The Questions section of your Dashboard lets you view a statistical breakdown of Survey Responses based on the questions included in your Survey Templates.
This feature helps you track trends, analyze open-ended responses, and identify areas for improvement by examining feedback at the question level.
🔍 Introduction
This article walks you through:
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How questions and Question Keys appear on the Dashboard
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How to navigate the Dashboard > Questions tab
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Important notes about unique keys across templates
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Advanced functionality like Sentiment Analysis
🧩 What Is a Question Key?
Every question in AskNicely has a unique Question Key that identifies it across Survey Templates. This is especially helpful when analyzing responses.
In the screenshot below, the question “If you could change one thing about our service, what would it be?” has the Question Key: change_one_thing.
📋 Viewing Questions in the Dashboard
To view your survey question data:
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Go to Dashboard > Questions
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Select the All filter to see every question with responses.
⚠️ Key Reminder About Unique Keys
If you use multiple Survey Templates, but want to report on a specific question in just one of them:
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Make sure it has a unique Question Key
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Question Keys are global — they are not template-specific
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Duplicate keys across templates will aggregate data together
📂 Drilling into a Specific Question
Once on the Questions page, you’ll see all Questions that have at least one response. For example, "Change One Thing" is now listed as a separate line item.
Clicking the name will open a detailed view of all responses for that question.
⚙️ Actions: Rearranging or Archiving
Click the ACTIONS dropdown in the top right of the Questions tab to:
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Rearrange your Dashboard question order
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Archive a Question you no longer need
💡 Advanced Feature: Sentiment Analysis
To unlock Sentiment Analysis, your Survey Template must have at least one Open-ended question with the key comment. Any additional open-ended questions will also be analyzed for sentiment.
Sentiment Analysis uses a machine-learning algorithm to evaluate each answer's tone:
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Positive
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Neutral
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Negative
This helps you assess the emotional tone of feedback at scale.
For example, in the screenshot below, the question "What did we miss that you expected us to do?" resulted in:
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13% Positive
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71% Neutral
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16% Negative
🔗 Read how Sentiment Analysis is calculated
🔗 Learn more about Sentiment Analysis accuracy
🙋♀️ We’d Love Your Feedback
Have thoughts on improving the Dashboard > Questions feature set?