A customer clicks 3 out of 5 stars on a resolved ticket and moves on. No comment, no context, nothing your team can act on. You now have a data point that tells you almost nothing: not what went wrong, not what would've made it a 5, not whether "3" means "fine, I guess" or "actively annoyed but couldn't be bothered to type it out." Multiply that by every mid-range score you've ever collected, and you've got a report full of numbers with no explanation attached to most of them.
The instinct is usually to add a comment box next to the rating and hope people use it. Some will. Most won't — a star click takes one second, a written explanation takes thirty, and most customers will take the fast exit unless something's genuinely bothering them enough to type. Which means your comment data skews toward extremes and your middle-of-the-road scores stay permanently unexplained.
The Real Problem: Not Every Question Wants a Number
CSAT and NPS are built around a score for a reason — "how satisfied were you" and "how likely are you to recommend us" are genuinely quantitative questions. You want a trend line. You want to track whether this month is better than last month. A number is the right tool.
But teams often reuse that same rating-first pattern for questions that were never quantitative to begin with:
"What would you like to see next?" — There's no meaningful scale for a feature request. Forcing someone through a star rating before they can tell you what they actually want just adds friction to a question that was always going to be answered in words.
"Was this documentation page helpful, and if not, what's missing?" — A thumbs-up-or-down or star rating can tell you the page failed, but not why. The value in a "not helpful" click is entirely in the follow-up text, and if the rating step feels like the whole ask, most people skip the part that would've actually told you something.
A general "tell us anything" feedback channel. Some teams want a low-friction way to catch a specific complaint or observation with no formal survey structure attached — closer to a suggestion box than a satisfaction metric.
In each of these, the score isn't measuring anything real. It's just a UI convention borrowed from CSAT, and it's standing between the customer and the thing you actually wanted to know.
The Fix: Configure the Survey to Skip the Score
When you create a Feedback Survey, the Field Type setting controls how a response is captured, and one of the three available options is built exactly for this situation: None. Instead of a star Rating or a 0–10 Number Pick, a None field type collects a comment only — no quantitative input at all. There's nothing to click before typing, which means the written response is the entire interaction rather than an afterthought tacked onto a score.
This isn't a workaround — it's a first-class configuration. The Calculation Strategy setting mirrors it: choosing None here means no mathematical calculation is performed on the survey at all, and your reports simply display the raw responses and comments rather than trying to compute an average or trend from data that was never numeric to begin with.
It also changes what you see in the Reports tab. A scored survey gives you a rolling average graph and a feedback-volume-by-rating breakdown. A None-type survey skips both of those — since there's no score to trend — and shows you the Public Survey Link plus a straightforward list of individual feedback items, which you can filter by date. That's not a limitation so much as the report matching the question: you asked for opinions, not a metric, so the report gives you opinions, not a chart.
If you're not ready to go fully scoreless, there's a middle ground worth knowing about. On a Rating or Number Pick survey, the Comments Enabled toggle in Additional Settings gives customers an optional text box alongside their score, so they can explain a low rating if they choose to. It's the same idea in a lighter form — but because it's optional, expect the same skew as before: mostly your most frustrated or most delighted customers will actually use it. A dedicated None-type survey removes that filter entirely, since typing is the only way to respond at all.
Where to Actually Use This
Don't replace your CSAT or NPS survey with a comment-only one — you'd lose the trend line that makes those metrics useful in the first place. Instead, run them side by side, matched to what each question is really asking:
Keep your transactional CSAT and relational NPS surveys scored, because you genuinely want to track whether those numbers move over time. Reach for a None-type survey anywhere you were asking an open question and forcing it through a rating widget out of habit — a feature-request box, a "help us understand what's missing" prompt on a knowledge base article, or a general suggestions channel that was never meant to produce a chart. In practice, this usually means a second, separate Feedback Survey configured specifically for that purpose, rather than trying to make one survey serve two different jobs.
The Takeaway
Before you set up your next feedback touchpoint, ask what you're actually going to do with the response. If the answer is "track it on a graph over time," you want a score. If the answer is "read what they wrote and act on it," a scored survey is adding a step that doesn't help you and might be costing you the written answer you actually wanted. Configure the Field Type — and the Calculation Strategy that goes with it — to match the question, not the other way around.