If you’ve ever rated your satisfaction on a scale from 1 to 5, you’ve used an ordinal scale. Researchers, marketers and customer experience professionals have used ordinal scale in surveys and feedback forms. What do they mean? In this blog, we will discuss the meaning, advantages and types of ordinal scale. 

What is an Ordinal Scale?

An ordinal scale depicts the order or rank of values without specifying the exact difference between them. It’s part of the four fundamental types of measurement scales: nominal, ordinal, interval, and ratio. In the ordinal scale, the categories are ranked in a specific order. The intervals between values are not necessarily equal.

Examples:

• Satisfaction levels: Very Unsatisfied, Unsatisfied, Neutral, Satisfied, Very Satisfied
• Education level: High School, Bachelor’s, Master’s, Doctorate
• Military ranks: Private, Corporal, Sergeant, Lieutenant, Captain

Example of a survey question: “How satisfied are you with our service?” respondents might choose from:

• Very satisfied
• Satisfied
• Neutral
• Dissatisfied
• Very dissatisfied

Here, “very satisfied” ranks higher than “satisfied,” but the difference between them is not measured in numerical values. Ordinal scales are commonly used in surveys, questionnaires, and polls because they simplify data collection and reveal trends.

Characteristics of an ordinal scale

These characteristics of ordinal scale make it versatile for qualitative and semi-quantitative research. 

• Ordered Ranks: Responses are arranged in a meaningful order (e.g., high to low or frequent to rare).
• Non-Quantifiable Intervals: The difference between ranks isn’t uniform or measurable (e.g., the gap between “satisfied” and “neutral” may vary by respondent).
• Categorical Data: Responses are grouped into categories rather than precise numbers.
• No Absolute Zero: Unlike ratio scales, ordinal scales don’t have a true zero point.

Why Should You Use Ordinal Scales in Surveys? 

Ordinal scales are widely used in surveys, research, and assessments because they strike a balance between simplicity and meaningful data. These scales are used to measure customer experience (1 to 5 poor to excellent rating scale), employee experience and for healthcare studies. 

• Ordinal scales are popularly used in market research. People are familiar with the format. So it becomes easier to use it to collect critical information. 
• Ordinal scale surveys offer more information than nominal scales. Nominal scales merely serve as a way to tag and group people in specific categories. Ordinal scale collects information on attitudes, behaviours and experiences at various levels. 
• This scale is ideal to collect closed-ended data but in a non-numerical format. This format follows a systematic order.

Common Types of Ordinal Scales

1. Likert scale

Likert scale is the most popular ordinal scale used in customer feedback surveys or used in market research. There are various types of Likert scales (agreement, quality, frequency etc.). It is mapped on a 5-point rating scale or a 7-point rating scale. Example: strongly disagree to strongly agree)

2. Guttman scale

The Guttman scale is arranged in a way that the elements can be arranged in a hierarchical order. Here the agreement with one item implies agreement with previous items.

3. Thurstone scale

Thurston scale is a psychometric scale that measures attitudes using a series of objective statements. Each statement has a preassigned number value. Respondents choose to agree or disagree with each statement. The overall attitude score is calculated by creating an average of the values of the statements they specifically agree with.

Examples of Ordinal Scale in Surveys 

1. Customer satisfaction surveys: Question: “How satisfied are you with our product?”

• • Very Satisfied
  • Satisfied
  • Neutral
  • Dissatisfied
  • Very Dissatisfied

2. Employee engagement: Question: “How motivated do you feel at work?”

• • Extremely motivated
  • Moderately motivated
  • Neutral
  • Slightly motivated
  • Not motivated
    

3. Socioeconomic status: Question: “How do you rank your economic status?”

• • Low-income
  • Middle-income
  • High-income
    

4. Fitness assessment with frequency of behaviour: Question: “How often do you exercise?”

• • Daily
  • Weekly
  • Monthly
  • Rarely
  • Never

Applications of Ordinal Scale

1. Market research

Ordinal scales help researchers understand customer preferences, satisfaction levels, and brand perception. Companies use ordinal data to refine their products and services based on customer feedback.

2. Psychological & social science studies

In psychology and social sciences, ordinal scales measure attitudes, opinions, and behaviors. Likert scales in surveys are a perfect example of ordinal measurement.

3. Healthcare & medical research

Doctors use ordinal scales to assess patient conditions, such as pain levels or severity of symptoms. Measuring levels of pain severity can help doctors diagnose and treat patients better.

4. Performance evaluation in businesses

Organizations rank employee performance using ordinal scales, such as “Exceeds Expectations,” “Meets Expectations,” and “Needs Improvement.”. Ordinal scales are often used to measure employee experience. 

Using Ordinal Scales: Advantages and Limitations

Advantages 

• Easy to understand, implement and run side by side comparisons of different variables. It can measure attitudes and preferences that you can analyze quantitatively. 
• A customer satisfaction survey segments customers based on their responses from a scale. It categorizes respondents into happy customers, passives, and those at risk of churn. This classification helps businesses tailor engagement strategies for each group effectively. 
• A flexible ordinal scale is ideal for polls, customer feedback surveys and questionnaires of most types. It can be for market research or to gauge general preferences. The scale measures non-numeric characteristics. So it can be used for both quantitative and qualitative research. 

