Transform unstructured customer feedback into actionable insights at scale
Customer feedback pours in from surveys, reviews, support tickets, and social media. Without proper coding, valuable insights get lost in the noise.
Feedback from multiple channels
Too much data to analyze manually
Insights buried in unstructured text
Survey Coder Pro processes feedback from any source, automatically categorizing themes and sentiment to surface what matters most to your customers.
Process feedback from any channel in one platform
Automatic theme detection and categorization
Sentiment analysis across all feedback types
Priority scoring for actionable insights
Everything you need to understand your customers
Upload feedback from surveys, reviews, tickets, or any text source.
AI discovers and organizes themes automatically from your data.
Understand emotional tone across all feedback categories.
Code thousands of responses in minutes, not days.
Export to Excel, SPSS, R, or Python for further analysis.
Automatic detection and filtering of spam and low-quality responses.
"We finally have a single view of customer feedback across all touchpoints. The AI categorization is remarkably accurate."
James Kim
VP of Customer Success, TechScale Inc
Almost every feedback tool today shows you a word cloud with the most mentioned terms. That's decoration, not analysis. The question that matters for product, CX, or marketing teams isn't "which words appear most" — it's:
Answering that requires structured codes, not keywords. And those codes need to be stable across waves so comparisons are real.
The score goes up or down, but without coding the open-ended questions the team doesn't know why. Coding mentions lets you cross drivers with the score: "detractors this quarter mention 'delivery delays' 3× more than last" is the kind of actionable insight operations teams can use.
High volume (10,000+ tickets/month at mid-size companies). Without standardized thematic coding, the product team only sees tickets that escalate to P1. Coding every ticket reveals trends in small recurring problems that individually don't escalate but together represent 40% of support cost.
App Store, Play Store, Google Maps, Trustpilot, or Mercadolibre reviews are public verbatims with positive bias (most rate 4-5 stars) and extreme-negative bias (1 star). The middle ground where the insight lives requires thematic coding to separate signal from noise.
A LATAM e-commerce CX team with ~12,000 quarterly verbatims (NPS + post-purchase + closed tickets) went from 2 people coding 4 days per quarter to 1 person coding 3 hours. The shift wasn't only about speed: the codebook stayed identical across waves, so quarterly comparisons became reliable. Before, changes between waves could be codebook drift; now they're real consumer changes.
Start coding open-ended responses with AI today. Free trial with 250 responses.