Software UX Research Skill — Quick Reference
Use this skill to identify problems/opportunities and de-risk decisions. Use software-ui-ux-design to implement UI patterns, component changes, and design system updates.
Dec 2025 Baselines (Core)
When to Use This Skill
- Discovery: user needs, JTBD, opportunity sizing, mental models.
- Validation: concepts, prototypes, onboarding/first-run success.
- Evaluative: usability tests, heuristic evaluation, cognitive walkthroughs.
- Quant/behavioral: funnels, cohorts, instrumentation gaps, guardrails.
- Research Ops: intake, prioritization, repository/taxonomy, consent/PII handling.
- Demographic research: Age-diverse, cultural, accessibility participant recruitment.
- A/B testing: Experiment design, sample size, analysis, pitfalls.
When NOT to Use This Skill
- UI implementation → Use software-ui-ux-design for components, patterns, code
- Analytics instrumentation → Use marketing-product-analytics for tracking plans and qa-observability for implementation patterns
- Accessibility compliance audit → Use accessibility-specific checklists (WCAG conformance)
- Marketing research → Use marketing-social-media or related marketing skills
- A/B test platform setup → Use experimentation platforms (Statsig, GrowthBook, LaunchDarkly)
Operating Mode (Core)
If inputs are missing, ask for:
- Decision to unblock (what will change based on this research).
- Target roles/segments and top tasks.
- Platforms and contexts (web/mobile/desktop; remote/on-site; assisted tech).
- Existing evidence (analytics, tickets, reviews, recordings, prior studies).
- Constraints (timeline, recruitment access, compliance, budget).
Default outputs (pick what the user asked for):
- Research plan + output contract (prefer ../software-clean-code-standard/assets/checklists/ux-research-plan-template.md; use assets/research-plan-template.md for skill-specific detail)
- Study protocol (tasks/script + success metrics + recruitment plan)
- Findings report (issues + severity + evidence + recommendations + confidence)
- Decision brief (options + tradeoffs + recommendation + measurement plan)
Method Chooser (Core)
Research Types (Keep Explicit)
| Type |
Goal |
Primary Outputs |
| Discovery |
Understand needs and context |
JTBD, opportunity areas, constraints |
| Validation |
Reduce solution risk |
Go/no-go, prioritization signals |
| Evaluative |
Improve usability/accessibility |
Severity-rated issues + fixes |
Decision Tree (Fast)
What do you need?
├─ WHY / needs / context → interviews, contextual inquiry, diary
├─ HOW / usability → moderated usability test, cognitive walkthrough, heuristic eval
├─ WHAT / scale → analytics/logs + targeted qual follow-ups
└─ WHICH / causal → experiments (if feasible) or preference tests
Method Selection Table (Practical)
| Question |
Best methods |
Avoid when |
Output |
| What problems matter most? |
Interviews, contextual inquiry, diary |
Only surveys/analytics |
Problem framing + evidence |
| Can users complete key tasks? |
Moderated usability tests, task analysis |
Stakeholder review |
Task success + issue list |
| Is navigation findable? |
Tree test, first-click, card sort |
Extremely small audience [Inference] |
IA changes + labels |
| What is happening at scale? |
Funnels, cohorts, logs, support taxonomy |
Instrumentation missing |
Baselines + segments + drop-offs |
| Which variant performs better? |
A/B, switchback, holdout |
Insufficient power or high risk |
Decision with confidence + guardrails |
Research by Product Stage
Stage Framework (What to Do When)
| Stage |
Decisions |
Primary Methods |
Secondary Methods |
Output |
| Discovery |
What to build and for whom |
Interviews, field/diary, journey mapping |
Competitive analysis, feedback mining |
Opportunity brief + JTBD |
| Concept/MVP |
Does the concept work? |
Concept test, prototype usability |
First-click/tree test |
MVP scope + onboarding plan |
| Launch |
Is it usable + accessible? |
Usability testing, accessibility review |
Heuristic eval, session replay |
Launch blockers + fixes |
| Growth |
What drives adoption/value? |
Segmented analytics + qual follow-ups |
Churn interviews, surveys |
Retention drivers + friction |
| Maturity |
What to optimize/deprecate? |
Experiments, longitudinal tracking |
Unmoderated tests |
Incremental roadmap |
Post-Launch Measurement (What to Track)
| Metric category |
What it answers |
Pair with |
| Adoption |
