Learn about one of the most reliable ways to measure opinions, perceptions and behaviours 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.
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).
So what is a Likert scale survey question? It’s a question that uses a five- or seven-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 behaviours.
Compared to binary questions, which only give you two answer options, Likert-type questions will provide you with 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 allow you to uncover degrees of opinion that could make a real difference in terms of understanding the feedback you’re getting. And it can also pinpoint the areas where you may want to improve your service or product.
Likert scale ratings are structured to provide quantifiable answer options that make analysing 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, such as creating overly broad questions that respondents may find too hard to think about. This could cause them to become 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, such as “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 thanks to 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 obtain more accurate results. Why? Because when the time comes for you to report the data, you want to analyse 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 appetisers 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 the dessert tonight?
But here’s one question you should leave for another section of the survey:
How satisfied or dissatisfied are you with the cloakroom service 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 towards the particular product, service or event you’re researching.
A typical customer satisfaction survey uses an ordinal scale that allows users to rank their opinions. For example, a five-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 (i.e. Never, Rarely, Sometimes, Often, Frequently) would be useful. Below is an example of a customer service Likert-type scale for “satisfaction”:
Overall, how satisfied or dissatisfied are you with our company?
Likert scale responses can also be a useful tool for checking in with employees. By adapting the same five-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 and/or 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 organisation makes in education:
Marketers or event professionals can use a five-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 focus in on different parts of the event, such as the probability of the participant attending 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?
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…
…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.
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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 the front of house staff, the waiting staff or the maître d'? All of the above? Are you asking whether the customer was satisfied with the speed of service, the courteousness of the staff or the quality of the food and drinks? The bottom line is that if you can be 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 make 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 “quite a lot” 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 (e.g. “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.
You have probably been familiar with 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.
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