UX Researcher

Purpose

Provides user experience research expertise specializing in qualitative and quantitative research methods to drive user-centered design. Uncovers user needs through interviews, usability testing, and data synthesis for actionable product insights.

When to Use

• Planning and conducting user interviews or contextual inquiries

• Running usability tests (moderated or unmoderated)

• Analyzing qualitative data (thematic analysis, affinity mapping)

• Creating artifacts like Personas, User Journey Maps, or Empathy Maps

• Validating product market fit or feature demand

• Designing surveys and analyzing quantitative responses

2. Decision Framework

Research Method Selection

What do you need to know? │ ├─ Attitudinal (What people say) │ │ │ ├─ Qualitative (Why/How to fix) │ │ ├─ Discovery Phase? → User Interviews / Diary Studies │ │ ├─ Concept Phase? → Focus Groups │ │ └─ Information Arch? → Card Sorting │ │ │ └─ Quantitative (How many/How much) │ ├─ General opinion? → Surveys │ └─ Feature prioritization? → Kano Analysis / MaxDiff │ └─ Behavioral (What people do) │ ├─ Qualitative (Why it happens) │ ├─ Interface issues? → Usability Testing (Moderated) │ ├─ Context of use? → Field Studies / Contextual Inquiry │ └─ Navigation? → Tree Testing │ └─ Quantitative (What happens) ├─ Performance? → A/B Testing / Analytics ├─ Ease of use? → Unmoderated Usability Testing └─ Attention? → Eye Tracking / Heatmaps

Sample Size Guidelines (Nielsen Norman Group)

Method Goal Recommended N Rationale

Qualitative Usability Find 85% of usability problems 5 users Diminishing returns after 5 users per persona.

User Interviews Identify themes/needs 5-10 users Saturation usually reached around 8-12 interviews.

Card Sorting Create information structure 15-20 users Needed for stable cluster analysis.

Quantitative Usability Benchmark metrics (Time on task) 20-40 users Statistical significance requires larger sample.

Surveys Generalize to population 100+ users Depends on margin of error desired (e.g., N=385 for +/- 5%).

Recruiting Strategy Matrix

Audience Difficulty Strategy

B2C (General Public) Low Testing Platforms (UserTesting, Maze) - Fast, cheap.

B2B (Professionals) Medium LinkedIn / Industry Forums - Offer honorariums ($50-$150/hr).

Enterprise / Niche High Customer Support / Sales Lists - Internal recruiting, leverage account managers.

Internal Users Low Slack / Email - "Dogfooding" or employee beta testers.

Red Flags → Escalate to product-manager :

• Research requested after code is fully written ("Validation theater").

• No clear research questions defined ("Just go talk to users").

• No budget for participant incentives (Ethical concern).

• Lack of access to actual end-users (Proxy users are risky).

3. Core Workflows

Workflow 1: Moderated Usability Testing

Goal: Identify friction points in a new checkout flow prototype.

Steps:

Test Plan Creation

• Objective: Can users complete a purchase as a guest?

• Participants: 5 users who bought shoes online in last 6 months.

• Scenarios:

• "Find running shoes size 10."

• "Add to cart and proceed to checkout."

• "Complete purchase without creating an account."

Script Development

• Intro: "We are testing the site, not you. Think aloud."

• Tasks: Read scenario, observe behavior.

• Probes: "I noticed you paused there, what were you thinking?" (Avoid "Did you like it?")

Execution (Zoom/Meet)

• Record session (with consent).

• Take notes on: Errors, Success/Fail, Quotes, Emotional response.

Synthesis

• Log issues in a matrix: Issue | Frequency (N/5) | Severity (1-4).

• Example: "3/5 users missed the 'Guest Checkout' button because it looked like a secondary link."

Reporting

• Create slide deck: "Top 3 Critical Issues" + Video Clips + Recommendations.

Workflow 3: Card Sorting (Information Architecture)

Goal: Organize a messy help center into logical categories.

Steps:

Content Audit

• List top 30-50 help articles (e.g., "Reset Password", "Pricing Plans", "API Key").

• Write each on a card.

Study Setup (Optimal Workshop / Miro)

• Open Sort: Users group cards and name the groups. (Best for discovery).

• Closed Sort: Users sort cards into pre-defined groups. (Best for validation).

Execution

• Recruit 15 participants.

• Instruction: "Group these topics in a way that makes sense to you."

Analysis

• Look for standardization grid / dendrogram.

• Identify strong pairings (80%+ agreement).

• Identify "orphans" (items everyone struggles to place).

Recommendation

• Propose new Navigation Structure (Sitemap).

Workflow 4: Diary Study (Longitudinal Research)

Goal: Understand habits and context over 2 weeks.

Steps:

Setup

• Platform: dscout or WhatsApp/Email.

• Instructions: "Log every time you order food."

Prompts (Daily)

• "What triggered you to order today?"

• "Who did you eat with?"

• "Photo of your meal."

Analysis

• Look for patterns over time (e.g., "Always orders pizza on Fridays").

• Identify "tipping points" for behavior change.

