Ordinal Scale Questions: Definition and Examples

Data collection is at the heart of informed decision-making in any thriving business or organization. Whether your goal is to improve your current offerings, choose new products to launch, develop a marketing campaign, gauge customer satisfaction, increase customer retention, or grow your revenue, understanding the attitudes, opinions, and preferences of your target audience is a necessary first step.

Ordinal survey questions are meant to gather that exact kind of data — nuanced insights into how your audience feels about all aspects of your organization.

In this article, we’ll explain what the ordinal scale is, discuss how you can use it, share examples of ordinal scale survey questions, consider advantages and disadvantages of the ordinal scale, and look at how you can use Jotform to create your own ordinal scale survey.

Why the survey question type you select is important

Posing the right kind of questions in a survey is key because the question type determines the kind of data you’ll be able to collect — and that will, in turn, determine the data analysis you’ll be able to do. There are several question types you can employ; you’ll likely use a mix of them in your survey.

For example, you might use both nominal and ordinal scale survey questions, among others.

Nominal scale questions can help you categorize demographic data that doesn’t need to be ranked, like age, income, or education level. Ordinal survey questions allow you to rank audience attitudes and opinions about new products, recent customer service experiences, employee satisfaction, and a host of other important business performance indicators.

If measuring attitudes and opinions is the goal of your survey, you’ll want to include ordinal survey questions.

How the ordinal scale helps measure data

The ordinal scale is the second of four levels of measurement (nominal, ordinal, interval, and ratio) used to measure and classify data. An ordinal scale arranges data in a specific order and assigns a rank to each variable.

Here’s an example of an ordinal scale question: “How would you rate your recent customer service experience on a scale of 1–5, with 1 being extremely satisfied and 5 being not at all satisfied?”

Ordinal scale rankings provide insights into customer attitudes, preferences, and behaviors based on a hierarchical order of responses.

How you can use the ordinal scale

The ordinal scale is useful for measuring nonmathematical concepts like satisfaction or happiness, pain, agreement, likelihood, importance, quality, and so on.

Ordinal survey questions are most useful for collecting qualitative data on the attitudes, opinions, preferences, and perspectives of your target audience about particular topics.

They’re also useful for ranking different variables. For example, if a respondent chooses “satisfied” over “very satisfied” in answer to a customer service question, an ordinal scale helps establish a precise difference between those two responses.

Let’s consider some ordinal survey question use cases:

  • Ask respondents to rate their interest in a potential new product on a five-item scale from “very interested” to “not at all interested” to help determine whether to create and launch the product.
  • Measure employee performance relative to other employees by asking how a certain employee’s productivity compares to that of other team members: more productive, less productive, or just as productive. This will help identify areas of improvement.
  • Gauge perceptions about your brand by asking respondents to indicate whether they find a series of statements “false,” “mostly false,” “neutral,” “mostly true,” or “true.” This data can help inform new branding and marketing initiatives.
  • Ask respondents to rate customer service satisfaction on a five-item scale from “very satisfied” to “very dissatisfied” so you can identify changes that will help improve the customer experience.
  • Evaluate the likelihood that your current customers will recommend your business on a scale of “very likely” to “not at all likely.” You can use this information to improve customer retention.
  • Ask your target audience how often they use different social media platforms on a scale of “extremely often” to “not at all.” You can then gauge which social media channels to consistently create content for.
  • Assess levels of agreement by asking respondents how much they agree with a statement on a scale of “strongly disagree” to “strongly agree.” The data can help you understand audience sentiment about new policy initiatives, for example.

An example ordinal survey question for respondents to rate customer service satisfaction.

What ordinal scale questions look like in practice

Let’s take a look at some examples of ordinal scale survey questions across different use cases and disciplines, including market research, employee satisfaction, and customer sentiment.

Please rank the importance of the following factors from 1 (most important) to 5 (least important) when considering an offer of employment:

  • Salary and benefits
  • Opportunity for advancement
  • Company culture
  • Vacation time
  • Responsibilities and workload

Thinking about your current experience at our company, how satisfied are you with growth opportunities?

