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Synthesis workflow
Learn how to use AI clustering in Leapfrog for automated data analysis and insight extraction
Synthesis Workflow
Leapfrog provides an AI-powered workflow for qualitative research, enabling efficient progression from raw interviews to actionable insights. The following steps outline the synthesis process:
1. Interview
- Conduct and record user interviews or research sessions to collect qualitative data (audio or video).
2. Transcribing
- Upload recordings to Leapfrog.
- The platform transcribes audio and video into text, supporting multiple languages and offering options for redaction and filler word removal.
3. Coding
- Use coding tools to tag and categorize key themes, concepts, and patterns in transcripts.
- Coding organizes complex conversations into manageable insights.
4. Canvas
- Move coded data onto the Canvas for visual mapping and clustering.
- Organize quotes, notes, and themes; use AI-powered clustering to group related data points.
5. Chat
- Use the AI-powered chat to ask questions, generate summaries, and receive feedback on your data.
- The chat feature provides contextual answers based on your research data.
6. Analytics
- Visualize findings with charts and reports.
- Use analytics tools to communicate insights with your team and stakeholders.
Workflow Summary
Leapfrog’s workflow enables you to:
- Capture and transcribe qualitative data
- Code and organize key themes
- Visualize relationships and patterns
- Interact with data using AI chat
- Analyze and present findings
This integrated workflow supports efficient, collaborative, and AI-powered qualitative research synthesis.