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The Likert scale is a method that collects and quantifies opinions, attitudes, and perceptions through graded responses. That’s why it has become one of the most widely used tools in surveys and customer satisfaction measurement. It’s also frequently applied in market research and user experience (UX).
But how can you measure an opinion beyond a simple yes or no?
The answer lies in understanding how the Likert scale works. In this guide, we explain it—along with its types, advantages, limitations, and best practices to apply it correctly.
The Likert scale is a measurement system designed to assess attitudes, opinions, and perceptions toward a specific statement. The goal is to capture the degree or intensity of a person’s response to a topic.
Its name comes from its creator, Rensis Likert, who developed this approach in 1932 for measuring attitudes. Since then, its use has spread across multiple disciplines and is now a common resource in quantitative studies—especially in surveys seeking to transform subjective answers into comparable data.
The Likert scale makes it possible to measure opinions with different levels of intensity beyond a simple “yes” or “no.”
Here’s how it works:
A question or statement is posed, and the person indicates their level of agreement, disagreement, or another assessment.
Instead of responding “yes” or “no,” they choose an option within an ordered scale that goes from lower to higher intensity—for example, from “strongly disagree” to “strongly agree.”
The options are usually symmetric, with opposite endpoints and intermediate points to nuance the response. The structure is meant to clearly indicate whether the perception leans positive or negative.
In addition, the scale can be:
Odd (such as 5 or 7 points): includes a neutral response.
Even (such as 4 or 6 points): removes the midpoint and forces a stance.
Wording and options should follow the same logic across all questions to avoid confusion and maintain consistency in results.
Likert scale types are mainly classified by the number of points or items they include. Some of the most common are:
3-point scale. Useful in basic satisfaction surveys where you only need to identify an overall perception.
5-point scale. Works well for most Likert questions due to its balance between clarity and precision. That’s why it’s the most used in general surveys and standard assessments.
7-point scale. Suitable when you need greater precision in measuring attitudes, for example, for comparative analyses.
10-point scale. Ideal if you want to measure intensity in more detail and distinguish small differences in responses.
This count determines the level of detail in the answers and the degree of precision with which the respondent’s perception is measured. However, the Likert scale can also be classified by its polarity (unipolar or bipolar) and by the dimension it measures.
Below are simple Likert question examples you can reuse in different contexts:
3-point Likert scale:
How would you rate how quickly your order arrived?
Slow.
Acceptable.
Fast.
5-point Likert scale:
The process to complete my request was clear and simple.
Strongly disagree.
Disagree.
Neither agree nor disagree.
Agree.
Strongly agree.
7-point Likert scale:
How comfortable do you feel expressing your ideas at work?
Not at all comfortable.
Very slightly comfortable.
Slightly comfortable.
Somewhat comfortable.
Quite comfortable.
Very comfortable.
Completely comfortable.
5-point Likert scale:
How quickly was your request handled?
Very slow.
Slow.
Neither slow nor fast.
Fast.
Very fast.
3-point Likert scale:
How useful was the class for understanding the topic?
Not useful.
Useful.
Very useful.
10-point Likert scale:
The scale begins at the lowest score and goes up to the highest:

The idea is to notice the pattern: a clear question/statement and ordered options that let you measure intensity—without limiting the response to a simple “yes” or “no.”
The Likert scale is used when you need to measure something that isn’t directly observable. In business contexts, this may be an opinion, perception, or the degree of a person’s satisfaction.
Therefore, it can be applied to:
Satisfaction surveys (CSAT). Measures how satisfied someone felt after a specific experience, such as a purchase or an interaction.
Market research. Used to understand how the target audience thinks—what they prefer, what interests them, and how they rate a brand, product, or message.
Human resources. Helps measure work climate, engagement, motivation, and internal perceptions, both in periodic evaluations and internal surveys.
Customer experience (CX). Applied to analyze how customers perceive their relationship with the brand over time, even comparing results by sales channel.
Education and academic evaluation. Used to gather student opinions about courses, teachers, or methodologies, as well as to assess attitudes and learning processes.
Likert findings on their own can be very useful for spotting trends and measuring perceptions. But if you combine them with an RFM analysis, for example, you can segment better and prioritize actions with greater precision.
The Likert scale is one of the most widely used tools for measuring opinions and attitudes in surveys. But it doesn’t always deliver the same value in every context:
It’s easy to understand.
It allows for comparisons, so you can see changes across periods, teams, or segments.
It makes it easy to measure perceptions and work with quantifiable results.
It works for internal surveys, education, services, and customer experience.
Each person may interpret the levels differently.
Some users avoid extremes and choose mid-range options.
It shows the trend but doesn’t reveal reasons unless you pair it with open-ended questions.
Overall, the Likert scale is practical and easy to analyze. You just need to use it carefully to avoid bias and obtain clearer results.
If you decide to use the Likert scale, here are some tips:
Avoid ambiguous questions. Each question should refer to a single idea and be easy to understand so the respondent knows exactly what they’re evaluating.
Don’t mix scales without reason. If you use “agree/disagree,” stick with that format—don’t switch to, say, “satisfaction” or “frequency” without a clear reason.
Keep the same number of points. Use the same number of options to make responses easier to compare. If you start with 5 points, try to use 5 throughout the survey.
Keep wording neutral. Avoid loaded or value-laden terms that might influence the response (e.g., excellent, obvious, terrible).
Use clear, concrete language. The simpler the wording, the fewer differing interpretations you’ll get.
On another note, we suggest creating flowcharts to streamline data collection and better define the survey process. You can also visualize the results with graphic organizers to spot patterns instantly and make decisions more clearly.
The Likert scale is a practical tool for measuring perceptions and turning opinions into comparable data. It doesn’t just evaluate experiences; it also helps detect trends and make clearer decisions based on what people think.
Of course, it works best when it’s carefully designed and interpreted with sound judgment. That’s why it’s a good idea to combine it with AI tools to automate data collection—especially if you run surveys regularly.
In essence, the Likert scale lets you put numbers to opinions and perceptions—just as DolarApp gives you clarity to measure and better manage your finances. With digital accounts to send or receive foreign currencies easily, and a fair rate to exchange USDc and EURc when you need it.
The Likert scale is a rating method used in surveys to measure attitudes, opinions, and perceptions. It works with ordered response options that identify the level or intensity of a person’s stance.
A Likert scale typically has between 3 and 10 points. However, the most commonly used versions are 5- and 7-point scales, as they balance ease of response with level of detail.
The best Likert scale depends on several factors, including the study’s objective, the audience, and the level of precision required to measure responses.
The Likert scale is used to measure attitudes, satisfaction, and perceptions in a quantifiable way. It simplifies trend analysis, result comparisons, and data-driven decision-making.
An example is a question offering answers like: strongly disagree, disagree, neither agree nor disagree, agree, and strongly agree.
Sources:
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