  • Extremely satisfied
  • Moderately satisfied
  • Neither satisfied nor dissatisfied
  • Moderately dissatisfied
  • Extremely dissatisfied

Please rank the importance of the following reasons from 1–5, with 1 being the most important, when deciding whether to attend our marketing conference:

  • Speakers
  • Breakout sessions and topics
  • Career growth opportunities
  • Conference location
  • Budget/cost considerations

Please rank the most effective methods for promoting your products or services on a scale of 1–5, with 1 being the most effective:

  • Word of mouth
  • Email marketing
  • Live events and conferences
  • LinkedIn
  • Facebook

On a scale of 1–5, with 1 being extremely happy and 5 being extremely unhappy, how would you rate your last experience staying at our hotel?

Thinking about your recent experience dining at our restaurant, how satisfied were you with the service you received on a scale of 1–5 (with 1 being very satisfied and 5 being very unsatisfied)?

Which most influences your purchasing decision when buying new software? Please rank the following in order from most important to least important:

  • Ease of use
  • Security
  • Reliability
  • Cost
  • Support and maintenance
  • Integration with existing systems
  • Availability of product information
  • Brand reputation
  • Recommendations from colleagues

On a scale of 1–5, how would you rate the user-friendliness of our software?

How likely are you to buy additional products from us in the future?

  • Very likely
  • Somewhat likely
  • Unsure
  • Unlikely
  • Very unlikely

How would you describe your feelings about [name of elected official]?

  • Very positive
  • Positive
  • Neutral/no opinion
  • Negative
  • Very negative

How likely are you to vote for [name of elected official] in the upcoming election?

  • Very likely
  • Somewhat likely
  • Unsure
  • Unlikely
  • Very unlikely

Advantages and disadvantages of using ordinal survey questions

Ordinal survey questions offer several advantages:

  • They measure attitudes, opinions, and perceptions. Because ordinal survey questions allow respondents to share their level of agreement, happiness, and similar sentiments on an ordered scale, you can collect nuanced qualitative data about attitudes and opinions.
  • Interpreting the data is straightforward. Ordinal survey questions provide an ordered, easy-to-understand array of answer options, making meaningful responses more likely and the resulting data easier to analyze.
  • Survey respondents are more likely to stay engaged, leading to higher completion rates. With their multiple choice or rating format, ordinal survey questions are simple to answer, ensuring that respondents stay engaged and complete the survey.

There are also disadvantages to using ordinal survey questions:

  • They don’t provide context. While the information you gather provides insights into respondents’ attitudes and opinions, it doesn’t offer reasons or context for their responses.
  • It’s difficult to compare responses. Because responses like “somewhat likely” or “somewhat agree” mean different things to different people depending on their individual experiences, it’s difficult to compare responses.

However, you can mitigate these disadvantages by using additional survey question types.

How Jotform makes creating ordinal scale surveys easy

A Likert scale is one of the most popular types of ordinal scales. It’s easy to use this type of scale in your surveys with Jotform’s free Likert scale creator, and you don’t need to know how to code to do it.

Whether you’re gathering feedback or research data, you can easily add a Likert rating scale to your online form and take advantage of Jotform’s full suite of features, including conditional logic, autoresponders, auto-generated reports, and more.

If you don’t want to build your Likert scale form from scratch, you can choose one of over 1,300 ready-made survey templates and customize it to fit your needs. Some of our ready-made Likert scale templates include our employee motivation survey, job satisfaction survey, and camper satisfaction survey, to name just three. Simply drag and drop to add new survey questions, change Likert scale response anchors, upload your logo, and more.

Discover the benefits of a Likert scale survey and learn how to create one.


Kimberly Houston is a conversion-focused marketing copywriter. She loves helping established creative service providers attract and convert their ideal clients with personality-driven web and email copy, so they can stand out online, and get more business, bookings, and sales.

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