Are people using it? |
Outcome/value metric |
| Value |
Does it help users succeed? |
Adoption + qualitative reasons |
| Reliability |
Does it fail in ways users notice? |
Error rate + recovery success |
| Accessibility |
Can diverse users complete flows? |
Assistive-tech coverage + defect trends |
Research for Complex Systems (Workflows, Admin, Regulated)
Complexity Indicators
| Indicator |
Example |
Research Implication |
| Multi-step workflows |
Draft → approve → publish |
Task analysis + state mapping |
| Multi-role permissions |
Admin vs editor vs viewer |
Test each role + transitions |
| Data dependencies |
Requires integrations/sync |
Error-path + recovery testing |
| High stakes |
Finance, healthcare |
Safety checks + confirmations |
| Expert users |
Dev tools, analytics |
Recruit real experts (not proxies) |
Evaluation Methods (Core)
- Contextual inquiry: observe real work and constraints.
- Task analysis: map goals → steps → failure points.
- Cognitive walkthrough: evaluate learnability and signifiers.
- Error-path testing: timeouts, offline, partial data, permission loss, retries.
- Multi-role walkthrough: simulate handoffs (creator → reviewer → admin).
Multi-Role Coverage Checklist
Research Ops & Governance (Core)
Intake (Make Requests Comparable)
Minimum required fields:
- Decision to unblock and deadline.
- Research questions (primary + secondary).
- Target users/segments and recruitment constraints.
- Existing evidence and links.
- Deliverable format + audience.
Prioritization (Simple Scoring)
Use a lightweight score to avoid backlog paralysis:
- Decision impact
- Knowledge gap
- Timing urgency
- Feasibility (recruitment + time)
Repository & Taxonomy
- Store each study with: method, date, product area, roles, tasks, key findings, raw evidence links.
- Tag for reuse: problem type (navigation/forms/performance), component/pattern, funnel step.
- Prefer “atomic” findings (one insight per card) to enable recombination [Inference].
Consent, PII, and Access Control
Follow applicable privacy laws; GDPR is a primary reference for EU processing https://eur-lex.europa.eu/eli/reg/2016/679/oj
PII handling checklist:
Research Democratization (2026 Trend)
Research democratization is a recurring 2026 trend: non-researchers increasingly conduct research. Enable carefully with guardrails.
| Approach |
Guardrails |
Risk Level |
| Templated usability tests |
Script + task templates provided |
Low |
| Customer interviews by PMs |
Training + review required |
Medium |
| Survey design by anyone |
Central review + standard questions |
Medium |
| Unsupervised research |
Not recommended |
High |
Guardrails for non-researchers:
Measurement & Decision Quality (Core)
Research ROI Quick Reference
| Research Activity |
Proxy Metric |
Calculation |
| Usability testing finding |
Prevented dev rework |
Hours saved × $150/hr |
| Discovery interview |
Prevented build-wrong-thing |
Sprint cost × risk reduction % |
| A/B test conclusive result |
Improved conversion |
(ΔConversion × Traffic × LTV) - Test cost |
| Heuristic evaluation |
Early defect detection |
Defects found × Cost-to-fix-later |
Rules of thumb:
- 1 usability finding that prevents 40 hours of rework = $6,000 value
- 1 discovery insight that prevents 1 wasted sprint = $50,000-100,000 value
- Research that improves conversion 0.5% on 100k visitors × $50 LTV = $25,000/month
Triangulation Rubric
| Confidence |
Evidence requirement |
Use for |
| High |
Multiple methods or sources agree |
High-impact decisions |
| Medium |
Strong signal from one method + supporting indicators |
Prioritization |
| Low |
Single source / small sample |
Exploratory hypotheses |
Adoption vs Value (Avoid Vanity Metrics)
| Metric type |
Example |
Common pitfall |
| Adoption |
Feature usage rate |
“Used” ≠ “helpful” |
| Value/outcome |
Task success, goal completion |
Harder to instrument |
When NOT to Run A/B Tests
| Situation |
Why it fails |
Better method |
| Low power/traffic |
Inconclusive results |
Usability tests + trends |
| Many variables change |
Attribution impossible |
Prototype tests → staged rollout |
| Need “why” |
Experiments don’t explain |
Interviews + observation |
| Ethical constraints |
Harmful denial |
Phased rollout + holdouts |
| Long-term effects |
Short tests miss delayed impact |
Longitudinal + retention analysis |
Common Confounds (Call Out Early)
- Selection bias (only power users respond).
