customer interview insight synthesizer
Transform messy interview transcripts into traceable, structured research artifacts with de-identified evidence IDs.
$5
Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
GitHub Copilot
Gemini CLI+20 moreClaude CodeCursorCodex CLIGitHub CopilotGemini CLI
OpenClaw
Manus
Grok+17 agentscustomer interview insight synthesizer
Example session with this skill installed
Analyze these three interview transcripts for our new project management tool. Focus on how they handle task prioritization and identify any gaps in our current understanding.
- Read your context and instructions
- Compiled the customer interview insight
- Generated the data export
I have processed the transcripts for P01, P02, and P03. I have de-identified the participants, categorized 14 unique evidence units, and mapped three primary themes regarding task prioritization.
User Research Synthesis: Project Management Tool
Participant Overview
| Evidence ID | Segment | Source | Notes |
|---|---|---|---|
| P01 | Engineering Lead | transcript_01.txt | Focuses on sprint velocity |
| P02 | Product Manager | transcript_02.txt | Focuses on stakeholder alignment |
| P03 | Freelance Designer | transcript_03.txt | Focuses on deadline visualization |
Evidence Map
| Theme | Evidence IDs | Strength |
|---|---|---|
| Manual Workarounds | E001, E005, E009 | STRONG |
| Visual Hierarchy Needs | E002, E011 | MODERATE |
| Notification Fatigue | E004, E007, E012 | STRONG |
Key Findings (Selected)
Behavior (E001, E005): P01 and P02 both maintain a separate "Urgent" spreadsheet outside the tool because the internal priority flags are "too noisy."
- Opinion (E009): P03 stated that "color-coding is more important than a numerical priority score."
Interpretation: Users distrust the tool's built-in priority logic, leading to data fragmentation in external sheets.
Contradictions
- P01 vs P03: P01 requires strict stack-ranking (E003), while P03 prefers fluid, visual grouping (E010).
Opportunity Hypotheses
H01: IF we implement a drag-and-drop "Custom Sort" view, THEN users like P01 and P02 will stop using external spreadsheets BECAUSE they currently lack a way to override system-generated priorities (E001, E005).
Gap Register
- G01: We lack evidence on how users prioritize tasks across multiple concurrent projects.
- G02: No data on how automated priority triggers (e.g., Jira sync) affect user trust.
Next steps
- Review the Opportunity Hypotheses with the engineering team to assess feasibility of H01.
- Schedule two additional interviews with Agency Owners to address G01.
- Archive the Raw Evidence Index in the project repository for future audit.
customer-interview-insight-synthesizer.csv
CSV · data export
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
User research often results in messy transcripts and vague summaries that blur the line between what users actually did and what the researcher thinks they meant. This lack of rigor leads to product decisions based on misinterpreted opinions or "cherry-picked" quotes rather than traceable behavioral data.
What it does
- Extracts raw interview data into a structured registry with stable, de-identified evidence IDs.
- Categorizes every finding strictly as BEHAVIOR, OPINION, or INTERPRETATION to prevent analytical bias.
- Maps contradictions and negative cases where participants disagree, avoiding false consensus.
- Generates testable opportunity hypotheses directly linked to specific evidence IDs for full auditability.
- Maintains a formal Gap Register to track unknowns and underrepresented segments.
Why this beats prompting it yourself
Generic prompts usually summarize away the nuances, losing the raw evidence needed for defensible product specs. This skill enforces a systematic research methodology that separates observation from inference, ensuring you don't over-quantify qualitative data or ignore outliers that could invalidate your strategy.
Use cases
- Synthesizing 10+ hours of discovery call transcripts into a prioritized opportunity backlog.
- Auditing customer feedback to identify where different user segments have conflicting needs.
- Building a traceable research repository where every product requirement can be tracked back to a specific user quote or action.
- Validating internal assumptions by explicitly looking for negative cases in existing interview notes.
Known limitations
Does not perform statistical significance testing. Quantification is restricted to descriptive counts of the provided sample.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
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