Survey Response Analysis Agent
Aggregates open-ended and scored survey responses across channels, clusters recurring themes, and produces a ranked summary of drivers behind satisfaction scores.
Teams collect customer and employee survey data through multiple tools but rarely have time to read every open-text comment, so qualitative insight gets reduced to a single average score that hides the real drivers of satisfaction or dissatisfaction
Manually coding hundreds or thousands of free-text responses into themes is slow and inconsistent between analysts
This agent ingests survey exports from all connected channels, applies theme clustering to open-text responses, and correlates recurring themes against quantitative scores to identify what is actually moving the needle
It produces a ranked list of positive and negative drivers with representative verbatim quotes, so stakeholders see both the 'what' and the 'why' in one report
The agent pulls raw survey response exports from connected survey tools, normalizing scored and open-text fields into a unified schema. It applies natural language clustering to group open-text responses into recurring themes, then statistically correlates theme presence with satisfaction score movement to rank drivers by impact. The agent generates a summary report with theme rankings, representative verbatim quotes, and wave-over-wave trend comparisons, distributed to stakeholders on a configured cadence.
Ingest Responses
- Pull raw response exports from connected survey platforms
- Normalize scored and open-text fields into a unified schema
- Deduplicate and filter incomplete or low-effort responses
- Tag responses with segment metadata (role, region, tenure)
Cluster Themes
- Apply semantic clustering to open-text responses
- Label clusters with representative theme names
- Merge near-duplicate themes across response batches
- Tag each theme as sentiment-positive or sentiment-negative
Correlate with Scores
- Statistically correlate theme presence with satisfaction score
- Rank themes by impact on overall score movement
- Compare theme prevalence across segments
- Identify emerging themes versus the prior survey wave
Report and Distribute
- Compile ranked drivers with representative verbatim quotes
- Generate wave-over-wave trend comparison
- Distribute the report to configured stakeholders
- Flag critical negative themes for immediate follow-up