Learning Goals

After you submit your research brief, the AI analyzes it and creates 2-5 learning objectives. Each objective represents a distinct area of inquiry — a key theme or topic your research aims to explore.

For example, a brief about checkout drop-off might produce objectives like:

• Understand perceived friction in the checkout flow
• Explore pricing and value perception
• Identify trust and security concerns

The flow builder gives you full control over your study structure:

• Drag and drop to reorder objectives and questions
• Edit inline — click any objective title or question text to modify it
• Add new objectives with the "Add Objective" button
• Add questions to any objective using the "Add Item" dropdown
• Delete any objective or question you don't need

Each question belongs to an objective. This grouping serves two purposes:

• During the interview — the AI understands the context and intent behind each question, producing better follow-up probes
• During analysis — transcripts are organized by objective, making it easy to compare responses across participants for each research goal

Questions are generated per objective, calibrated to your study's format and duration:

• Voice studies default to open-ended questions with follow-up probes, since conversational depth is the goal
• WhatsApp studies use a mix of open-ended and structured questions (single-select, rating scales) since participants type responses
• Duration calibration — the AI adjusts the number of questions and follow-up depth to fit your target interview length

You can regenerate questions for any objective at any time, or add your own manually.