How to create and analyze 5-point Likert scales

If you’re looking to create a survey to measure how an audience truly feels about your product or service, consider including a Likert scale. By using a Likert scale — essentially a rating scale that helps measure people’s opinions and overall satisfaction levels — you’ll be able to collect better, more valuable feedback that can help guide future business decisions.

One of the best, most popular types of Likert scales is the 5-point scale, as it provides respondents with a manageable range of options to choose from: two positive (e.g., strongly agree and somewhat agree), two negative (strongly disagree and somewhat disagree), and one neutral.

Likert scales can deliver a number of benefits:

Here’s a breakdown of how they work.

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Creating a 5-point Likert scale

To get a better idea of how to create and analyze a 5-point Likert scale, let’s imagine you want to create an employee exit interview questionnaire to better understand a recent increase in employee turnover at your company. Perhaps you have your suspicions about what could be causing the uptick, but you’d feel more comfortable having tangible data to back up your concerns in order to prepare for an upcoming staff meeting.

As a baseline, your exit interview survey includes the following five aspects of working for your company for your respondents to rate (though you could always make it much longer and more granular): work/life balance, relationship with colleagues, relationship with management, salary, and work arrangement flexibility (e.g., whether your organization allows employees to work remotely). Based on the responses you receive, you can assess which factor most influenced their decision to leave.

Once you add the response options to the exit interview survey, it should look something like this survey sample below (created using Jotform’s online form builder).

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Analyzing a 5-point Likert scale

Now that you’ve collected all the surveys from former employees, it’s time to analyze the results by finding the mode of the responses, which isolates the value that appears most often in a set of data.

By assigning numerical values for each sentiment level — 1 for “Strongly influenced me to stay” and 5 for “Strongly influenced me to leave” — you can quantify how your respondents feel about each category and the job overall.

To illustrate, let’s assume you gave the exit interview survey to five people and these were their responses: