Pulse Classifier is Smartinterview’s AI tool for coding open-ended survey responses. Instead of manually reading and tagging thousands of verbatim answers, you upload your data, let the AI propose a topic code plan, review and refine it, then run classification across your full dataset. Results export to Excel with structured topic sheets ready for analysis. Use Pulse Classifier when you have open-ended survey questions — either from an Excel or SPSS file you already own, or from a Smartinterview survey you ran — and need to turn free-text answers into structured, countable topic codes.Documentation Index
Fetch the complete documentation index at: https://docs.smartinterview.ai/llms.txt
Use this file to discover all available pages before exploring further.
End-to-end workflow
Upload your data
Upload an Excel (
.xlsx / .xls) or SPSS (.sav) file, or connect directly to an existing Smartinterview survey question. You then map which sheet, respondent ID column, and response text column to use.Upload data →Generate topics
Click Generate Topics to let the AI read a sample of your responses and propose a topic code plan. Review the suggested topics, rename or delete any that don’t fit, add your own, and optionally expand any topic into L1/L2 sub-topics.Define and manage topics →
Configure and classify
Set classification depth, tolerance, and maximum codes per response. Run a preview classification on a small sample to validate topic quality, then launch the full classification job and monitor progress in real time.Classify responses →
Export and analyze
Download results as Excel — your original data plus topic assignment columns, a Topics summary sheet, and a Top Topics sheet. Explore topic distributions, co-occurrence heatmaps, and sentiment summaries directly in the platform.Export results →
When to use Pulse Classifier
Pulse Classifier is best suited for:- Survey open-ends — Net Promoter Score verbatims, satisfaction open-ends, “Why did you choose us?” questions, and similar free-text fields collected in Excel or via Smartinterview.
- Large response volumes — Hundreds to tens of thousands of responses where manual coding would take days.
- Iterative coding projects — When you need to refine topic definitions over multiple rounds or reuse a topic frame across survey waves.
- Multi-column files — Files with several open-ended columns that each need their own classification plan.
Key concepts
| Term | Definition |
|---|---|
| Topic | A thematic code assigned to a response (e.g., “Price”, “Customer service”). |
| L1 / L2 | Classification depth. L1 = top-level topics only. L2 = L1 parent topics with sub-topics beneath them. |
| Tolerance | Controls how strictly the AI applies topic rules. Lower values are more conservative; higher values are more inclusive. |
| Consensus | The AI runs multiple classification passes per response and keeps only topics that appear in enough passes, improving accuracy. |
| FilesQO | The primary output sheet in the Excel export — one row per response with all assigned topic columns. |