Semi-Structured User Research Interview

Template Overview

Generative user research uncovers the underlying motivations, unspoken frustrations, and mental models that drive human behavior. When product teams rely solely on quantitative analytics, they see what users clicked—but have no idea why they clicked, what they struggled with, or what they wished they could accomplish instead.

Conducting semi-structured user interviews requires balancing open-ended exploration with systematic note-taking. Without a structured synthesis template, research notes become disorganized transcripts that teams never revisit.

This template organizes qualitative discovery: participant background, core workflow observations, verbatim customer quotes, unexpected pain points, and strategic product opportunities.

Markdown Template Structure

Copy the block below or click Download .md File to add this template directly to your personal vault:

---
title: "User Research Interview: [Participant ID / Role]"
date: [YYYY-MM-DD]
participant_id: "P-104"
participant_role: "Staff Infrastructure Engineer"
researcher: "[[Lead UX Researcher]]"
study_name: "Developer Meeting Documentation & Vault Workflows"
participant_segment: "Privacy-Conscious Senior Engineers"
tags: [ux-research, user-interview, qualitative, discovery, research]
---

# User Research Interview: [Participant ID / Role] — [YYYY-MM-DD]

## 1. Participant Profile & Tooling Ecosystem
- **Work Context:** Leads a 12-person distributed infrastructure team across 4 time zones.
- **Current Software Stack:** macOS, Obsidian for personal notes, terminal-based CLI tools, Zoom for meetings.
- **Core Friction:** Spends 2 hours every Monday manually reviewing scattered meeting notes to reconstruct architectural decisions.

## 2. Current Workflow & Observational Inquiries
- **How do you document architecture meetings today?**
  - "I take rapid Markdown notes in my daily scratchpad, but when discussions move fast, I miss exact parameters and quotes."
- **How do you handle cloud meeting transcription bots?**
  - "Our security team explicitly bans them. We work on cryptographic key management; an unvetted cloud bot recording our screens would get us audited."

## 3. Highlighted Verbatim Quotes
> [!NOTE] Verbatim Quote: Privacy Mandate
> "If an app requires me to send my meeting audio to an external server, I cannot use it. Period. It doesn't matter how pretty the UI is. Data sovereignty is not a preference for us; it's a legal requirement."

> [!NOTE] Verbatim Quote: Plain Text Freedom
> "I need my notes to be plain Markdown files on my Mac. I refuse to lock my knowledge inside another proprietary database that requires a monthly subscription just to search my own thoughts."

## 4. Key Pain Points & Frustrations
1. High cognitive fatigue from trying to participate in technical debates while simultaneously typing meeting notes.
2. Existing cloud transcription tools produce massive, unstructured walls of text rather than crisp Markdown summaries.
3. Fear of accidental third-party data leaks when discussing confidential systems code.

## 5. Strategic Product Implications & Opportunities
- **Opportunity 1:** Develop automated Markdown table formatters that summarize meeting metrics without cloud dependencies.
- **Opportunity 2:** Create one-click vault templates that organize architectural decisions into standard ADR formats.
- [ ] Tag video clip timestamps for research highlight reel.
- [ ] Share quote synthesis in upcoming product design review.

Filled Real-World Example

Here is a realistic example demonstrating how this template captures actual deliberations:

---
title: "Research: P-104 Infrastructure Lead"
date: 2026-10-06
participant_id: "P-104"
researcher: "[[Kiran Shah]]"
tags: [ux-research, interview]
---

# Research: P-104 Infrastructure Lead — October 6, 2026

## 1. Summary
Participant confirmed strict corporate ban on cloud meeting bots. Highlighted urgent need for on-device local transcription.

## 2. Key Quote
"Data sovereignty is not a preference; it's our compliance requirement."

## 3. Product Impact
Validates high demand for local-first desktop audio processing.

When to Use and When to Avoid

When to Use

• Use during 45-60 minute generative user research interviews and customer discovery sessions.
• Use to capture qualitative mental models, workflow observations, and verbatim participant quotes.
• Use to feed user insights into product requirements documents (PRDs) and design roadmaps.

When to Avoid

• Avoid using for quantitative surveys or statistical A/B testing analysis.
• Avoid using for transactional pre-sales discovery calls (use [[sales-discovery-call]]).

On-Device AI Integration

Capture generative user research sessions with Oyma on macOS:

Analyze the qualitative user research interview transcript:
1. Synthesize the participant's background, professional tooling stack, and daily workflow context.
2. Extract highlighted verbatim participant quotes that illustrate core emotional frustrations or motivations.
3. Group observed customer pain points into prioritized thematic clusters.
4. Record strategic product opportunities and design implications for the engineering team.
Output in clean, empathetic CommonMark.

Your research participants’ confidential workflow disclosures and private thoughts remain secure on your Mac.