- Survivorship bias (you miss churned users).
- Novelty effect (short-term lift).
- Instrumentation changes mid-test (metrics drift).
Optional: AI/Automation Research Considerations
Use only when researching automation/AI-powered features. Skip for traditional software UX.
2026 benchmark: Trend reports consistently highlight AI-assisted analysis. Use AI for speed while keeping humans responsible for strategy and interpretation. Example reference: https://www.lyssna.com/blog/ux-research-trends/
Key Questions
| Dimension |
Question |
Methods |
| Mental model |
What do users think the system can/can’t do? |
Interviews, concept tests |
| Trust calibration |
When do users over/under-rely? |
Scenario tests, log review |
| Explanation usefulness |
Does “why” help decisions? |
A/B explanation variants, interviews |
| Failure recovery |
Do users recover and finish tasks? |
Failure-path usability tests |
Error Taxonomy (User-Visible)
| Failure type |
Typical impact |
What to measure |
| Wrong output |
Rework, lost trust |
Verification + override rate |
| Missing output |
Manual fallback |
Fallback completion rate |
| Unclear output |
Confusion |
Clarification requests |
| Non-recoverable failure |
Blocked flow |
Time-to-recovery, support contact |
Optional: AI-Assisted Research Ops (Guardrailed)
- Use automation for transcription/tagging only after PII redaction.
- Maintain an audit trail: every theme links back to raw quotes/clips.
Synthetic Users: When Appropriate (2026)
Trend reports frequently mention synthetic/AI participants. Use with clear boundaries. Example reference: https://www.lyssna.com/blog/ux-research-trends/
| Use Case |
Appropriate? |
Why |
| Early concept brainstorming |
WARNING: Supplement only |
Generate edge cases, not validation |
| Scenario/edge case expansion |
PASS Yes |
Broaden coverage before real testing |
| Moderator training/practice |
PASS Yes |
Practice without participant burden |
| Hypothesis generation |
PASS Yes |
Explore directions to test with real users |
| Validation/go-no-go decisions |
FAIL Never |
Cannot substitute lived experience |
| Usability findings as evidence |
FAIL Never |
Real behavior required |
| Quotes in reports |
FAIL Never |
Fabricated quotes damage credibility |
Critical rule: Synthetic outputs are hypotheses, not evidence. Always validate with real users before shipping.
Navigation
Resources
Core Research Methods:
- references/research-frameworks.md — JTBD, Kano, Double Diamond, Service Blueprint, opportunity mapping
- references/ux-audit-framework.md — Heuristic evaluation, cognitive walkthrough, severity rating
- references/usability-testing-guide.md — Task design, facilitation, analysis
- references/ux-metrics-framework.md — Task metrics, SUS/HEART, measurement guidance
- references/customer-journey-mapping.md — Journey mapping and service blueprints
- references/pain-point-extraction.md — Feedback-to-themes method
- references/review-mining-playbook.md — B2B/B2C review mining
Demographic & Quantitative Research (NEW):
- references/demographic-research-methods.md — Inclusive research for seniors, children, cultures, disabilities
- references/ab-testing-implementation.md — A/B testing deep-dive (sample size, analysis, pitfalls)
Competitive UX Analysis & Flow Patterns:
- references/competitive-ux-analysis.md — Step-by-step flow patterns from industry leaders (Wise, Revolut, Shopify, Notion, Linear, Stripe) + benchmarking methodology
Data & Sources:
- data/sources.json — Curated external references
Domain-Specific UX Benchmarking
IMPORTANT: When designing UX flows for a specific domain, you MUST use WebSearch to find and suggest best-practice patterns from industry leaders.
