Ordinal survey questions Polling Errors

Ordinal survey questions


Table of Contents

What is an ordinal scale?

Capturing people’s responses in a way it will be of better use to your research is the most challenging thing. Especially when the survey runs deep and long. Sometimes you just want to get quick one word or direct measurable answers to most of the questions and don’t expect the respondents to reply with long paragraphs. In such cases, ordinal scales really come handy. 

An ordinal or ordered scale helps you to study the respondents’ attitudes towards your research topic through a defined set of ordered responses or answer options provided with the question itself. You might have come across a lot of survey questions with options like: “very good” “good” “average” “bad” “very bad”. This is the ordinal scale. 

The ordinal scale basically presents the respondent with answer options to choose from depending on which one suits their views and opinions the most. The only limitation is that sometimes the meaning is unclear between similar options like “very satisfied” and “satisfied. It can be relative but not exact.

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When to use ordinal survey questions?

  • Nuanced opinions: Do respondents “agree” or “strongly agree” with a take on an issue?
  • Perceptions: Do respondents find a particular statement “false,” “mostly false,” “mostly true,” or “true”?
  • Relative performance: Is a certain employee “more productive,” “just as productive,” or “less productive” than other employees?
  • Gauge sentiment: Is a customer “very satisfied,” “satisfied,” “dissatisfied,” or “very dissatisfied” with a recent purchase?


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Designing ordinal survey questions

Ordinal survey questions are the ones where the answer options provided are ranked according to their significance or importance depending on the questions. 

1. Choose the question type

There are two basic types of ordinal survey questions:

Unipolar: has one dimension and the zero point at the end of the scale.

Ordinal survey questions Polling Errors

Bipolar: has two dimensions and the zero point is in the middle of the scale.

Ordinal survey questions Polling Errors

2. Choosing a scale length 

Ordinal questions are said to have 2 to more than 100 options, but the key to choosing a perfect scale for your questions lies in how much of a detailed answer you wish to have. 

Ideally, it is ok to have 4 or 5 answer options for each question. 

More options: it will create more generic and nuance between responses and will leave you with more data to analyze in the end. 

Fewer options: it will be lighter on response load and there will be a low chance of respondents skipping the questions just because it looked like a “burden” 

It is advised to have 5-7 options for bipolar ordinal scales and 4-5 options for unipolar ordinal scales. 

3. Starting the scale

The common question that arises when people start to frame ordinal survey questions is “should I start with positive or negative options?” everyone gets too sceptical regarding whether the first options influence the respondents choice or not. The truth is it doesn’t matter. Research has proved that keeping the positive option “very satisfied” or the negative option “very dissatisfied” does not make any effect on how the respondents actually feel about the question asked. 

So the key here is to choose whichever option you want to put first, but be consistent. Make sure you follow the same pattern through the survey. 

4. Using direct labels

Any ordinal question looks like this:

How would you agree/disagree with the fact that our website assures data security? 

  • Strongly agree
  • Somewhat agree
  • Neutral 
  • Somewhat disagree
  • Strongly disagree 

The problem here is, you will get your answer and it is although a very easy practice to copy-paste the options all over the survey. But directing the options to the construct of interest will help you get more focused and specific answers. This practice will also help you in the data analysis and the cognitive load of the responses. So the construct of interest focused questions would look like this:

 How secure or insecure is our website regarding your data? 

  • Strongly secure
  • Somewhat secure
  • Neutral 
  • Somewhat insecure
  • Strongly insecure

5. Specific metrics

Make sure to use specific metrics or measures to your questions rather than having vague and confusing quantifiers. Example:

How often do you exercise?

  • Regularly
  • Occasionally 
  • Rarely 
  • Never 

Now, these quantifiers are going to be interpreted differently by different respondents. For some the meaning of “rarely” and “occasionally” might mean the same. In such cases, it is helpful to be more specific with your questions and the ordinal scale. Example:

How often have you exercised in the past week?

  • Several hours a day
  • Every day for a short time
  • Alternate days
  • Never 

This gives a frame of reference to the respondents and measure their exercise routine and match it to the suitable given options. 

6. Balanced scale

Most of the time especially in bipolar scales, the ordinal survey questions have a scale that is not equally balanced for the respondents to choose their option from. Example: 

How would you rate our customer service?

  • Excellent 
  • Very good
  • Good
  • Fair
  • Poor 

As you can see, the first three options imply the “positive” response while it is a 5 pointer scale. Hence, making it an unbalanced ordinal scale. This gives the respondents very few to no options to choose from if they have a negative response or something slightly less. 

The more appropriate way to frame this question is:

How would you rate our customer service? 

  • Very good 
  • Good 
  • Average 
  • Poor 
  • Very poor

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Examples of ordinal scale questions

In this section, we will see some commonly used ordinal survey questions and patterns:

  1. How would you rate the efficiency of our products?
  • Very efficient 
  • Somewhat efficient 
  • Neither efficient nor inefficient 
  • Somewhat inefficient 
  • Very inefficient 
  1. Metric questions 
Ordinal survey questions Polling Errors
  1. How much are you satisfied with our work environment?
  • Extremely satisfied 
  • Moderately satisfied 
  • Slightly satisfied
  • Neither satisfied nor dissatisfied 
  • Slightly dissatisfied 
  • Moderately dissatisfied
  • Extremely dissatisfied 
Ordinal survey questions Polling Errors
  1. How many connections do you have on LinkedIn?
  • More than 1000
  • Between 500-1000
  • Between 100-500
  • Less than 100

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