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