Learn about one of the most reliable ways to measure opinions, perceptions, and behaviors and how you can use it in your next survey.

Have you ever answered a question that asked you how much you agree or disagree with something?

That kind of question is known as a Likert scale. Likert scales are widely used to measure attitudes and opinions with a greater degree of nuance than a simple “yes/no” question.

Let’s explore what makes up a Likert question, find examples, understand when you should use this tool, and see how you can put it to work for your surveys.

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

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).

So what is a Likert scale survey question? It’s a question that uses a 5 or 7-point scale, sometimes referred to as a satisfaction scale, that ranges from one extreme attitude to another. Typically, the Likert survey question includes a moderate or neutral option in its scale.

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 behaviors.

Compared to binary questions, which give you only two answer options, Likert-type questions will get you more granular feedback about whether your product was just “good enough” or (hopefully) “excellent.” And Likert questions can help you decide whether a recent company outing left employees feeling “very satisfied,” “somewhat dissatisfied,” or maybe just neutral.

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

in-article-cta

Get opinions from the market with our online survey panel

Likert scale ratings are structured to provide quantifiable answer options that make analyzing data easier. Respondents also have a range of answers that are more specific to how they feel about a product or service.

One great thing about the Likert scale is that it can help you avoid some of the common pitfalls of survey design, like creating overly broad questions that respondents may find too hard to think about. This could lead them to get frustrated and start answering too quickly–spoiling the quality of your data.

Survey designers who are in a bit of a hurry sometimes reach for the broader types of questions–like “yes/no,” “select all,” open-ended, ranking, or matrix questions–as a sort of survey shortcut.

As a rule of thumb, though, in most of these scenarios they should trust their old friend the Likert scale, which will keep the respondent focused and happy with its simple, direct language.

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

For example, you could ask this initial question:

How satisfied or dissatisfied are you with the quality of the dinner you were served tonight?

And then follow up with:

How satisfied or dissatisfied are you with the quality of your appetizers tonight?

How satisfied or dissatisfied are you with the quality of the main course tonight?

How satisfied or dissatisfied are you with the quality of dessert tonight?

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

How satisfied or dissatisfied are you with service at the coat-check room tonight?

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

Likert scale questions are used in many different types of surveys, whether you are trying to find out how your employees feel about their work or what your customers think about your latest product.

A typical customer satisfaction survey uses an ordinal scale that allows users to rank their opinions. For example, a 5-point Likert scale asks customers to specify their levels of agreement with a statement, from high to low with one neutral option in the middle.

Likert scale responses for customer service are very flexible and can be used to measure a variety of sentiments; from agreement, to satisfaction, frequency, and desirability. For example, you might be interested in how often customers use your online help portal, in which case a frequency response (ie: Never, Rarely, Sometimes, Often, Frequently) would be useful. Below is an example of a customer service Likert-type scale on “satisfaction”:

Overall, how satisfied or dissatisfied are you with our company?

  • Very satisfied
  • Somewhat satisfied
  • Neither satisfied nor dissatisfied
  • Somewhat dissatisfied
  • Very dissatisfied

Likert scale responses can also be a useful tool for checking in with employees. By adapting the same 5-point Likert scale to employee issues, companies can keep tabs on employee engagement and sentiment. For example, companies can find out how aware employees are about resources, how familiar they are with IT policies, or how often they may use or take advantage of new tools. Likert scale responses also help companies uncover a central tendency, or and gauge the levels of agreement that the average employee thinks about a given issue. Here’s an example:

I’m satisfied with the investment my organization makes in education:

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

Marketers or event professionals can use a 5-point Likert scale to collect valuable feedback on the success of their events. A post-event survey can use a variety of Likert scale responses to evaluate the overall event experience, or probe on different parts of the event such as the probability of the participant to attend again, or the importance of location. For example, here’s a Likert scale question about the value of event content:

How helpful was the content presented at the professional event?

  • Extremely helpful
  • Very helpful
  • Somewhat helpful
  • Not so helpful
  • Not at all helpful

Since there are so many kinds of survey questions, how do you know when you should use Likert questions?

Likert scales are great for digging down deep into one specific topic to find out (in greater detail) what people think about it. So, think of using Likert survey questions any time you need to find out more about…

  • How people are reacting to your new product
  • What your team thinks about a recent development in the office
  • How your clients feel about customer service at your company
  • How successful your public event was with attendees

…or any other questions where you need to measure sentiment about something specific and you want a deeper level of detail in your responses.

If you want to get a bit geeky about it, the deeper level of detail is what survey experts call variance. The more variance you have, the better you know the nuances of someone’s thinking.

in-article-cta

SurveyMonkey Genius helps you quickly build surveys with more confidence—just choose an answer type to automatically add a set of prewritten answer choices to your question.

