Designing a great survey isn’t just about asking the right questions — it’s about how you ask them. One of the most reliable and widely used tools for gathering feedback is the Likert scale, a simple yet powerful method for quantifying opinions, satisfaction, and perceptions.

Whether you’re measuring employee morale, customer experience, or user satisfaction, knowing how to design surveys using the Likert scale can make the difference between clear, actionable data and confusing, biased results.

Understanding the Role of the Likert Scale in Survey Design

A Likert scale helps you capture degrees of opinion rather than binary answers. Instead of asking “Did you like the product?” — which limits responses to “yes” or “no” — you ask, “How much did you like the product?” and provide a range of options such as Strongly Agree to Strongly Disagree.

This structured approach turns emotional, subjective feelings into measurable data, helping you analyze not only what respondents think but how strongly they feel about it.

If you’re new to the concept, start with What Is a Likert Scale and How Does It Work? — a detailed introduction to the fundamentals of Likert-based research.

Why the Likert Scale Is Ideal for Modern Surveys

The Likert format is flexible and intuitive, which makes it suitable for almost any type of research. Marketers use it to assess brand perception, HR teams to measure engagement, educators to evaluate student satisfaction, and researchers to quantify social attitudes.

Because it’s based on agreement, frequency, or satisfaction, the Likert scale simplifies data collection without oversimplifying human emotion. For instance, you can easily adapt it to measure:

• Levels of agreement (Strongly Agree → Strongly Disagree)

• Frequency (Always → Never)

• Importance (Very Important → Not Important at All)

• Satisfaction (Very Satisfied → Very Dissatisfied)

The Likert scale has become a universal language for feedback, allowing you to collect structured, comparable results across different audiences. To see how scale length impacts design and response quality, read 5-Point vs 7-Point Likert Scale: Which One Should You Use?.

Components of a Well-Designed Likert Question

A typical Likert item consists of two elements:

1. A statement that expresses an opinion or attitude.

2. A response scale that allows the respondent to indicate their level of agreement or experience.

For example:

“I feel that the onboarding process at my company is efficient.”

• Strongly Agree

• Agree

• Neutral

• Disagree

• Strongly Disagree

The statement should be specific, clear, and neutral in tone. Avoid emotional or ambiguous wording that might bias responses. Each statement should evaluate one single concept — never combine two ideas in one question (known as a double-barreled question).

Writing Effective “Agree/Disagree” Statements

When designing Likert questions, phrasing is everything. Statements that are too vague lead to inconsistent answers, while those that are too long confuse respondents. The best Likert statements are short, factual, and opinion-driven.

Here are examples of strong and weak Likert items:

By focusing each statement on a single thought, you make it easier for respondents to evaluate their level of agreement accurately. This improves data consistency and reduces respondent fatigue — a major advantage when running long surveys.

For more on interpreting these responses correctly, check out How to Interpret Likert Scale Responses Accurately.

Choosing the Right Scale: 5-Point or 7-Point?

One of the biggest decisions when designing a Likert-based survey is whether to use a 5-point or 7-point scale. The 5-point scale is simple, widely recognized, and works best for quick surveys. The 7-point scale provides greater detail, allowing respondents to express more subtle opinions.

If you’re collecting broad satisfaction data (for example, measuring customer service feedback), the 5-point Likert scale is likely sufficient. But if you’re analyzing complex attitudes — such as confidence, emotional response, or brand trust — the 7-point Likert scale gives more nuance.

The best practice is to stay consistent: once you choose your scale length, use it throughout the entire survey to maintain comparability. To understand how the number of points influences your data’s reliability, see How Many Points Should a Likert Scale Have?.

Avoiding Bias and Design Errors

Even well-designed Likert questions can fail if the scale is biased. For instance, if all statements are phrased positively, respondents might unconsciously agree with everything. To prevent this, include a mix of positively and negatively worded statements.

Example:

• “The company communicates clearly about new policies.”

• “The company’s goals are often unclear.”

This contrast helps you identify inconsistent or automatic responses.

Another common error is unbalanced scales. A scale that leans too heavily in one direction (e.g., more positive than negative options) can distort your findings. Always aim for symmetry — equal positive and negative response choices with a clear neutral midpoint.

We explore more pitfalls like these in Common Mistakes When Using the Likert Scale.

Using Likert Scales Across Different Research Types

The beauty of the Likert design lies in its adaptability. It can be used for:

• Employee engagement: “I feel recognized for my work.”

• Customer satisfaction: “The checkout process was easy to complete.”

• Market research: “This brand reflects my personal values.”

• Education: “I feel confident using online learning tools.”

In each case, the Likert structure provides quantifiable insight into subjective experiences, enabling researchers to track trends, spot improvement areas, and guide data-driven decisions.

For a deeper look into how these responses are processed, visit How to Analyze Likert Scale Data Like a Pro.

Real-World Likert Scale Examples

To illustrate how Likert items appear in practice, here are three example questions from different fields:

Example 1 – HR Survey

“My manager provides clear feedback on my performance.”
Scale: Strongly Disagree → Strongly Agree

Example 2 – Customer Satisfaction Survey

“The product I ordered matches the description provided online.”
Scale: Strongly Disagree → Strongly Agree

Example 3 – Education Research

“I find the online course materials easy to follow.”
Scale: Strongly Disagree → Strongly Agree

Each example uses the agree/disagree format, but you can also apply the Likert principle to frequency (Always → Never), satisfaction (Very Satisfied → Very Dissatisfied), or likelihood (Very Likely → Very Unlikely) scales.

Testing and Refining Your Survey

Before launching your survey, test it with a small group of participants. Observe whether respondents interpret questions as intended and whether any wording causes confusion. This step helps fine-tune your statements and ensures your Likert scale data will be reliable and valid.

It’s also worth monitoring response patterns. If most participants always choose the same column, it could indicate question fatigue or bias. In such cases, review your phrasing and balance.

Once your data collection is complete, follow the best practices described in How to Analyze Likert Scale Data Like a Pro to extract meaningful insights from your results.

Conclusion

Designing effective surveys with the Likert scale requires more than just inserting “agree/disagree” options — it demands careful attention to question phrasing, balance, and consistency. When built correctly, Likert-based questions can capture attitudes, emotions, and behaviors with clarity that few other formats can achieve.

Start small, keep your scales consistent, and remember that your wording shapes your data. By mastering Likert design, you’ll create surveys that are not only easy to answer but also rich in insight — allowing you to transform subjective opinions into actionable results.

To continue your learning, explore How to Interpret Likert Scale Responses Accurately — a complete guide to decoding your results and identifying meaningful trends in respondent behavior.