Likert scaling is a question that may be answered with a statement that is scaled with 5 or 7 choices from which the respondent can select.
Have you ever responded to a survey question asking how much you agree with a statement? The likely responses were: strongly disagree, disagree, neither disagree nor agree, agree, or highly agree. That’s a Likert scale inquiry.
Perhaps you’ve heard of a satisfaction scale, an agree-disagree scale, or a highly agree scale. Whatever its name, it is a rather strong and extensively used method of survey measurement. It is widely utilized in customer satisfaction and staff satisfaction surveys.
In this article, we’ll answer some frequently asked questions concerning Likert scales and how they’re used, as well as how to evaluate the findings of a Likert survey scale.
Continue reading to find out, how to Interpret the Results of a Satisfaction Survey Scale, how you can profit from the results of satisfaction surveys and how to execute change to enhance your business!
What makes a Likert scale different from a Likert scale questionnaire?
A Likert scale often has 5 or 7 response options, ranging from strongly agree to strongly disagree, with subtleties in between and a necessary middle option of neither agree nor disagree. Rensis Likert, a psychologist, created the Likert-type scale in 1932 and gave it his name.
Closed-ended questions, such as yes-or-no questions, are what Likert scales are. Instead of being allowed to express their thoughts in their own words, participants must pick from a predetermined list of replies. Unlike yes-or-no questions, satisfaction-scale questions, on the other hand, provide for a more nuanced assessment of people’s opinions on a certain issue.
The settings for the answers can be numerical, descriptive, or a mix of both numbers and words. The comments run the gamut from one extreme to the other, with a neutral opinion in the middle of the spectrum.
A Likert-scale question is one of the most regularly used in surveys to determine a customer’s or employee’s level of satisfaction. Customer satisfaction surveys, which are an important aspect of market research, are the most typical example of their application.
Is it true that satisfaction-scale questions are the best survey questions?
Perhaps you’ve filled out one too many customer satisfaction surveys with Likert scales in your life and now find them to be too generic and uninteresting. They are, nonetheless, one of the most common surveys question kinds.
What is the reason behind this?
First and foremost, they appeal to responses since they are simple to comprehend and do not necessitate excessive thought.
Furthermore, whereas binary questions only allow for two responses, satisfaction scale inquiries allow you to gain a better grasp of your consumers’ ideas and opinions.
You can ask questions regarding specific goods or portions of your service by utilizing well-prepared extra questions. That way, you’ll be able to get to the root of your consumers’ displeasure, making it simpler to resolve their issues and enhance their experience.
They allow you to determine why clients are happy with one product but not with another. This allows you to identify goods and service areas in which consumers have confidence while also identifying opportunities to enhance others.
These questions are useful for assessing and understanding survey scale findings because they give quantitative data that is simple to code and analyze. Cross-tabulation analysis may also be used to examine the results.
Examples of Likert scales: the many types and applications of satisfaction scale inquiries
Likert scale questions may be utilized in a variety of studies. You may, for example, figure out how satisfied your customers are with your most recent offering. After a given event, analyze employee satisfaction or obtain post-event comments from guests.
Questions come in a variety of styles, but the 5-point or 7-point Likert scale inquiry is the most popular. There are also Likert scale questions with a 4-point and even a 10-point scale.
What should you do if you have so many options?
The 5-point question is the most popular, and most studies recommend using at least five response alternatives. This guarantees that responders have a wide range of options from which to express themselves as correctly as possible.
Some studies recommend utilizing an odd number of options so that respondents aren’t given a neutral answer and are forced to “choose aside.” This is to prevent one of the most prevalent forms of surveying errors: a lukewarm answer when respondents have an opinion.
Such inaccuracies can lead to wrong replies, which can have a big detrimental impact on your study. Here are some more suggestions for avoiding faulty survey data:
- When feasible, utilize statements instead of questions
- Use statements that are simple to grasp and do not mislead
- Keep your questions and statements brief
- Use a negative remark as a counterpoint to every good comment later in the poll. This ensures that the survey is not deceptive and yields useful findings. If a respondent agrees with a positive statement, they should subsequently disagree with its opposite
- Last but not least, ensure that the poll is anonymous
When it comes to response options, provide your responders with a few choices based on the information you’re looking for. Agree-disagree, satisfied-dissatisfied, useful-not helpful, excellent-poor, and never-always are some instances.