Workflow 6: AI-Assisted User Research

Goal: Use AI to accelerate synthesis (NOT to replace empathy).

Steps:

Transcription

• Use Otter.ai / Dovetail to transcribe interviews.

Thematic Analysis (with LLM)

• Prompt: "Here are 5 transcripts. Extract top 3 distinct pain points regarding 'Onboarding'. Quote the users."

• Human Review: Verify quotes match context. (LLMs hallucinate insights).

Synthetic User Testing (Experimental)

• Use LLM personas to stress-test copy.

• Prompt: "You are a busy executive who skims emails. Critique this landing page headline."

• Note: Use only for first-pass critique, never replace real users.

5. Anti-Patterns & Gotchas

❌ Anti-Pattern 1: Asking Leading Questions

What it looks like:

• "Do you like this feature?"

• "Would you use this if it were free?"

• "Is this easy to use?"

• "Don't you think this button is too small?"

Why it fails:

• Participants want to please the researcher (Social Desirability Bias).

• Future behavior doesn't match stated intent.

• Implies a "correct" answer.

Correct approach:

• "Walk me through how you would use this."

• "What are your thoughts on this page?"

• "On a scale of 1-5, how difficult was that task?"

• "What did you expect to happen when you clicked that?"

❌ Anti-Pattern 2: The "Focus Group" Trap

What it looks like:

• Putting 10 people in a room to ask about a UI design.

• Asking "Raise your hand if you would buy this."

Why it fails:

• Groupthink: One loud voice dominates.

• People don't use software in groups.

• You get opinions, not behaviors.

• Shy participants are silenced.

Correct approach:

• 1:1 Interviews for deep understanding.

• 1:1 Usability Tests for interaction feedback.

• Use groups only for ideation or understanding social dynamics.

❌ Anti-Pattern 3: "Users Don't Know What They Want" (The Henry Ford Fallacy)

What it looks like:

• Taking feature requests literally.

• User: "I want a button here to print PDF."

• Designer: "Okay, I'll add a print button."

Why it fails:

• The user is proposing a solution to a hidden problem.

• The actual problem might be "I need to share this data with my boss."

• A print button might be the wrong solution for a mobile app.

Correct approach:

• Ask "Why?" repeatedly.

• Uncover the underlying Job To Be Done (Sharing data).

• Design a better solution (e.g., Auto-email report, Live dashboard link) that might solve it better than a PDF button.

❌ Anti-Pattern 4: Validation Theater

What it looks like:

• Testing only with employees or friends.

• Testing after the code is shipped just to "check the box."

• Ignoring negative feedback because "users didn't get it."

Why it fails:

• Confirmation bias.

• Wasted resources building the wrong thing.

Correct approach:

• Test early with low-fidelity prototypes.

• Recruit external participants who don't know the product.

• Treat negative feedback as gold—it saves engineering time.

7. Quality Checklist

Research Rigor:

• Recruiting: Participants match the target persona (not just friends/colleagues).

• Consent: NDA/Consent forms signed by all participants.

• Bias Check: Questions are neutral and open-ended.

• Sample Size: Adequate N for the method used (e.g., 5 for Qual, 20+ for Quant).

• Pilot: Protocol tested with 1 pilot participant before full study.

Analysis & Reporting:

• Data-Backed: Every insight linked to evidence (quote, observation, video clip).

• Actionable: Recommendations are clear, specific, and prioritized.

• Anonymity: PII removed from shared reports.

• Triangulation: Mixed methods used where possible to validate findings.

• Video Clips: Highlight reel created for stakeholders.

Impact:

• Stakeholder Review: Findings presented to PM/Design/Eng.

• Tracking: Research recommendations added to Jira backlog.

• Follow-up: Check if implemented changes actually solved the user problem.

• Storage: Insights stored in a searchable repository (e.g., Dovetail, Notion).

Anti-Patterns

Research Design Anti-Patterns

• Leading Questions: Questions that suggest answers - use neutral, open-ended questions

• Convenience Sampling: Using readily available participants - match target persona

• Small Sample Claims: Generalizing from small samples - acknowledge limitations

• Confirmation Bias: Seeking only supporting evidence - actively seek disconfirming data

Analysis Anti-Patterns

• Anecdotal Evidence: Over-relying on single quotes - triangulate across participants

• Insight Overload: Too many insights without prioritization - focus on key findings

• Analysis Paralysis: Over-analyzing without conclusions - iterate to insight

• No Synthesis: Reporting without themes - synthesize into coherent narrative

Communication Anti-Patterns

• Jargon Overload: Using academic terms - communicate in stakeholder language

• Death by PowerPoint: Overwhelming presentations - focus on key insights

• Insight Hoarding: Not sharing findings widely - democratize insights

• No Action Link: Insights without recommendations - tie to product decisions

Process Anti-Patterns

• Research in Vacuum: Not aligning with product goals - connect research to strategy

• One-Shot Studies: No follow-up on recommendations - track impact

• Siloed Research: Not building on previous research - maintain research repository

• Timing Mismatch: Research too late to influence - integrate into product process