Setting Up Study Details

Overview

The Study Details section is crucial for establishing the foundation of your research. High-quality, well-considered details will:

• Guide Interviewers: Help interviewers understand the study's purpose and objectives
• Improve Data Quality: Ensure consistent data collection across all interviews
• Enhance Analysis: Provide context for better interpretation of results
• Streamline Reporting: Make it easier to generate meaningful insights and reports

Core Study Details

1. Research Question

Purpose: Defines the central inquiry of your study

Best Practices: - Be specific and focused - Make it answerable through data collection - Ensure it aligns with your overall research goals - Example: "How do remote work policies affect employee productivity and job satisfaction in tech companies?"

2. Research Objectives

Purpose: Outlines what you aim to achieve with the study

Best Practices: - List 3-5 key objectives - Make them specific and measurable - Align with your research question - Example: - Identify key factors influencing remote work productivity - Measure employee satisfaction with current remote work policies - Document challenges faced in remote work environments

3. Target Population

Purpose: Defines who should participate in your study

Best Practices: - Be specific about demographics, roles, or characteristics - Consider inclusion/exclusion criteria - Example: "Full-time employees in tech companies (100+ employees) who have been working remotely for at least 6 months"

4. Study Description

Purpose: Provides an overview of your research

Best Practices: - Include context and background - Explain the study's importance - Describe the expected outcomes - Keep it concise but comprehensive

5. Methodology (Optional)

Purpose: Describes how the research will be conducted

Best Practices: - Specify data collection methods (interviews, surveys, etc.) - Mention any specific approaches or frameworks - Include details about data analysis methods if known

Methodology can be set when the study is created (Enter Manually) and over the API, but the Details page does not show it for editing afterwards.

6. Delivery settings

Set on the Details page rather than at creation time:

• Model Tier — which model conducts the interview, and what it costs per 5 questions
• Limit number of completed responses — the quota that closes the study
• Interview Modalities — voice and video links alongside text chat
• Session Recording — keep audio (and optionally video) of voice/video interviews; off by default

Known issue (September 2026). Session recording does not work in production: the interviewer cannot reach its recording storage, every upload fails, and participants are told "Recording has stopped working — the interview continues and your answers are still saved as text." Transcripts are unaffected. Leave the toggles off until this is fixed, and do not promise participants a recording in your consent text. - Redirect URL — where participants land after finishing. Put {{external_participant_id}} in it to hand a panel or CRM its own ID back — https://panel.example/done?pid={{external_participant_id}} — and it is replaced with the ID that interview arrived with (the ?participant_id= on its link, or a participant_id key in embed metadata), or with nothing if it arrived without one. See tagging a link.

Why Quality Matters

High-quality study details are essential for:

1. Better Interview Outcomes
2. Clear research questions lead to more focused interviews

3. Well-defined objectives help maintain consistency across interviewers

4. Improved Data Analysis

5. Clear objectives make it easier to code and analyze responses

6. Well-defined target population ensures data relevance

7. Time Efficiency

8. Reduces need for clarification during interviews
9. Minimizes data cleaning efforts during analysis

Common Pitfalls to Avoid

1. Vague Research Questions
2. ❌ Bad: "Study about remote work"

3. ✅ Good: "How do remote work policies affect employee productivity in mid-sized tech companies?"

4. Overly Broad Objectives

5. ❌ Bad: "Understand employee satisfaction"

6. ✅ Good: "Measure employee satisfaction with current remote work technology tools"

7. Poorly Defined Target Population

8. ❌ Bad: "People who work from home"
9. ✅ Good: "Full-time employees in companies with 100-1000 employees who work remotely at least 3 days per week"

Where these fields are used

• Questions — AI question generation reads the research question, objectives, methodology and target population
• Welcome message — drafting uses the title, description, duration, researcher name and contact
• Recruitment — the strategy suggester and flyer use the title, description and target population
• Analysis — thematic analysis is framed by the research question and objectives

Thin details produce thin generated content, which is the most common cause of vague AI output.

With MCP

update_study {"study_id": "…",
              "research_question": "…",
              "objectives": "…",
              "target_population": "…",
              "methodology": "…",
              "model_tier": "standard",
              "max_responses": 50}
get_study    {"study_id": "…"}

get_study also reports which lifecycle stages are configured — welcome set, screening and characteristics enabled with their question counts, and the main question count.

Next Steps

1. Review your entries for clarity and completeness
2. Add questions — see Study Questions
3. Write the welcome and consent message — see Welcome Message

Getting Help

• Browse the Help Center
• Contact support

Last updated: September 2026