Likert scaling is a question answerable with a statement that is scaled with 5 or 7 options that the respondent can choose from.
Have you ever answered a survey question that asks to what extent you agree with a statement ? The answers were probably: strongly disagree, disagree, neither disagree nor agree, agree, or strongly agree. Well, that’s a Likert question.
Maybe you know it as a satisfaction scale or an agree-disagree scale or a strongly agree scale. Whatever its name, it is a pretty powerful and widely used means of measurement in surveys. It is primarily used in customer experience surveys and employee satisfaction surveys.
In this article, we’ll answer some common questions about Likert scales and how Likert scales are used, though most importantly how to interpret the results of a Likert survey scale.
Continue reading to learn our advice on how you can benefit from the conclusions you draw from satisfaction surveys and how to implement change to improve your business!
What are a Likert scale and Likert scale questionnaires?
A Likert scale usually contains 5 or 7 response options , ranging from strongly agree to strongly disagree, with differing nuances between these and a mandatory mid-point of neither agree nor disagree (for those who hold no opinion). The Likert-type scale got its name from psychologist Rensis Likert, who developed it in 1932.
Likert scales are a type of closed-ended questions, like the common yes-or-no questions. Participants get to choose from a predefined set of answers , as opposed to being able to phrase their opinions in their own words. However, unlike yes-or-no questions, satisfaction-scale questions allow for the measurement of people’s views on a specific topic with a greater degree of nuance.
But since these questions are predefined, it’s essential to include questions that are as specific and understandable as possible.
The answer presets can be numerical, descriptive, or a combination of both numbers and words. The responses range from one extreme attitude to the other, while always including a neutral opinion in the middle of the scale.
A Likert-scale question is one of the most commonly used in surveys measuring how satisfied a customer or employee is. The most common example of their use is in customer satisfaction surveys, which are an integral part of market research.
Are satisfaction-scale questions the best survey questions?
Maybe you’ve answered one too many customer satisfaction surveys with Likert scales in your lifetime and now consider them way too generic and bland. But, the fact is they are one of the most popular types of survey questions .
Why is that?
First of all, they are pretty appealing to respondents because they are easy to understand and do not require overthinking to answer.
And, while binary (yes-or-no) questions offer only two response options (i.e., if a customer is satisfied with your products and services or not), satisfaction scale questions give you a clearer understanding of customers’ thoughts and opinions .
By using well-prepared additional questions, you can ask questions about particular products or segments of your service. That way, getting to the bottom of your customers’ dissatisfaction is possible and it’s easier to find a way to address their complaints and improve their experience.
They enable you to figure out why customers are satisfied with one product but not another. This empowers you to recognize products and service areas customers are confident in and find ways to improve others.
When it comes to analyzing and interpreting survey scale results, these questions are helpful because they provide quantitative data that is easy to code and interpret . Results can also be analyzed through cross-tabulation analysis (we’ll get back to that later).
Likert scale examples: the types and uses of satisfaction scale questions
Likert questions can be used for many kinds of research. For example, you can determine the level of customer satisfaction with your latest product. Or assess employee satisfaction or get post-event feedback from attendees after a specific event.
Questions can take different formats, but the most common is the 5-point or 7-point Likert scale question. There are 4-point and even 10-point Likert scale questions as well.
How to choose from these options?
The most common is the 5-point question , with most researchers advising the use of at least five response options (if not more). This ensures that respondents have enough choices to express their opinion as accurately as possible.
Some researchers suggest always using an even number of responses so respondents are not presented with a neutral answer, therefore having to “choose a side.” This is to avoid a tepid response when respondents have an opinion, which is one of the most common types of errors in surveying.
Such errors can create incorrect responses, which can negatively affect your research to a significant degree. Here are some other tips to avoid bad data from your survey:
- Instead of asking questions, use statements where possible.
- Use statements (and questions) that are easily understandable and not misleading.
- Keep questions and statements short.
- For every positive statement, use a negative one as a counterpart later in the survey. This will ensure that the survey is not misleading and has valuable results. If a respondent agrees with a positive statement, they should later disagree with its negative counterpart.
- And last but not least, make the survey anonymous .
