Likert Scale: Gauging the Attitudes of Your Customers

It is hard to talk about survey methodology and practices without mentioning the Likert scale. While some may think the Likert scale is only used in academic research, it is a cornerstone of survey strategies across various industries such as travel & hospitality, automotive, and financial services.

What is the Likert Scale?

The Likert Scale, named after psychologist Rensis Likert, is a widely used tool in social science research and survey methodology for measuring attitudes, opinions, and perceptions of respondents. The Likert Scale usually ranges from five to seven points, with respondents selecting a response that best reflects their agreement or disagreement with each statement. The typical format includes options such as “Strongly Disagree,” “Disagree,” “Neutral,” “Agree,” and “Strongly Agree.” In some cases, scales may also include “Don’t Know” or “Not Applicable” options.

Researchers analyze the responses to calculate measures of central tendency (like mean or median) and dispersion (like standard deviation) to understand the distribution of opinions or attitudes within the sample population. This scale provides a structured way to quantify subjective opinions, making it easier to analyze and compare data across respondents and groups.

What are the Different Types of Likert Scales?

There are several variations of Likert scales, differing primarily in the number of response options provided to respondents. The two most common types are the 5-point Likert scale and the 7-point Likert scale.

5-Point Likert Scale:

In this scale, respondents are typically presented with a statement and five response options ranging from “Strongly Disagree” to “Strongly Agree.” The options might look like this:

  • Strongly Disagree
  • Disagree
  • Neither Agree nor Disagree (Neutral)
  • Agree
  • Strongly Agree

7-Point Likert Scale:

The 7-point Likert scale expands on the 5-point scale by providing additional response options, usually to offer more nuanced distinctions between levels of agreement and disagreement. The options might look like this:

  • Strongly Disagree
  • Disagree
  • Somewhat Disagree
  • Neither Agree nor Disagree (Neutral)
  • Somewhat Agree
  • Agree
  • Strongly Agree

Both scales serve the same purpose of measuring attitudes or opinions, but the 7-point Likert scale allows for a finer granularity of responses, which can sometimes provide more detailed insights into respondents’ attitudes or perceptions. The choice between the two scales depends on the specific needs of the research or survey design and the level of detail desired in the responses.

What is the Best Type of Likert Scale to Use?

The choice of which Likert scale to use depends on several factors, including the research objectives, the nature of the survey questions, and the preferences of the researcher or organization conducting the survey. There isn’t a universally “best” type of Likert scale; rather, it’s about selecting the most appropriate scale for the specific context. Here are some considerations to keep in mind when choosing a Likert scale:

Research Objectives

Consider the goals of your research and the type of data you need to collect. If you require more nuanced responses to accurately capture the variability in respondents’ attitudes or opinions, a 7-point Likert scale might be more suitable. However, if simplicity and ease of interpretation are priorities, a 5-point Likert scale could suffice.

Question Complexity

The complexity of the survey questions can influence the choice of the Likert scale. If the questions are straightforward and do not require fine-grained distinctions in responses, a simpler scale like the 5-point Likert scale may be sufficient. On the other hand, if the questions are more complex or cover a wide range of opinions, a 7-point Likert scale might provide more flexibility.

Response Bias

Consider the potential for response bias in your survey. Providing more response options (e.g., with a 7-point Likert scale) can sometimes reduce the likelihood of respondents selecting neutral options as a default. However, too many response options could overwhelm respondents and lead to careless responses.

Comparison with Existing Data

If you have existing data or are conducting research in a field where a particular Likert scale is commonly used, it may be advantageous to maintain consistency for easier comparison and analysis across studies.

Ultimately, the choice of the Likert scale should be made thoughtfully, taking into account the specific requirements of the research, the characteristics of the respondents, and the overall survey design. It’s often beneficial to pilot test different versions of the Likert scale to gauge respondent understanding and ensure the scale effectively captures the intended attitudes or opinions.

Examples of Likert Scale Questions

Writing effective Likert scale questions involves careful consideration of the topic, clarity of language, and ensuring that response options adequately capture the range of attitudes or opinions you want to measure. These factors are of the utmost importance to limit any type of voluntary response bias in sampling. Remember, whoever answers the question will be answering by selecting a range of emotions such as “satisfied/agree” or “not satisfied/disagree.” So, more often than not, these questions will be statements that reflect aspects of the topic you are trying to assess. Here are some examples of Likert scale questions:

  • I am likely to recommend this product to others.
  • The quality of the product meets my expectations.
  • I am happy with the level of support provided by customer service.
  • How pleased are you with your job?
  • I thought this system was easy to use.

These examples represent Likert questions that can be direct questions or statements about a range of products and services. 

Examples of Bad Likert Scale Questions

Poorly constructed Likert questions often consist of double-barreled statements that contain ambiguous language that causes them to be biased or misleading. Consider the following examples:

  • “Do you agree that the product is excellent and worth recommending?”

