Likert scales are a common way to measure attitudes, opinions and sentiment in surveys. They ask respondents to indicate how strongly they agree or disagree with a statement, or how positively or negatively they feel about something.
This article explains when to use Likert scales and how to set them up correctly in Attest.
What is a Likert scale?
A Likert scale is an ordered scale that captures the intensity of a respondent’s attitude. It is most often evenly balanced between positive and negative responses, with a neutral midpoint.
Likert scales are typically made up of five points, for example:
Strongly agree
Slightly agree
Neither agree nor disagree
Slightly disagree
Strongly disagree
Or:
I love it
I like it
Neither like nor dislike it
I don’t like it
I hate it
Using a consistent scale makes it easier to compare sentiment across different questions or subjects.
When to use a Likert scale
Likert scales are best used when you want to:
Measure attitudes or opinions
Compare sentiment across multiple items
Track changes in perception over time
They work well as a standalone single choice question or as the answer scale in a grid question, where the same scale is applied to multiple subjects.
Set up Likert scales correctly in Attest
You can create a Likert scale using a single choice question or by adding scale answers to a grid question.
When using a Likert scale, make sure answer randomisation is turned off. Randomising scale answers would break the natural order of the scale and make it harder for respondents to answer accurately.
Use suggested scale answers
To make setup faster, Attest provides a set of suggested scale answers. When adding multiple answers to a question, you can choose to insert a predefined scale. Select the scale you want and Attest will add the answers in the correct order and automatically turn off answer randomisation.
If you are unsure whether a Likert scale is the right choice, Compass can help you choose an appropriate question format based on your research goal. You can also speak to the in-house Customer Research Team via in-platform live chat for guidance on best practice.