Trigger Conditions
- "We're designing [flow type] for [domain]"
- "What's the best UX for [feature] in [industry]?"
- "How do [Company A, Company B] handle [flow]?"
- "Benchmark our [feature] against competitors"
- Any UX design task with identifiable domain context
Domain → Leader Lookup Table
| Domain |
Industry Leaders to Check |
Key Flows |
| Fintech/Banking |
Wise, Revolut, Monzo, N26, Chime, Mercury |
Onboarding/KYC, money transfer, card management, spend analytics |
| E-commerce |
Shopify, Amazon, Stripe Checkout |
Checkout, cart, product pages, returns |
| SaaS/B2B |
Linear, Notion, Figma, Slack, Airtable |
Onboarding, settings, collaboration, permissions |
| Developer Tools |
Stripe, Vercel, GitHub, Supabase |
Docs, API explorer, dashboard, CLI |
| Consumer Apps |
Spotify, Airbnb, Uber, Instagram |
Discovery, booking, feed, social |
| Healthcare |
Oscar, One Medical, Calm, Headspace |
Appointment booking, records, compliance flows |
| EdTech |
Duolingo, Coursera, Khan Academy |
Onboarding, progress, gamification |
Required Searches
When user specifies a domain, execute:
- Search:
"[domain] UX best practices 2026"
- Search:
"[leader company] [flow type] UX"
- Search:
"[leader company] app review UX" site:mobbin.com OR site:pageflows.com
- Search:
"[domain] onboarding flow examples"
What to Report
After searching, provide:
- Pattern examples: Screenshots/flows from 2-3 industry leaders
- Key patterns identified: What they do well (with specifics)
- Applicable to your flow: How to adapt patterns
- Differentiation opportunity: Where you could improve on leaders
Example Output Format
DOMAIN: Fintech (Money Transfer)
BENCHMARKED: Wise, Revolut
WISE PATTERNS:
- Upfront fee transparency (shows exact fee before recipient input)
- Mid-transfer rate lock (shows countdown timer)
- Delivery time estimate per payment method
- Recipient validation (bank account check before send)
REVOLUT PATTERNS:
- Instant send to Revolut users (P2P first)
- Currency conversion preview with rate comparison
- Scheduled/recurring transfers prominent
APPLY TO YOUR FLOW:
1. Add fee transparency at step 1 (not step 3)
2. Show delivery estimate per payment rail
3. Consider rate lock feature for FX transfers
DIFFERENTIATION OPPORTUNITY:
- Neither shows historical rate chart—add "is now a good time?" context
Trend Awareness Protocol
IMPORTANT: When users ask recommendation questions about UX research, you MUST use WebSearch to check current trends before answering.
Tool/Trend Triggers
- "What's the best UX research tool for [use case]?"
- "What should I use for [usability testing/surveys/analytics]?"
- "What's the latest in UX research?"
- "Current best practices for [user interviews/A/B testing/accessibility]?"
- "Is [research method] still relevant in 2026?"
- "What research tools should I use?"
- "Best approach for [remote research/unmoderated testing]?"