Likert-type questions must be phrased correctly in order to avoid confusion and increase their effectiveness. If you ask about satisfaction with the service at a restaurant, do you mean the service from valets, the waiters, or the host? All of the above? Are you asking whether the customer was satisfied with the speed of service, the courteousness of the attendants, or the quality of the food and drinks? Bottom line: If you can get more specific, there’s a higher chance that your Likert questions will deliver more valuable responses.

When you’re using words to ask about concepts in your survey, you need to be sure people will understand exactly what you mean. Your response options need to include descriptive words that are easily understandable. There should be no confusion about which grade is higher or bigger than the next: Is “pretty much” more than “quite a bit”? It’s advisable to start from the extremes (“extremely,” “not at all”,) set the midpoint of your scale to represent moderation (“moderately,”) or neutrality (“neither agree nor disagree,”) and then use very clear terms–“very,” “slightly”–for the rest of the options.

Do you want a question where attitudes can fall on two sides of neutrality–“love” vs. “hate”– or one where the range of possible answers goes from “none” to the maximum? The latter, a unipolar scale, is preferable in most cases. For example, it’s better to use a scale that ranges from “extremely brave” to “not at all brave,” rather than a scale that ranges from “extremely brave” to “extremely shy.” Unipolar scales are just easier for people to think about, and you can be sure that one end is the exact opposite of the other, which makes it methodologically more sound as well.

Statements carry an implicit risk: Most people will tend to agree rather than disagree with them because humans are mostly nice and respectful. (This phenomenon is called acquiescence response bias.) It’s more effective, then, to ask a question than to make a statement.

  1. Keep it labeled. Numbered scales that only use numbers instead of words as response options may give survey respondents trouble, since they might not know which end of the range is positive or negative.
  2. Keep it odd. Scales with an odd number of values will have a midpoint. How many options should you give people? Respondents have difficulty defining their point of view on a scale greater than seven. If you provide more than seven response choices, people are likely to start picking an answer randomly, which can make your data meaningless. Our methodologists recommend five scale points for a unipolar scale, and seven scale points if you need to use a bipolar scale.
  3. Keep it continuous. Response options in a scale should be equally spaced from each other. This can be tricky when using word labels instead of numbers, so make sure you know what your words mean.
  4. Keep it inclusive. Scales should span the entire range of responses. If a question asks how quick your waiter was and the answers range from “extremely quick” to “moderately quick,” respondents who think the waiter was slow won’t know what answer to choose.
  5. Keep it logical. Add skip logic to save your survey takers some time. For example, let’s say you want to ask how much your patron enjoyed your restaurant, but you only want more details if they were unhappy with something. Use question logic so that only those who are unhappy skip to a question asking for improvement suggestions.

You have probably known Likert-scale questions for a long time, even if you didn’t know their unique name. Now you also know how to create effective ones that can bring a greater degree of nuance to the key questions in your surveys.

Get the best possible insights by customizing a Likert rating scale in your next survey. With SurveyMonkey, you can subscribe to a tier that’s budget-friendly. Sign up today.

Toolkits directory

Discover our toolkits, designed to help you leverage feedback in your role or industry.

Learn how Chime invests in brand insights

Learn how Chime uses SurveyMonkey to land critical brand partnerships and drive growth across the organization.

SurveyMonkey gives back for Week of Service 2023

Solutions for your role

SurveyMonkey can help you do your job better. Discover how to make a bigger impact with winning strategies, products, experiences, and more.

Use SurveyMonkey's survey templates and get the feedback you need.
https://www.surveymonkey.com/mp/likert-scale/?ut_source=mp&ut_source2=employee-pulse-surveys&ut_source3=inline
www.surveymonkey.com
CC-MAIN-2023-50
569499
application/http; msgtype=response
sha1:664VPECYYNAQKM5U3TFWU772YWK3WPYJ
<urn:uuid:3397ae71-dbcb-4e53-a903-20b3dca94d50>
2023-11-30T12:12:23Z
18.160.10.2
text/html
sha1:V2CEKTSLHH5FYCPOYUVSXGORWKTJGWP4
<urn:uuid:a1fd776a-dbd4-4e65-a595-be0ce32733fd>
https://www.surveymonkey.com/mp/likert-scale/?ut_source=mp&ut_source2=employee-pulse-surveys&ut_source3=inline
response
<urn:uuid:ff91e503-8fd3-4a23-9227-cae8c72ff835>
isPartOf: CC-MAIN-2023-50
publisher: Common Crawl
description: Wide crawl of the web for November/December 2023
operator: Common Crawl Admin (info@commoncrawl.org)
hostname: ip-10-67-67-94
software: Apache Nutch 1.19 (modified, https://github.com/commoncrawl/nutch/)
robots: checked via crawler-commons 1.5-SNAPSHOT (https://github.com/crawler-commons/crawler-commons)
format: WARC File Format 1.1
conformsTo: https://iipc.github.io/warc-specifications/specifications/warc-format/warc-1.1/