How do you analyse questions on a satisfaction survey scale?
The way you interpret the data obtained is just as essential as the survey itself in making your survey the best it can be. As a result, we’ll now look at the most successful methods for assessing satisfaction survey scale replies.
The analytic methods utilized while employing Likert scale questions include meaning, median, and mode. They’ll assist you in better comprehending the data you’ve gathered.
The average value of your data is the mean. This is calculated by summing all of the numbers and dividing by the total number of options available to responders. The median is the data set’s midway value, whereas the mode is the most common number.
Filtering and cross-tabulation are two more useful methods for information analytics.
How can you optimize your Likert scale analysis by using filtering and cross-tabulation?
A filter allows you to focus on the replies of a certain set of people while filtering out the others. Filtering out male respondents, for example, can reveal how female consumers rank a product while filtering out older respondents can reveal clients aged 20 to 30.
On the other hand, cross-tabulation is a technique for comparing two sets of data in one chart and analyzing the relationship between numerous variables. In other words, it can display the replies of a single subgroup while still allowing for the inclusion of responses from other subgroups.
Let’s say you’re interested in the replies of jobless female responders between the ages of 20 and 30. All three parameters—gender, age, and work status—can be merged and their connection assessed using cross-tabulation.
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How should Likert scale data be interpreted?
It’s time to convey the information to stakeholders after it’s been acquired and processed. This is the last stage of your investigation. The findings of Likert scale surveys must be analyzed in order to enhance service and expand a company. One of the most important steps is to present the results accurately.
Here’s how to create a clear aim and deliver it in an understandable and entertaining manner.
1. Comparing new and old data to have a better picture of your development
Compare the information you’ve just gotten with what you’ve learned from earlier surveys. Sure, knowledge gleaned from the most recent studies is useful in and of itself, but it isn’t enough. It will tell you if customers are now happy with products or services, but not whether they are better or worse than they were last year.
Comparing current replies to prior ones is the key to enhancing customer service—and ultimately growing your organization. Longitudinal analysis is the term for this. It may provide you with useful information on how your firm is progressing, whether you’re advancing or regressing in certain areas, and what issues need to be addressed.
Start collecting feedback to compare findings with future surveys if there is no data from past years or if surveys on that particular subject have yet to be delivered. This is referred to as benchmarking. It allows you to keep track of your success and monitor how your goods, services, and overall client happiness evolve over time.
2. Compare your results to other types of data and objective markers.
Previous surveys are the most important data to compare current findings to. However, it is critical to compare conclusions with other sorts of data, such as Google Analytics and sales data, as well as other objective indications.
Comparing qualitative and quantitative data is also a beneficial approach. The more information you have, the more accurate your research results will be, and you’ll be able to communicate your findings to stakeholders more effectively. This will also enhance company decision-making, which will improve consumer and employee experiences.
3. Create a visual depiction to assist your audience in better comprehending you
With the right visual depiction, numbers are simpler to understand.
However, it is critical to choose a media that effectively displays the most important aspects of your research.
Line graphs, pie charts, bar charts, histograms, scatterplots, and infographics are just a few examples.
But don’t overlook the value of good old tables. Even if they aren’t as visually exciting and are a bit more difficult on the eyes, there is some information that is best presented in tables, particularly numerical data.
More satisfying presentations may be generated by combining all of these possibilities.
4. Instead of focusing just on the data, consider your observations
Don’t merely focus on the numbers when presenting findings to stakeholders. Instead, emphasize the research’s findings of customer or staff happiness. Everyone in the room will have a better comprehension of what you’re attempting to say this way.
Focusing on the tale the data tell is a crucial and fascinating piece of advice. Don’t just jot down the numbers you’ve gathered. Instead, utilize relevant examples to link all of the data, constructing a coherent whole from each dataset.
Define and describe issues that need to be handled in interesting and easy-to-understand words so that listeners can grasp what you’re saying. Include recommendations that might help to enhance customer experience results, for example. It’s also crucial to communicate results with appropriate teams, listen to their viewpoints, and work together to identify solutions.
Likert scales are a powerful tool for gathering qualitative data. They assist you in gaining a better grasp of your client’s requirements and opinions.
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