Limitations

While powerful, ordinal scales have drawbacks:

• The intervals between ranks are not equal, limiting statistical analysis (e.g., you can’t calculate an average).
• Respondents may interpret options differently (e.g., “Satisfied” means different things to different people).
• You can’t quantify how much better one rank is than another. This offers limited comparison.

Ordinal Scale vs. Other Scales

Understanding how ordinal scales differ from other measurement scales helps you choose the right tool for your research.

Nominal scale

Nominal scale categorizes data without order (e.g., “What is your favorite color?” with options Red, Blue, Green). It does not conduct ranking assessments. Nominal scale presents questions objectively and enables people to choose from a given option. It does not involve any experience or emotional metrics of respondents.

Interval scale

Interval scale ranks data with equal intervals but no true zero (e.g., temperature in Celsius). Intervals are measurable unlike ordinal scales. This scale measures IQ scores. 

Ratio scale

Ratio scale ranks data with equal intervals and a true zero (e.g., weight or height). This scale allows for ratios (e.g., 10 kg is twice of 5 kg). Ratio scale is used to track sales revenues.

How to Use Ordinal Scales in Surveys

Designing effective ordinal scale questions requires strategy. Follow these tips:

1. Used balanced labels that are easy to read

Each option should be easy to read and understand. Use simpler scales where you can use a 1 to 5 rating scale survey. Each option should be evenly distributed with a simple language.

2. Limit scale points when possible   

Net Promoter Score uses a 0-10 point rating scale because it is a standard measurement metric. NPS surveys are familiar to respondents. However, use 1-5 rating scale or 1-7 rating scale according to the occasion. When possible, keep scales smaller for quick  and unbiased response.

3. Keep language simple even during multilingual  translation

Avoid leading questions in this manner: Do you agree the service was pleasant?. Instead ask : Please rate our service today. Focus on a simple yet neutral language that enables customers to share their response without bias.

4. Run your surveys via multiple survey channels 

Run ordinal scale surveys via various interactive survey channels. Use Merren and run surveys on WhatsApp, Facebook messenger and dynamic emails to get a high survey response rate. Most people stay on their mobile devices. This makes surveys accessible for customers across touchpoints.

5. Demo test the survey across sample respondents

Run the survey on various devices before sharing it among the final group of respondents. This will prevent any errors and help you refine questions. Make sure that the surveys are compatible across devices and platforms.

Example Survey Question:

• Question: “How likely are you to recommend our service?”
• Options: Extremely likely, Likely, Neutral, Unlikely, Extremely unlikely
• Analysis: Calculate the percentage of “Likely” or “Extremely likely” responses to measure Net Promoter Score (NPS).

How to Analyze Responses in Ordinal Scale

Here’s how to analyze ordinal data effectively:

1. Descriptive analysis

a. Frequency Distribution

• Count and percentage of responses per category.

b. Mode & Median

• Mode: Most frequently occurring response.
• Median: Middle response when data is ordered.
• Avoid calculating the mean or standard deviation for ordinal data . It assumes equal intervals which don’t exist here.

2. Visualizing ordinal data

• Bar Chart: To show category counts.
• Stacked Bar Chart: For comparisons across groups.
• Box Plot: Displays median and interquartile range.

3. Statistical analysis

There are various statistical treatments of data to assess responses from ordinal scale. One test can compare two groups yet another test can compare more than two groups. Some models will predict an ordinal outcome while some will check for odds of responses falling in different categories.

4. AI & machine learning

If an ordinal scale survey includes open-ended questions, sentiment analysis and word cloud segregation can analyze responses. Merren’s AI-driven assessment offers a summary of emotional metrics.

Frequently Answered Questions (FAQs) About Ordinal Scales

What is an ordinal scale in surveys?

An ordinal scale ranks responses in a specific order without measuring the distance between them. For example, a survey might ask, “How satisfied are you?” with options from “Very satisfied” to “Very dissatisfied.”

How is an ordinal scale different from an interval scale?

An ordinal scale ranks data without equal intervals (e.g., satisfaction levels), while an interval scale has equal intervals but no true zero (e.g., temperature in Celsius).

What is the best scale for measuring opinions?

Ordinal scales, particularly Likert scales, are ideal for this purpose. It can assess attitudes, emotional metrics, preferences and purchasing behaviours. 

Can I calculate an average with ordinal scale data?

No, averages are unreliable because intervals between ranks aren’t equal. Use the median or mode instead.

Is a star rating survey an ordinal scale?

Yes, if it represents ordered preferences without precise distances between stars.

Conclusion

Create micro surveys and pulse surveys with ordinal scale questionnaires on Merren. Merren is a customer feedback tool that can create instant customer feedback campaigns in a few clicks. With AI-driven and conversational survey channels, increase your response rate with Merren. Sign up for a 14 day free trial.