What is a Likert scale?

Likert scales are a structured way for researchers to gather diverse opinions and attitudes. They allow respondents to express agreement, disagreement or neutrality concerning statements or questions.

Named after Rensis Likert, these scales are widely used in disciplines such as psychology, sociology and market research to quantify qualitative data effectively.

Let’s explore what makes up a Likert question, including examples, when you should use Likert scales and how you can use them in your surveys.

To understand the Likert rating scale, you first need to understand what a survey scale is.

A survey scale represents a set of answer options (either numeric or verbal) that cover a range of opinions on a topic. It’s always part of a closed-ended question (a question that presents respondents with pre-populated answer choices).

A Likert scale is a rating scale used to measure survey participants’ opinions, attitudes, motivations and more. It uses a range of answer options ranging from one extreme attitude to another, sometimes including a moderate or neutral option. However, four- to seven-point scales are the most popular.

So what is a Likert scale survey question? Instead of asking a yes/no question, such as “Do you like our product?”, respondents rate their attitudes on a scale ranging from “don’t like it at all” to “like it a lot”. 

Using Likert scales, researchers and practitioners can effectively quantify and capture the complexity of individual opinions, psychology and attitudes. For instance, someone who “likes the product but is not crazy about it” would probably give a Likert rating of “somewhat like it”.

Likert scales (named after their creator, American social scientist Rensis Likert) are quite popular because they are one of the most reliable ways to measure opinions, perceptions and behaviours.

Likert scales are easy to design and can be used for various topics and quantitative surveys.

Compared to binary questions, which only give you two answer options, Likert-type questions will give you more granular feedback about whether your product was just “good enough” or (hopefully) “excellent”. 

This method will let you uncover degrees of opinion that could make a real difference in understanding the feedback you’re getting. It can also pinpoint areas where you might want to improve your customer or employee experience.

Using the same Likert scales in longitudinal or recurring surveys can also track seasonal changes in customer attitudes. For example, you can send a quarterly survey to assess customer loyalty to your brand. With those data, you can see the quarterly and yearly changes in customer loyalty. This will help you understand your current and past brand health and, most importantly, predict how it may trend.

Likert scale surveys can come in many forms. Here are a few of the most commonly used question types.

Likelihood: How likely a respondent is to take a particular action, such as signing up for a membership or purchasing a product. These questions are good if you’re trying to determine how likely someone is to do something instead of just how much they like the idea of something. 

Satisfaction: How satisfied are your customers with something your company offers or does? Asking satisfaction questions is a great way to work that out. 

Importance: To gauge how strongly people feel about a certain service, product or experience, you can ask a Likert scale question that measures how important something is to a customer. 

Likert scales are very flexible rating scales and you can adjust the scale points easily to suit your survey design. Some of the common ones are four-point, five-point, seven-point and 10-point scales.

The four-point Likert scale does not usually provide the midpoint or neutral points of the scale. This is typically used to make sure that respondents provide an attitude. An example of a four-point Likert scale could look like this:

How satisfied or dissatisfied are you with the speed of product delivery?

The five-point Likert scale uses five answer options, including a midpoint or neutral option, to assess a respondent’s opinions. A typical five-point Likert scale example looks like this: 

How easy or difficult is it to sign up for our mobile app?

The six-point Likert scale is similar to a four-point one but offers more options to respondents. The following example demonstrates what a six-point Likert scale may look like: 

How important or unimportant is using social media to you?

The seven-point Likert scale offers more response options to your survey-takers in order to get a more nuanced data set. A sample seven-point Likert scale survey could look like this: 

How much do you agree or disagree that the company helps its employees develop their careers?  

The 10-point Likert scale provides 10 choices to survey respondents, allowing you to obtain data with more granularity and precision. The following is an example of a 10-point scale:

How important or unimportant is it for you to talk about your career development regularly with your manager?

The Net Promoter® Score (NPS) is a famous Likert scale question commonly used to measure customer satisfaction and brand loyalty. It uses an 11-point Likert scale from 0 to 10. The NPS survey question differs from other scales as it uses a numerical scale rather than verbal descriptors.

Frequency is a common measurement for Likert scales in quantitative surveys. It is used for collecting the self-reported frequency of a behaviour, such as using or purchasing your product, or engaging in team-building activities, etc. Here’s an example of a frequency Likert scale:

In general, how often do you shop in our store?