Tool/Trend Searches
- Search:
"UX research trends 2026"
- Search:
"UX research tools best practices 2026"
- Search:
"[Maze/Hotjar/UserTesting] comparison 2026"
- Search:
"AI in UX research 2026"
Tool/Trend Report Format
After searching, provide:
- Current landscape: What research methods/tools are popular NOW
- Emerging trends: New techniques or tools gaining traction
- Deprecated/declining: Methods that are losing effectiveness
- Recommendation: Based on fresh data and current practices
Example Topics (verify with fresh search)
- AI-powered research tools (Maze AI, Looppanel)
- Unmoderated testing platforms evolution
- Voice of Customer (VoC) platforms
- Analytics and behavioral tools (Hotjar, FullStory)
- Accessibility testing tools and standards
- Research repository and insight management
Templates
- Shared plan template: ../software-clean-code-standard/assets/checklists/ux-research-plan-template.md — Product-agnostic research plan template (core + optional AI)
- assets/research-plan-template.md — UX research plan template
- assets/testing/usability-test-plan.md — Usability test plan
- assets/testing/usability-testing-checklist.md — Usability testing checklist
- assets/audits/heuristic-evaluation-template.md — Heuristic evaluation
- assets/audits/ux-audit-report-template.md — Audit report
1---2name: software-ux-research3description: Use when conducting user research (interviews, usability tests, surveys, A/B tests) or designing research studies. Covers discovery, validation, evaluative methods, research ops, governance, and measurement for software experiences.4---5
6# Software UX Research Skill — Quick Reference
7
8Use this skill to identify problems/opportunities and de-risk decisions. Use `software-ui-ux-design` to implement UI patterns, component changes, and design system updates.
9
10---
11
12## Dec 2025 Baselines (Core)
13
14- **Human-centred design**: Iterative design + evaluation grounded in evidence (ISO 9241-210:2019) https://www.iso.org/standard/77520.html
15- **Usability definition**: Effectiveness, efficiency, satisfaction in context (ISO 9241-11:2018) https://www.iso.org/standard/63500.html
16- **Accessibility baseline**: WCAG 2.2 is a W3C Recommendation (12 Dec 2024) https://www.w3.org/TR/WCAG22/
17- **WCAG 3.0 preview**: Working Draft published Sep 2025; introduces Bronze/Silver/Gold conformance tiers and enhanced cognitive accessibility; not expected before 2028-2030 https://www.w3.org/WAI/standards-guidelines/wcag/wcag3-intro/
18- **EU shipping note**: European Accessibility Act applies to covered products/services after 28 Jun 2025 (Directive (EU) 2019/882) https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32019L0882
19
20## When to Use This Skill
21
22- Discovery: user needs, JTBD, opportunity sizing, mental models.
23- Validation: concepts, prototypes, onboarding/first-run success.
24- Evaluative: usability tests, heuristic evaluation, cognitive walkthroughs.
25- Quant/behavioral: funnels, cohorts, instrumentation gaps, guardrails.
26- Research Ops: intake, prioritization, repository/taxonomy, consent/PII handling.
27- **Demographic research**: Age-diverse, cultural, accessibility participant recruitment.
28- **A/B testing**: Experiment design, sample size, analysis, pitfalls.
29
30## When NOT to Use This Skill
31
32- **UI implementation** → Use [software-ui-ux-design](../software-ui-ux-design/SKILL.md) for components, patterns, code
33- **Analytics instrumentation** → Use [marketing-product-analytics](../marketing-product-analytics/SKILL.md) for tracking plans and [qa-observability](../qa-observability/SKILL.md) for implementation patterns
34- **Accessibility compliance audit** → Use accessibility-specific checklists (WCAG conformance)
35- **Marketing research** → Use [marketing-social-media](../marketing-social-media/SKILL.md) or related marketing skills
36- **A/B test platform setup** → Use experimentation platforms (Statsig, GrowthBook, LaunchDarkly)
37
38---
39
40## Operating Mode (Core)
41
42If inputs are missing, ask for:
43
44- Decision to unblock (what will change based on this research).
45- Target roles/segments and top tasks.
46- Platforms and contexts (web/mobile/desktop; remote/on-site; assisted tech).
47- Existing evidence (analytics, tickets, reviews, recordings, prior studies).
48- Constraints (timeline, recruitment access, compliance, budget).
