CrowdPrisma

Automatically identifies and groups survey respondents into meaningful subgroups based on patterns in their responses without requiring predefined categories or manual coding. Uses NLP to discover natural clusters and segments within the respondent population.

Automatically analyzes and synthesizes open-ended survey responses into coherent summaries and key themes without requiring manual coding or predefined response categories. Extracts patterns and insights from unstructured text at scale.

Extracts actionable insights from survey data by identifying patterns, correlations, and meaningful findings across respondent groups and response types. Transforms raw survey data into business-relevant conclusions.

Automatically codes and categorizes qualitative survey responses without requiring manual thematic coding or predefined codebooks. Reduces the time-intensive process of manually reviewing and tagging open-ended responses.

Enables users to upload, organize, and manage survey data from various sources into the CrowdPrisma platform. Handles data ingestion and preparation for analysis.

Filters and analyzes survey responses based on respondent demographics and metadata to compare insights across different audience segments. Enables demographic-based analysis and comparison.

Automatically generates formatted reports and presentations of survey insights, findings, and recommendations. Creates shareable outputs suitable for stakeholder communication.

Compares and contrasts survey responses across different respondent groups, time periods, or survey versions to identify differences and patterns. Enables side-by-side analysis of how different segments respond.

Identifies recurring patterns, correlations, and relationships within survey feedback that might not be obvious through manual review. Discovers non-obvious connections between responses and respondent characteristics.