This question is double-barreled, combining two distinct concepts (“excellent” and “worth recommending”) into a single statement. This question would not yield a meaningful response as the question is comparing two items into one question. 

  • “How much do you like the product: very much, much, somewhat, little, very little?”

This question lacks a clear direction or anchor for respondents to understand the meaning of each response option. It also uses imprecise language (e.g., “somewhat”) that may be interpreted differently by respondents. This question would also not yield a meaningful response. 

How to Analyze Likert Scale Data

After your surveys have been completed, it is time to analyze the data. When it comes to analyzing Likert scale data, there are a number of ways to segment the data. Which method you choose will ultimately end on the initial research questions. Some examples of this data analysis are descriptive, frequency, and regression analysis. 

  • Descriptive analysis: Calculate the mean, median, mode, and standard deviation for each response on the Likert scale for a quick summarization of the data. 
  • Frequency analysis: Total the number of items each response was selected and use the quantitative data to create tables or charts to show the distribution of each answer. 
  • Regression analysis: Depending on the objective of the survey, you may be able to analyze the relationship between the various Likert responses and an independent variable. 

Advantages of Using the Likert Scale

The Likert scale offers several advantages for organizations that are looking to implement a simple, effective survey methodology. Likert scales are straightforward and easy to understand for both respondents and researchers. Along with ease of use, here are some other benefits of utilizing the Likert scale: 

  • Flexibility: Likert scales can be adapted to measure a wide range of constructs, including attitudes, opinions, behaviors, satisfaction levels, and more. Researchers can customize Likert scale questions to fit their specific research objectives and contexts.
  • Comparability: Likert scale data enables researchers to compare responses across different groups, variables, or time points. This comparability facilitates meaningful analysis of trends, differences, or relationships within the data.
  • Standardization: Likert scales provide a standardized format for measuring attitudes or opinions, enhancing the consistency and replicability of research findings. This standardization allows for easier comparison of results across studies and populations.

Limitations of the Likert Scale

The Likert scale offers many advantages, but those are not without a small set of limitations. One of the biggest limitations of the Likert scale is the finite number of responses that respondents are limited to. These may not fully capture the complexity of respondents’ attitudes or opinions. This can lead to oversimplification or loss of nuance in the data.

Along with this, respondents may exhibit response bias, such as acquiescence bias (tendency to agree with statements) or social desirability bias (tendency to provide socially acceptable responses), particularly if the scale lacks anonymity or if respondents feel pressured to conform to perceived norms.

Despite these limitations, the Likert scale remains a widely used and valuable tool for measuring attitudes, opinions, and perceptions in various research settings. Researchers should carefully consider these limitations and take steps to mitigate potential biases and challenges when designing and interpreting Likert scale surveys.

When to Use the Likert Scale

Likert scales are well-suited for assessing individuals’ attitudes or opinions toward specific topics, issues, products, services, or experiences. This can come in the form of a Net Promoter Score (NPS) survey or a Customer Satisfaction Survey (CSAT). For example, they can be used to gauge satisfaction with customer service or perceptions of organizational culture. 

Furthermore, Likert scales are effective in quantifying subjective perceptions or experiences. Researchers can use Likert scales to measure perceptions of quality, trust, reliability, fairness, or effectiveness in various domains. This can be used to ask customers about their personal experiences with an organization and make those answers measurable. 

How the Likert Scale Effects Your CX Efforts

The Likert scale is a great tool to be utilized in your customer experience efforts. They are a great way to provide a structured method for measuring customer satisfaction across various touchpoints in the customer journey. By asking customers to rate their satisfaction levels with specific aspects of their experience (e.g., product quality, service responsiveness, website usability), organizations can identify areas of strength and areas for improvement.

Similarly, Likert scale data provides valuable insights that can inform strategic decision-making and resource allocation. By identifying areas with low satisfaction scores or high variability in responses, organizations can prioritize investments in CX improvement initiatives that are most likely to have a positive impact on customer loyalty and retention. 

Involving customers in the feedback process through Likert scale surveys can enhance engagement and satisfaction. By demonstrating a commitment to listening to customer feedback and taking action based on their responses, organizations can build trust, loyalty, and advocacy among their customer base.

Utilize the Likert Scale with InMoment

InMoment’s XI Platform allows you to utilize the Likert Scale to gather actionable feedback, measure satisfaction, and drive meaningful improvements. Schedule a demo today to see how we can help your business. 

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About Author

Mike Henry CX Writer

Mike is a passionate professional dedicated to uncovering and reporting on the latest trends and best practices in the Customer Experience (CX) and Reputation Management industries. With a keen eye for innovation and a commitment to excellence, Mike strives to deliver insightful content that empowers CX practitioners to enhance their businesses. His work is driven by a genuine interest in exploring the dynamic landscape of CX and reputation management and providing valuable insights to help businesses thrive in the ever-evolving market.

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