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. |