Yes, a Likert scale is ordinal. The intervals between the values that your respondents can choose are not truly equal and therefore can’t be considered a set of quantitative intervals.

Likert scales capture attitudes or opinions more precisely than binary questions. For example, customers who “like the product but are not crazy about it” can give either a “yes” or “no” answer to the binary question of “Do you like our product?”, making it almost impossible to understand the degree of preference for the product.

Likert scale questions, on the other hand, improve survey data quality by allowing more accurate and nuanced answers from survey-takers.

It’s important to keep each series of questions in your survey focused on the same topic. In the end, this will help you obtain more accurate results. Why? Because when the time comes for you to report the data, you want to analyse a score that summarises the results from a few questions.

For example, you could ask this initial question:

And follow up with:

But here’s one question you should leave for another section of the survey:

Grouping questions about one topic together and adding up their responses to get a score (a “Quality-of-Food” score, in this case) will give you a more reliable measurement of attitudes towards the particular product, service or event you’re researching.

Likert scales are easier for survey-takers to understand and respond to than open-ended, ranking or multiple-choice questions. Therefore, respondents are less likely to experience survey fatigue and become frustrated during the survey-taking process. They will have a positive survey experience and be willing to provide their feedback again in your future surveys.

Likert scales will provide you with insights into how your customers, employees or target market think about your product, company or service, but they do not tell you exactly why they hold these opinions. For example, by using Likert scales, you may find out that your customers are not satisfied with your mobile app, but the scales don’t suggest how to change your mobile app to improve customer satisfaction.

Carefully planning the survey design will help address the “why”. For example, after you’ve asked participants to rate their satisfaction on Likert scales, follow up with a multiple choice or open-ended question enquiring about their reasons for awarding those particular ratings. Combining Likert scales with follow-up questions will give you a full picture of customer insights.

The interpretation of Likert scale points can vary between respondents. Individuals also think of the extremity of their opinions and attitudes differently. One person’s “strongly agree” might be another’s “somewhat agree”.

To mitigate the potential subjectivity issue, researchers or practitioners must make sure they choose Likert scales with the right number of scale points. More scale points could mean more nuances in data and insights, but having too many scale points also increases potential ambiguity between answer options.

In some survey topics, survey-takers may intentionally choose the neutral point in Likert scales to avoid being perceived as having extreme views. For example, suppose a customer is rating different aspects of your product, service or business on a 1–10 Likert scale. In that case, most of the answers will fall in the centre (4–7), with only a few being rated highly (8–10) or lower (1–3).

Ensuring that respondents know the survey is anonymous can help. Knowing when to introduce a neutral or midpoint option is also crucial and this depends on the specific question being asked.

For instance, this structure recognises the possibility that individuals may genuinely feel neutral about the experience:

Would you say that the experience had a positive or negative impact?

Net Promoter Score is a highly regarded loyalty metric that companies use to collect customer feedback. An NPS survey is simple to create. It asks respondents to rate the question “How likely is it that you would recommend this company to a friend or colleague?” on a 0–10 Likert scale.

The answers that customers provide are classified as follows:

Related reading: Everything you need to know about the NPS® survey question

A Customer Satisfaction Score (CSAT score) measures customer satisfaction with your products, services or business. Typically, CSAT surveys ask customers about their satisfaction levels on a Likert scale. Below is an example of a customer satisfaction Likert-type scale on “satisfaction”:

How satisfied or dissatisfied are you with the speed of checking out on our website?

Related reading: Customer satisfaction surveys: Examples and tips for getting started

Similar to NPS, the employee Net Promoter Score measures employees’ sentiment and loyalty towards the employer. Employees are asked a single question: “On a scale of 0 to 10, how likely is it that you would recommend working at this company to a friend or colleague?”

Similarly, employees’ answers can be classified as follows:

Related reading: What is the employee Net Promoter® Score?

An employee engagement survey measures how committed employees are to the mission and goals of your company. Insights from the survey can indicate the health of the business. You can stay informed about how employees feel about life at your company by using Likert scale surveys. This could cover various factors, such as employee training, career development or new policies, etc.

How satisfied or dissatisfied are you with the training opportunities provided by our company?

Related reading: Enhancing the employee lifecycle: strategies and insights for EX success

After an event, you can use Likert scales to gather feedback from your attendees in order to evaluate the success of the event. Regardless of whether the event is in person or online, you can use event feedback surveys to understand participants’ overall experience and their sentiments about different aspects of the event. For example:

How helpful or unhelpful was the event in terms of connecting you with people who have similar interests?

