Canvs provides you rich emotional measurement for your open-ended dataset responses. However, sometimes the questions you've asked your respondents aren't framed in a way that maximize Emotional Reactions. 

At Canvs, we've worked with numerous clients to help them drive higher levels of emotional responses and longer form, richer answers from their respondents. 

We recommend these best practices in designing your open-ended dataset questions:

  • Focus on asking Why questions. Why is usually the trigger for emotional expression.

  • When developing your dataset questions, try to make it impossible to answer with "Yes"/"No" responses.

  • Followup, clarifying questions to a simple score often yield better responses. 

  • We've seen that people are more willing to provide longer form answers to support a score they give.

Here are some sample questions that may work for you:

"What would you like to see from {Your Movie, Book, Product, etc.}?"

  • Don't just ask your audience their opinion on one of your ideas – ask them to suggest ideas of their own.

"Why did you rate {1-5 rating of product} that way?"

  • Many datasets have included this type of question about a product. By asking them to provide the supporting proof points for a numeric score, we usually see longer responses and more Emotional Reactions.

"What is the top reason for your score?" (The classic followup question to the NPS survey)

  • This question is similar to the previous question, but specific to the NPS survey framework. We've actually seen some robust answers from this question when people upload the NPS/user engagement surveys, even with surveys about "boring" brands in the CPG category.

  • Asking your respondents for their "top" reason can be very effective at getting a focused response that still contains a lot of nuance.

We hope this additional context is helpful as you think through how to optimize your dataset to generate more emotional responses.

Any followup questions? Reach out to Canvs' Support team at

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