Likert scale: examples and practical guide to using it in your studies

Escala de Likert | Likert scale
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The Likert scale is a type of question used in market research surveys to evaluate the opinions and attitudes of survey respondents. It is one of the most commonly used measurement types. Let’s see what it consists of, in which cases it can be applied, and some examples of Likert scale in practice.

What is the Likert Scale?

The Likert scale is designed to assess the level of agreement or disagreement of survey respondents on a topic using a scale. Questions designed with the Likert scale model offer response options that span two extremes, with intermediate rating levels. Compared to binary models that offer only two response options, Likert scales are more effective at obtaining more precise and nuanced information.

The Likert scale is used in market research to assess the degree of agreement of survey respondents with affirmative or negative statements. It is commonly used to evaluate consumer reactions, attitudes, intentions, and behaviors regarding brands, products, or markets.

It is also a multi-item scale, consisting of a series of statements (items) expressing the types of attitudes to be investigated. Responses are presented as closed and predefined, provided with numerical or verbal options from which the survey respondent chooses.

This method was developed in 1932 by the American educator and psychologist Rensis Likert with the aim of establishing a way to measure opinions and attitudes.

Advantages and Disadvantages of Using the Likert Scale

Let’s explore the advantages and disadvantages of this technique.

Advantages of the Likert Scale

  • Easy to apply and design
  • Provides a gradation of opinions
  • Easy to answer
  • Yields quality measurements
  • Allows for necessary analysis to achieve research objectives
  • Enables comparison with previous service evaluations or similar services

Disadvantages of the Likert Scale

  • Some studies claim that the scale exhibits bias because positive responses consistently outweigh negative ones
  • Other studies claim that a high percentage of respondents tend to answer «agree» as it implies less mental effort when responding to the survey
  • Difficulty in accurately establishing the quantity of positive and negative responses

Examples of the Likert Scale

One of the clearest examples of the application of the Likert scale is in customer satisfaction surveys about products or services.

Let’s see what data we can obtain and how to formulate questions using this scale.

Measuring Satisfaction Level

The Likert scale allows for responses within a range of options that encompass different degrees.

For example:

How was the purchasing process?

Very positive




Very negative


What is your level of satisfaction with our product?

Very satisfied




Very dissatisfied


Measuring Relevance to Potential Consumers

Is our product useful to you?

Very useful



Not very useful

Not useful at all


Or with another approach:

Is this service important to your needs?

Very important



Not very important

Not important at all


Measuring Customer Experience (CX)

The Likert scale can also be used to assess the customer experience (CX) of specific products or services, for example:

When trying to contact customer service, I find it easy

Strongly agree



Somewhat disagree

Strongly disagree

Tips for Using the Likert Scale

Here are some basic tips to consider when creating surveys based on the Likert scale.

  • Maintain a balance between positive and negative questions
  • Write statements clearly and concisely
  • Provide the same number of response options for all questions
  • Offer a neutral response option for survey respondents who may not know how to or cannot choose


As you can see, the Likert scale can be a very useful technique for your surveys.

We at We are testers allow you to use the Likert scale in all the questionnaires you want to create. Additionally, our team of experts can assist you in designing your survey to obtain all the data you need to make the best decisions regarding your market and your products and services.

Update date 15 April, 2024

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