Related reading: The ultimate guide to event surveys

Learning how easy to use and enjoyable your prospects and customers find your website is a great reason to create a survey. You need to make sure you’re presenting your company and products in the best way possible and providing a great user experience. A Likert scale survey question to gather website feedback from your site visitors could look like this: 

How likely or unlikely is it that you will return to our website to find information? 

Knowing more about your customers and their habits is always helpful. It is vital for your marketing and product teams so they can tailor ads and new items to exactly what your customers want. Asking them Likert survey questions can help give you a deeper understanding of their opinions and preferences. A survey question to gather opinions from your customers might look like this: 

How important or unimportant to you is attractive packaging? 

As we mentioned above, Likert scales are flexible. You don’t have to use a fixed survey design. Instead, you can determine how many scale points to use in your survey. 

There are many factors to consider when making a decision. Likert scales with fewer scale points are easier for respondents to read and process but will not provide as many details and nuances. 

Likert scales with more scale points give you more detailed data, but you will sacrifice some response time. They can make your respondents feel fatigued fast. They worsen the subjective interpretation of scale points, too.

You will also need to decide whether to use an odd-numbered or even-numbered scale. If ensuring that survey-takers provide attitudes is important to your project, then you may consider taking out the midpoint or the neutral point of the Likert scale and use an even-numbered one.

Ultimately, you will need to consider your research priorities and weigh up the factors accordingly.

To maximise their effectiveness, Likert-type questions need to be phrased just right. 

For instance, when asking about satisfaction with restaurant service, it’s crucial to specify which aspect of service is being referred to: service from the front of house staff, the waiting staff or the maître d’. You also need to be clear about the aspects of service that you want to evaluate, such as the quality of food and drinks, the courtesy of the staff or the speed of service.

Being more specific in Likert scales will give you more valuable responses.

When crafting Likert scales, make sure respondents understand your intent clearly. Use descriptive words in response options to avoid confusion about relative rankings. 

This approach helps respondents navigate the scale effectively.

Bipolar constructs are those where attitudes can fall on one side or the other of a midpoint that itself is true ambivalence or neutrality. Unipolar constructs are those that lend themselves strictly to an amount and don’t have a neutral midpoint: there is either the maximum amount of the attitude or none of it. 

For instance, let’s suppose I asked you to rate how helpful this article is. It may fall between being the most helpful article you’ve ever read and not helpful at all. From there, we can safely assume there is something in between, such as “sort of” helpful. This is an example of a unipolar construct.

Statements pose a risk: most people tend to agree rather than disagree. This is because survey respondents tend to select positive response options more frequently (known as agreement or acquiescence response bias). Therefore, asking a question is more effective than making a statement.

Once you’ve created your Likert scale survey, most of your hard work is done! However, you still need to analyse the data you receive from the survey responses to measure your performance in your survey target area. 

Since Likert scales are ordinal scales, Likert scale analysis is best summarised using a median or a mode. Means/averages are not always useful. 

When analysing Likert scale data, you need to look at the distribution of responses across scale points or categories. You can summarise the percentages of each response category and then visualise the results using bar graphs. 

Depending on the goal of your project, you can also merge Likert scale points into simpler categories. For example, let’s suppose you gathered customer satisfaction on a five-point Likert scale ranging from “not at all satisfied” to “highly satisfied”. In that case, you may want to find out the total number of respondents who gave a “somewhat satisfied” or “highly satisfied” answer. This will tell your team the total number or percentage of people with a positive sentiment. The treatment of NPS data is also an example of categorising scale points.

Remember when analysing your Likert survey data that despite it being a very accurate way of gathering data, it’s still susceptible to social desirability bias. This makes it likely that people will give answers they feel are socially acceptable instead of being honest, especially with difficult questions. They may choose to answer as undecided or use neutral options instead of revealing their true opinions.

By now, you must be an expert at using Likert scales. Here are six tips to help you become even more proficient:

Customising a Likert rating scale in your next survey will give you the best-possible insights. Learn more about SurveyMonkey plans or create a free account.

Net Promoter, Net Promoter Score and NPS are trademarks of Satmetrix Systems, Inc., Bain & Company, Inc. and Fred Reichheld.