Our Quality Engine automatically filters low-quality responses.
Focus on insights, not data cleaning.
Every response is evaluated on three core dimensions.
We measure how thoroughly a respondent engaged with the question. Responses that provide rich context, specific examples, and detailed reasoning score higher than brief, surface-level answers.
"It's good."
"The product itself is great, but the onboarding was confusing because the tutorial showed features that aren't on my plan..."
Quality responses reference specific features, moments, or experiences. We prioritize feedback that includes concrete examples, named features, or particular use cases.
"The app is confusing."
"The checkout flow on mobile is frustrating. After I add items to cart, hitting 'back' clears my cart completely..."
Does the feedback explain context, impact, or suggest solutions? Responses score higher when they include reasoning or potential paths forward.
"Support is terrible."
"The support chat only shows agents available from 9-5 EST. Adding evening hours would let customers like me actually get help..."
Why manual analysis fails at scale, and how Sentic solves it.
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