49
50Default outputs (pick what the user asked for):
51
52- Research plan + output contract (prefer [../software-clean-code-standard/assets/checklists/ux-research-plan-template.md](../software-clean-code-standard/assets/checklists/ux-research-plan-template.md); use [assets/research-plan-template.md](assets/research-plan-template.md) for skill-specific detail)
53- Study protocol (tasks/script + success metrics + recruitment plan)
54- Findings report (issues + severity + evidence + recommendations + confidence)
55- Decision brief (options + tradeoffs + recommendation + measurement plan)
56
57---
58
59## Method Chooser (Core)
60
61### Research Types (Keep Explicit)
62
63| Type | Goal | Primary Outputs |
64|------|------|-----------------|
65| Discovery | Understand needs and context | JTBD, opportunity areas, constraints |
66| Validation | Reduce solution risk | Go/no-go, prioritization signals |
67| Evaluative | Improve usability/accessibility | Severity-rated issues + fixes |
68
69### Decision Tree (Fast)
70
71```text
72What do you need?
73 ├─ WHY / needs / context → interviews, contextual inquiry, diary
74 ├─ HOW / usability → moderated usability test, cognitive walkthrough, heuristic eval
75 ├─ WHAT / scale → analytics/logs + targeted qual follow-ups
76 └─ WHICH / causal → experiments (if feasible) or preference tests
77```
78
79### Method Selection Table (Practical)
80
81| Question | Best methods | Avoid when | Output |
82|----------|--------------|------------|--------|
83| What problems matter most? | Interviews, contextual inquiry, diary | Only surveys/analytics | Problem framing + evidence |
84| Can users complete key tasks? | Moderated usability tests, task analysis | Stakeholder review | Task success + issue list |
85| Is navigation findable? | Tree test, first-click, card sort | Extremely small audience [Inference] | IA changes + labels |
86| What is happening at scale? | Funnels, cohorts, logs, support taxonomy | Instrumentation missing | Baselines + segments + drop-offs |
87| Which variant performs better? | A/B, switchback, holdout | Insufficient power or high risk | Decision with confidence + guardrails |
88
89---
90
91## Research by Product Stage
92
93### Stage Framework (What to Do When)
94
95| Stage | Decisions | Primary Methods | Secondary Methods | Output |
96|-------|-----------|-----------------|-------------------|--------|
97| Discovery | What to build and for whom | Interviews, field/diary, journey mapping | Competitive analysis, feedback mining | Opportunity brief + JTBD |
98| Concept/MVP | Does the concept work? | Concept test, prototype usability | First-click/tree test | MVP scope + onboarding plan |
99| Launch | Is it usable + accessible? | Usability testing, accessibility review | Heuristic eval, session replay | Launch blockers + fixes |
100| Growth | What drives adoption/value? | Segmented analytics + qual follow-ups | Churn interviews, surveys | Retention drivers + friction |
101| Maturity | What to optimize/deprecate? | Experiments, longitudinal tracking | Unmoderated tests | Incremental roadmap |
102
103### Post-Launch Measurement (What to Track)
104
105| Metric category | What it answers | Pair with |
106|----------------|------------------|----------|
107| Adoption | Are people using it? | Outcome/value metric |
108| Value | Does it help users succeed? | Adoption + qualitative reasons |
109| Reliability | Does it fail in ways users notice? | Error rate + recovery success |
110| Accessibility | Can diverse users complete flows? | Assistive-tech coverage + defect trends |
111
112---
113
114## Research for Complex Systems (Workflows, Admin, Regulated)
115
116### Complexity Indicators
117
118| Indicator | Example | Research Implication |
119|-----------|---------|----------------------|
120| Multi-step workflows | Draft → approve → publish | Task analysis + state mapping |
121| Multi-role permissions | Admin vs editor vs viewer | Test each role + transitions |
122| Data dependencies | Requires integrations/sync | Error-path + recovery testing |
123| High stakes | Finance, healthcare | Safety checks + confirmations |
124| Expert users | Dev tools, analytics | Recruit real experts (not proxies) |
125
126### Evaluation Methods (Core)
127
128- Contextual inquiry: observe real work and constraints.
129- Task analysis: map goals → steps → failure points.
130- Cognitive walkthrough: evaluate learnability and signifiers.
131- Error-path testing: timeouts, offline, partial data, permission loss, retries.
132- Multi-role walkthrough: simulate handoffs (creator → reviewer → admin).
