What is a Likert scale?
Learn when and how to use Likert scale survey questions
Have you ever taken a survey and “neither agreed nor disagreed” with a question at some point?
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.
What’s the definition of Likert scale?
By definition Likert scales are survey questions that offer a range of answer options — from one extreme attitude to another, like “extremely likely” to “not at all likely.” Typically, they include a moderate or neutral midpoint.
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.” They can help 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.
Likert scale examples
Here are some examples to see how you can use them effectively.
From our Customer Satisfaction Survey Template:
Overall, how satisfied or dissatisfied are you with our company?
– Very satisfied
– Somewhat satisfied
– Neither satisfied nor dissatisfied
– Somewhat dissatisfied
– Very dissatisfied
From our Employee Engagement Survey Template:
I am satisfied with the investment my organization makes in training and education:
– Strongly disagree
– Neutral/Neither agree nor disagree
– Strongly agree
From our Professional Event Feedback Template:
How helpful was the content presented at the professional event?
– Extremely helpful
– Very helpful
– Somewhat helpful
– Not so helpful
– Not at all helpful
When to use a Likert scale questionnaire
Since there are so many kinds of survey questions, how do you know when you should use a Likert scale?
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 a Likert scale 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.
Likert scale questions keep your respondents happy
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.
Likert scales work better when questions are focused on one topic
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.
How to write Likert scale survey questions
Be accurate. 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? The more specific you are, the better your data will be.
Be careful with adjectives. 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.
Bipolar or unipolar? 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.
Better to ask. 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.
5 extra tips on how to use Likert scales
- 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.
- 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.
- 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.
- 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.
- 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.