scale. Common scale question examples include both 5-point and 7-point Likert scales, which vary in the number of response options.

Below are some Likert scale question examples: It will show you when to use them in market research and what insights they can give.

5-Point Likert Scale Question Examples

5-Point Likert scale examples typically include options such as “Strongly Agree,” “Agree,” “Neutral,” “Disagree,” and “Strongly Disagree.” These scales are ideal for gauging a respondent’s opinion or feelings on a topic with a moderate range of choices. Common Likert scale questionnaire items might ask about customer satisfaction, product preferences, or agreement with certain statements.

1. Service Quality:
   • “How would you rate the quality of our service?”
     • 1 – Very Poor
     • 2 – Poor
     • 3 – Average
     • 4 – Good
     • 5 – Excellent
2. Product Satisfaction:
   • “How satisfied are you with your recent purchase?”
     • 1 – Very Dissatisfied
     • 2 – Dissatisfied
     • 3 – Neutral
     • 4 – Satisfied
     • 5 – Very Satisfied
3. Brand Perception:
   • “To what extent do you agree with the statement: ‘This brand is trustworthy’?”
     • 1 – Strongly Disagree
     • 2 – Disagree
     • 3 – Neutral
     • 4 – Agree
     • 5 – Strongly Agree
4. Likelihood to Purchase:
   • “How likely are you to buy from us again?”
     • 1 – Very Unlikely
     • 2 – Unlikely
     • 3 – Neutral
     • 4 – Likely
     • 5 – Very Likely

7 Point Likert Scale Question Examples

On the other hand, 7 Point likert scale examples offer a broader range of responses, allowing for a more nuanced view of respondent opinions. These scales might include options like “Strongly Agree,” “Agree,” “Somewhat Agree,” “Neutral,” “Somewhat Disagree,” “Disagree,” and “Strongly Disagree.” The Likert scale survey can capture subtle differences in attitudes or perceptions, making it more sensitive to variations in responses.

1. Customer Satisfaction:
   • “How satisfied are you with our product?”
     • 1 – Very Dissatisfied
     • 2 – Dissatisfied
     • 3 – Somewhat Dissatisfied
     • 4 – Neutral
     • 5 – Somewhat Satisfied
     • 6 – Satisfied
     • 7 – Very Satisfied
2. Brand Loyalty:
   • “How likely are you to recommend our brand to others?”
     • 1 – Very Unlikely
     • 2 – Unlikely
     • 3 – Somewhat Unlikely
     • 4 – Neutral
     • 5 – Somewhat Likely
     • 6 – Likely
     • 7 – Very Likely
3. Product Quality:
   • “To what extent do you agree with the statement: ‘This product meets my expectations’?”
     • 1 – Strongly Disagree
     • 2 – Disagree
     • 3 – Somewhat Disagree
     • 4 – Neutral
     • 5 – Somewhat Agree
     • 6 – Agree
     • 7 – Strongly Agree
4. Customer Experience:
   • “How would you rate your overall experience with our customer service?”
     • 1 – Very Poor
     • 2 – Poor
     • 3 – Fair
     • 4 – Neutral
     • 5 – Good
     • 6 – Very Good
     • 7 – Excellent

Incorporating 7-point and 5-point likert scale examples into your market research can significantly enhance your understanding of customer attitudes and behaviors. By utilizing these scales effectively, you can gather actionable insights that drive informed decision-making and improve overall business performance.

How to Utilize Your Likert Scale Results?

Likert scale results can be a goldmine of info. But, you need to process them right to get the insights. After collecting data from your Likert scale survey, you can begin analyzing the results to understand respondents’ opinions, attitudes, and perceptions.

Here are a few ways to approach analyzing Likert scale data:

• Understand that a Likert scale represents ordinal data: The response categories are ranked, but the intervals between them are not necessarily equal. For example, in a five-point Likert scale ranging from “strongly disagree” to “strongly agree,” “agree” is ranked higher than “disagree,” but you can’t assume that “agree” is twice as strong as “disagree.”

• Use appropriate descriptive statistics: Because Likert scale data is ordinal, researchers typically use the median or mode as the measure of central tendency rather than the mean. You can also present your results as percentages or frequencies for each response category. For example, you could calculate what percentage of respondents “strongly agree” with a statement.

• Visualize the data: Bar charts are a common way to visualize Likert scale data. Each bar can represent a response category, and the height of the bar corresponds to the frequency or percentage of responses in that category. You could also create a pie chart to illustrate the distribution of responses for a single question. Diverging stacked bar charts can illustrate how responses split based on positive and negative sentiment.

• Consider combining Likert scale points into simpler categories: For instance, if you have a five-point Likert scale, you might combine the “strongly agree” and “agree” categories into a single “agree” category. This can simplify your analysis, but remember that you lose granularity by combining categories.

Consider using inferential statistics to test hypotheses and explore relationships in your data. Depending on whether you treat your Likert-derived data as interval or ordinal, you can use various statistical tests:

• Ordinal data: You might use a chi-square test to determine if there is a relationship between two different variables measured with Likert scales. You could also use Spearman’s correlation to see if there is a correlation between two ordinal variables.

• Interval data: If you treat Likert scale scores as interval data, you could use ANOVA to compare means between groups, or Pearson’s correlation to measure the relationship between two interval variables. However, it is important to explicitly state that you are assuming the data are at the interval level.

• Be aware of respondent biases: Even when carefully designed, Likert scales are prone to certain biases. Social desirability bias, central tendency bias, extreme response bias, and acquiescence response bias are common. Consider these biases when interpreting your data, as they can affect the validity of your results.

By following these steps, you can effectively analyze and interpret your Likert scale data to gain valuable insights into your target audience.

Wrapping Up

The Likert scale is valuable for researchers. It helps gauge opinions and attitudes. It offers a simple way to collect data. It is effective and goes beyond a yes/no response, providing a spectrum of feelings. 

However, it’s important to know the limits. Respondents have a limited understanding of the scale. Also, the data is ordinal. Carefully craft Likert scale questions or likert questionnaires to consider their potential drawbacks. You can use them to gain valuable insights from surveys. 

Don’t forget to explore SurveySlack for easy creation of Likert scales – Get started!

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