> ## Documentation Index > Fetch the complete documentation index at: https://www.pickfu.com/llms.txt > Use this file to discover all available pages before exploring further. # What is a Likert Scale question and when should I use it? > Likert Scale questions ask respondents to rate 2-8 statements on an agreement, frequency, or satisfaction scale and explain their ratings in a comment. A Likert Scale question asks respondents to rate several statements on the same scale, such as from "Strongly Disagree" to "Strongly Agree", and then leave a comment explaining their ratings. Use it when you want to measure attitudes, habits, or satisfaction across multiple statements at once. Instead of asking a separate question for each idea, a Likert Scale question groups 2 to 8 related statements together. Respondents rate each statement independently, so you can compare them side by side. [See an example Likert Scale question](https://app.pickfu.com/results/wwCpI853OY?tab=responses-uTRK1cbTGj) # When should I use a Likert Scale question? Likert Scale questions work best when you want to measure how strongly people feel about several related statements. They're ideal for: * **Brand perception** – how strongly do people agree that your brand is trustworthy, affordable, or innovative? * **Product claims** – which benefits or claims do shoppers believe? * **Shopping habits** – how often do people buy online, read reviews, or use coupons? * **Customer satisfaction** – how satisfied are people with price, quality, shipping, or support? If you want respondents to pick a favorite from a set of options, use a [Single Select question](/help/what-is-a-single-select-poll-and-when-should-i-use-it) or [Ranked question](/help/what-is-a-ranked-poll-and-when-should-i-use-it) instead. # Choosing a scale When you build a Likert Scale question, you choose one of four rating scales. Every statement in the question uses the same scale. | Scale | Rating options | | - | - | | **5-point agreement** | Strongly Disagree, Disagree, Neutral, Agree, Strongly Agree | | **7-point agreement** | Strongly Disagree, Disagree, Somewhat Disagree, Neutral, Somewhat Agree, Agree, Strongly Agree | | **Frequency** | Never, Rarely, Sometimes, Often, Always | | **Satisfaction** | Very Dissatisfied, Dissatisfied, Neutral, Satisfied, Very Satisfied | Use an agreement scale for opinions and claims, frequency for behaviors, and satisfaction for experiences with a product or service. # How to create a Likert Scale question 1. **Start a new survey** – click the **New survey** button from your dashboard 2. **Choose Likert Scale** – select it from the question type menu 3. **Write your prompt** – the default prompt is "Respond to each of the following statements." You can edit it to add more direction. 4. **Choose a scale type** – pick 5-point agreement, 7-point agreement, frequency, or satisfaction 5. **Add your statements** – enter 2 to 8 text statements. Click **Add statement** to add more. 6. **Target your audience** – choose demographics that match your target market 7. **Preview and launch** – review your survey, then launch to start collecting feedback Respondents rate each statement on the scale, then write a comment explaining their ratings. **Via MCP:** AI assistants connected to the [PickFu MCP server](/docs/integrations/mcp-server#likert-questions) can create Likert Scale questions with the `save_survey` and `mini_poll` tools. **Tip:** Write each statement as a single, clear idea. For example, write "This product looks durable" instead of "This product looks durable and affordable." Combining two ideas makes the rating hard to interpret. # How to read your Likert Scale results Once responses arrive, you'll see: * **Mean** – the average rating for each statement, so you can quickly compare statements * **Response distribution** – a chart showing how many respondents chose each point on the scale for each statement * **Written feedback** – comments from each respondent explaining their ratings Likert Scale response distribution chart for four statements on a 5-point agreement scale, with the mean rating for each statement Look for statements with a high mean and a tight distribution. Those are the statements your audience rates most consistently highly on the selected scale. Statements with split distributions are worth digging into through the comments. # Frequently asked questions ## How many statements can I include? You can include 2 to 8 statements in a single Likert Scale question. ## Can I use images or videos as statements? No. Likert Scale statements are text only. To show respondents an image or video, add it as context to the question. ## Does the number of statements affect the price? Yes. Your survey's price summary shows a separate Likert line item based on how many statements you add. ## Can I use a Likert Scale question to branch my survey? Not currently. Likert Scale questions can't be used as the source question for [branch logic](/help/how-do-i-use-branch-logic-in-my-survey). You can still add a Likert Scale question to a survey that uses branch logic, and you can set it to show only to respondents who gave a specific answer to an earlier question. *** Related Articles * [Which question type should I use?](/help/which-poll-type-should-i-use) * [How do I write good survey questions?](/help/how-do-i-write-good-survey-questions) * [What is a Van Westendorp price test and when should I use it?](/help/what-is-a-van-westendorp-price-test-and-when-should-i-use-it) * [How do I use branch logic in my survey?](/help/how-do-i-use-branch-logic-in-my-survey) ## Related topics - [What is a Van Westendorp price test and when to use it?](/help/what-is-a-van-westendorp-price-test-and-when-should-i-use-it.md) - [How do I use branch logic in my survey?](/help/how-do-i-use-branch-logic-in-my-survey.md) - [PickFu Help Center](/help.md) - [What is a Star Rating question and when should I use it?](/help/what-is-a-star-rating-poll-and-when-should-i-use-it.md) - [What is a Ranked question and when should I use it?](/help/what-is-a-ranked-poll-and-when-should-i-use-it.md) This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.