133
134### Multi-Role Coverage Checklist
135
136- [ ] Role-permission matrix documented.
137- [ ] “No access” UX defined (request path, least-privilege defaults).
138- [ ] Cross-role handoffs tested (notifications, state changes, audit history).
139- [ ] Error recovery tested for each role (retry, undo, escalation).
140
141---
142
143## Research Ops & Governance (Core)
144
145### Intake (Make Requests Comparable)
146
147Minimum required fields:
148
149- Decision to unblock and deadline.
150- Research questions (primary + secondary).
151- Target users/segments and recruitment constraints.
152- Existing evidence and links.
153- Deliverable format + audience.
154
155### Prioritization (Simple Scoring)
156
157Use a lightweight score to avoid backlog paralysis:
158
159- Decision impact
160- Knowledge gap
161- Timing urgency
162- Feasibility (recruitment + time)
163
164### Repository & Taxonomy
165
166- Store each study with: method, date, product area, roles, tasks, key findings, raw evidence links.
167- Tag for reuse: problem type (navigation/forms/performance), component/pattern, funnel step.
168- Prefer “atomic” findings (one insight per card) to enable recombination [Inference].
169
170### Consent, PII, and Access Control
171
172Follow applicable privacy laws; GDPR is a primary reference for EU processing https://eur-lex.europa.eu/eli/reg/2016/679/oj
173
174PII handling checklist:
175
176- [ ] Collect minimum PII needed for scheduling and incentives.
177- [ ] Store identity/contact separately from study data.
178- [ ] Redact names/emails from transcripts before broad sharing.
179- [ ] Restrict raw recordings to need-to-know access.
180- [ ] Document consent, purpose, retention, and opt-out path.
181
182### Research Democratization (2026 Trend)
183
184Research democratization is a recurring 2026 trend: non-researchers increasingly conduct research. Enable carefully with guardrails.
185
186| Approach | Guardrails | Risk Level |
187|----------|------------|------------|
188| Templated usability tests | Script + task templates provided | Low |
189| Customer interviews by PMs | Training + review required | Medium |
190| Survey design by anyone | Central review + standard questions | Medium |
191| Unsupervised research | Not recommended | High |
192
193**Guardrails for non-researchers:**
194
195- [ ] Pre-approved research templates only
196- [ ] Central review of findings before action
197- [ ] No direct participant recruitment without ops approval
198- [ ] Mandatory bias awareness training
199- [ ] Clear escalation path for unexpected findings
200
201---
202
203## Measurement & Decision Quality (Core)
204
205### Research ROI Quick Reference
206
207| Research Activity | Proxy Metric | Calculation |
208|-------------------|--------------|-------------|
209| Usability testing finding | Prevented dev rework | Hours saved × $150/hr |
210| Discovery interview | Prevented build-wrong-thing | Sprint cost × risk reduction % |
211| A/B test conclusive result | Improved conversion | (ΔConversion × Traffic × LTV) - Test cost |
212| Heuristic evaluation | Early defect detection | Defects found × Cost-to-fix-later |
213
214**Rules of thumb**:
215- 1 usability finding that prevents 40 hours of rework = **$6,000 value**
216- 1 discovery insight that prevents 1 wasted sprint = **$50,000-100,000 value**
217- Research that improves conversion 0.5% on 100k visitors × $50 LTV = **$25,000/month**
218
219### Triangulation Rubric
220
221| Confidence | Evidence requirement | Use for |
222|------------|----------------------|---------|
223| High | Multiple methods or sources agree | High-impact decisions |
224| Medium | Strong signal from one method + supporting indicators | Prioritization |
225| Low | Single source / small sample | Exploratory hypotheses |
226
227### Adoption vs Value (Avoid Vanity Metrics)
228
229| Metric type | Example | Common pitfall |
230|-------------|---------|----------------|
231| Adoption | Feature usage rate | “Used” ≠ “helpful” |
232| Value/outcome | Task success, goal completion | Harder to instrument |
233
234### When NOT to Run A/B Tests
235
236| Situation | Why it fails | Better method |
237|----------|--------------|---------------|
238| Low power/traffic | Inconclusive results | Usability tests + trends |
239| Many variables change | Attribution impossible | Prototype tests → staged rollout |
240| Need “why” | Experiments don’t explain | Interviews + observation |
241| Ethical constraints | Harmful denial | Phased rollout + holdouts |
242| Long-term effects | Short tests miss delayed impact | Longitudinal + retention analysis |
243
244### Common Confounds (Call Out Early)
245
246- Selection bias (only power users respond).
