Understanding Reports

User Intuition automatically synthesizes your interview data into actionable reports. Reports transform hours of conversations into clear insights, recommendations, and supporting evidence.

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Accessing Reports

From your Study Dashboard:

1. Click the Reports tab
2. View the AI-generated analysis

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Report Structure

Reports are organized into several sections designed to take you from high-level findings to supporting detail:

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Executive Summary

A one- or two-paragraph overview of the most important findings, followed by a compact set of within-sample metrics. It communicates what the study found without mixing in the separate assessment of evidence adequacy.

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Total Participants

A clear count of how many interviews contributed to this report (e.g., “Total Participants (N): 1”). This helps you and your stakeholders understand the sample size behind the insights.

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Key Insights

A short list of the most significant, source-linked findings and material exceptions. Key Insights are synthesized from the same full cross-participant review used for Detailed Findings; they are not generated from a separate evidence source.

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Detailed Findings

Each Learning Goal contains numbered findings. Every finding separates its main point, within-sample prevalence, verbatims, observed impact, variation and exceptions, interpretation and limits, and decision relevance. Counts always include both the count and percentage—for example, 2 of 5 participants (40%). These percentages describe only the report sample; they are not population estimates. Example:

• Value is Price-Driven, Not Actively Tracked: The participant defines value as getting “bargains” and low prices, trusting the overall basket total reflects savings rather than performing explicit ROI calculations.
• Pharmacy Lacks Credibility: Despite using the pharmacy for convenience, the participant feels it lacks a “real health care experience” and desires more proactive counsel from staff.

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Detailed Analysis

In-depth exploration of findings organized by research objective or theme. Each section includes:

• Key observations: What the data shows
• Supporting evidence: Quotes and examples from interviews
• Implications: What this means for your business

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Recommendations

Zero to two justified next steps, each linked to an important evidence gap in the same report. If a material research gap is surfaced, the report must provide at least one linked next step. A valid empty list means the assessment found no actionable, decision-relevant research gap. An unavailable assessment is a different state. Recommendations require your existing review and launch approvals.

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Evidence Coverage

Evidence Coverage appraises the evidence behind Detailed Findings rather than repeating the findings. It describes the evidence available for each Learning Goal, coverage limitations, and the resulting decision boundary. The study-level sample-adequacy assessment explains what the included interviews can and cannot support and whether additional interviews would materially help. It considers the research purpose, participant specificity, depth, variation, alternatives and missing perspectives instead of applying a universal sample-size threshold. One prioritized gap list explains what remains unresolved and why it matters. Generic qualitative boundaries—such as not being able to estimate population prevalence or prove causal impact—remain decision boundaries unless the study purpose explicitly requires that decision. When report inputs are unchanged, regenerated reports reuse the last validated gap and linked recommendations. New interviews, plan edits, or generation-contract changes trigger a fresh assessment. Per-interview analysis remains available in Participant Responses and call evaluation, but is not aggregated into a separate study-level metric. Missing analysis does not automatically imply a need to recruit. These assessments are interpretations, not adequacy scores. You decide whether the evidence is sufficient for the intended decision. Older or revised plans explicitly identify inferred requirements or uncertain timing.

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Generating Reports

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Initial Report Generation

Reports can be generated on demand when usable interviews are available:

1. Navigate to the Reports tab
2. Click Generate Report (if no report exists yet)
3. Wait for the AI to analyze your interviews and produce the report

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Updating Reports

As more responses come in, you’ll need to regenerate the report to include new data:

1. Navigate to the Reports tab
2. Click Regenerate Report
3. The updated report will incorporate all completed interviews

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Working with Reports

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Public API structure

GET /api/public/v1/studies/{study_id}/report returns a small report-v2 overview by default. It includes identity, freshness, counts, a short summary, and available_sections. Pass ?view=study_findings, participant_profiles, participant_responses, evidence_coverage, recommended_next_steps, or references to fetch one section; pass ?view=full when the complete report is needed. included_sections identifies which sections were requested. based_on_interview_ids_included says whether the complete interview-ID list is present. The selectable sections contain:

• study_findings: executive summary and metrics plus learning_goals, each containing stable finding_id values that Evidence Coverage can reference
• participant_profiles: an array of profile questions with stable, heading-derived question_id values
• participant_responses: every report-eligible call’s overall_takeaways and learning_goal_responses
• recommended_next_steps
• evidence_coverage, containing its introductory text, sample_adequacy, per-goal learning_goal_evaluations, and prioritized evidence_gaps; recommendations link to these gaps through gap_ids

The public response intentionally omits the rendered report, Key Insights, duplicate open-question text, internal assessment fields, empty rendering wrappers, and presentation metadata such as Markdown, heading level, and display order. evidence_gaps.learning_goal_ids identifies the affected Learning Goal, and its finding_ids resolve directly to findings nested under that goal. New reports preserve the interview count, response analysis, evidence coverage, and recommendations from their generation snapshot. Later evidence or plan changes mark a report stale; reading it does not silently refresh its assessment. Legacy reports need regeneration to obtain evidence coverage. Each finding has a stable ID, reference_ids, and structured prevalence: { n, of } when the saved report states an explicit within-sample frequency. Its quotes[] identifies source references, public interview IDs, transcript turn IDs, and stored start times when available. Older findings can have null prevalence or empty quotes; the API does not infer missing evidence. Fetch ?view=references to resolve citation IDs, then get_interview for the source turn. Public report responses use interview_id as their interview join key. New reports are indexed for research search and cited answers. POST /api/public/v1/research/search/ searches canonical study plans and report objects across authorized studies. Search ranks candidates, but its content values are loaded from persisted Study/Report JSON. Results and index freshness are grouped under each entry in studies; check index_status separately from that study’s results array. Follow next_cursor with the same request to continue. POST /api/public/v1/research/answer/ generates an answer from accessible indexed evidence and returns validated source citations; inspect the cited records before using an exact quote.

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Sharing with Stakeholders

Reports are designed to be presentation-ready:

• Executive Summary for leadership and quick reviews
• Top Insights for team meetings and discussions
• Detailed Analysis for deep dives and planning sessions

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Using Quotes and Evidence

The report includes verbatim quotes from participants. Use these to:

• Build credibility for your findings
• Illustrate points in presentations
• Create empathy for customer perspectives

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Connecting to Transcripts

If you want to explore a finding more deeply:

1. Note the relevant insight from the report
2. Switch to the Calls tab
3. Review the source transcripts for additional context

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Report Quality

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Factors Affecting Report Quality

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How many interviews a report needs

Reports can generate from 2 interviews, but a report does not make a small sample broadly representative. Sample adequacy depends on the research purpose, how specific and relevant the participants are, interview depth, observed variation, unresolved alternatives, and whether the intended decision requires segment comparison or prevalence estimates. Evidence Coverage makes that boundary explicit and explains when additional interviews would materially help.

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Frequently Asked Questions