When it comes to the answer options, present your respondents with several options, based on the information you want to gather. Some examples are: agree-disagree, satisfied-dissatisfied, helpful-not helpful, excellent-poor, and never-always.
How to analyze satisfaction survey scale questions?
For your survey to be its best, how you analyze the information gathered is as important as the survey itself. That’s why we’ll now turn to the most effective ways of analyzing responses from satisfaction survey scales.
When using Likert scale questions, the analysis tools used are mean, median, and mode . They will help you better understand the information you’ve collected.
The mean (or average) is the average value of your data. You calculate this by adding all the numbers you get and dividing by the total number of values offered to respondents. The median is the middle value of a data set, while the mode is the number that occurs most often.
How to use filtering and cross-tabulation for your Likert scale analysis?
With a filter, you focus on the responses of one particular group of respondents and filter out the rest. For example, how female customers rate a product can be determined by filtering out male respondents, or customers aged 20 to 30 gleaned by filtering out older respondents.
Cross-tabulation , on the other hand, is a method to compare two sets of information in one chart and analyze the relationship between multiple variables. In other words, it can show the responses of a particular subgroup but can be combined with other subgroups.
Say you want to look at the responses of unemployed female respondents aged 20-30. By using cross-tabulation, all three parameters—gender, age, and employment status—can be combined and their correlation calculated.
If this all sounds confusing, luckily SurveyPlanet doesn’t just offer you great examples of surveys and the capability to create custom themes , but also the power to export your survey results into several different formats , such as Microsoft Excel and Word files, CSV, PDF, and JSON files.
How to interpret Likert scale data?
When information has been gathered and analyzed, it’s time to present it to stakeholders. This is the final stage of your research. Analyzing the results of Likert scale questionnaires is a vital way to improve service and grow a business. Presenting the results correctly is a key step.
Here’s how to develop a clear goal and present it understandably and engagingly .
1 Compare new to past information to ensure a better understanding of your progress
Compare the newly obtained information with data gathered from previous surveys. Sure, information gathered from the latest research is valuable on its own, but not helpful enough. For example, it tells you if customers are currently satisfied with products or services, but not whether things are better or worse than last year.
The key to improving customer service—and thus developing your business—is comparing current responses with previous ones. This is called longitudinal analysis . It can give you valuable insights on how your business is developing, if you’re improving or falling back in some areas, and what issues need to be solved.
If there is no data from previous years or surveys on that particular matter yet haven’t been distributed before, then start collecting feedback to compare results with future surveys. This is called benchmarking. It helps keep track of progress and see how products, services, and overall customer satisfaction change over time.
2 Compare your information with other types of data and objective indicators
The most crucial information to compare new findings with is previous surveys. But it is highly recommended to constantly compare findings with other types of information, such as Google Analytics and sales data , and other objective indicators.
A good practice is also to compare qualitative with quantitative data. The more information you have, the more accurate research results you will get, which will help better convey findings to stakeholders. This will also improve business decision-making, which will strengthen the experiences of customers and employees.
3 Make a visual representation: help your audience understand you better
Numbers are easier to understand with suitable visual representation. However, it is essential to use a medium that adequately highlights key points of your findings.
Line graphs, pie charts, bar charts, histograms, scatterplots, infographics, and many more can be used.
But don’t forget good old tables. Even if they’re not so visually dynamic and a little harder on the eyes, there is simply some information best presented through tables, especially numerical data.
Working with all of these options, more satisfactory presentations can be created.
4 Focus on your insights instead of the numbers alone
When presenting findings to stakeholders, don’t just focus on the numbers. Instead, highlight the conclusions about customer or employee satisfaction you drew from the research. That way, everyone present at the meeting will gain a deeper understanding of what you’re trying to convey.
A valuable and exciting piece of advice is to focus on the story the numbers tell . Don’t just simply list the numbers you’ve collected. Instead, use relevant examples and connect all the information, building on each dataset to make a meaningful whole.
Define and describe problems that need to be solved in engaging and easy-to-understand terms so that listeners don’t have a hard time understanding what is being shared. Include suggestions that could improve, for example, customer experience outcomes. It is also important to share findings with the relevant teams, listen to their perspectives, and find solutions together .
Likert scales are a highly effective way of collecting qualitative data. They help you gain a deeper understanding of customers’ opinions and needs.
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