247- Survivorship bias (you miss churned users).
248- Novelty effect (short-term lift).
249- Instrumentation changes mid-test (metrics drift).
250
251---
252
253## Optional: AI/Automation Research Considerations
254
255> Use only when researching automation/AI-powered features. Skip for traditional software UX.
256>
257> **2026 benchmark**: Trend reports consistently highlight AI-assisted analysis. Use AI for speed while keeping humans responsible for strategy and interpretation. Example reference: https://www.lyssna.com/blog/ux-research-trends/
258
259### Key Questions
260
261| Dimension | Question | Methods |
262|----------|----------|---------|
263| Mental model | What do users think the system can/can’t do? | Interviews, concept tests |
264| Trust calibration | When do users over/under-rely? | Scenario tests, log review |
265| Explanation usefulness | Does “why” help decisions? | A/B explanation variants, interviews |
266| Failure recovery | Do users recover and finish tasks? | Failure-path usability tests |
267
268### Error Taxonomy (User-Visible)
269
270| Failure type | Typical impact | What to measure |
271|-------------|----------------|----------------|
272| Wrong output | Rework, lost trust | Verification + override rate |
273| Missing output | Manual fallback | Fallback completion rate |
274| Unclear output | Confusion | Clarification requests |
275| Non-recoverable failure | Blocked flow | Time-to-recovery, support contact |
276
277### Optional: AI-Assisted Research Ops (Guardrailed)
278
279- Use automation for transcription/tagging only after PII redaction.
280- Maintain an audit trail: every theme links back to raw quotes/clips.
281
282### Synthetic Users: When Appropriate (2026)
283
284Trend reports frequently mention synthetic/AI participants. Use with clear boundaries. Example reference: https://www.lyssna.com/blog/ux-research-trends/
285
286| Use Case | Appropriate? | Why |
287|----------|--------------|-----|
288| Early concept brainstorming | WARNING: Supplement only | Generate edge cases, not validation |
289| Scenario/edge case expansion | PASS Yes | Broaden coverage before real testing |
290| Moderator training/practice | PASS Yes | Practice without participant burden |
291| Hypothesis generation | PASS Yes | Explore directions to test with real users |
292| Validation/go-no-go decisions | FAIL Never | Cannot substitute lived experience |
293| Usability findings as evidence | FAIL Never | Real behavior required |
294| Quotes in reports | FAIL Never | Fabricated quotes damage credibility |
295
296**Critical rule**: Synthetic outputs are **hypotheses**, not evidence. Always validate with real users before shipping.
297
298---
299
300## Navigation
301
302### Resources
303
304**Core Research Methods:**
305
306- [references/research-frameworks.md](references/research-frameworks.md) — JTBD, Kano, Double Diamond, Service Blueprint, opportunity mapping
307- [references/ux-audit-framework.md](references/ux-audit-framework.md) — Heuristic evaluation, cognitive walkthrough, severity rating
308- [references/usability-testing-guide.md](references/usability-testing-guide.md) — Task design, facilitation, analysis
309- [references/ux-metrics-framework.md](references/ux-metrics-framework.md) — Task metrics, SUS/HEART, measurement guidance
310- [references/customer-journey-mapping.md](references/customer-journey-mapping.md) — Journey mapping and service blueprints
311- [references/pain-point-extraction.md](references/pain-point-extraction.md) — Feedback-to-themes method
312- [references/review-mining-playbook.md](references/review-mining-playbook.md) — B2B/B2C review mining
313
314**Demographic & Quantitative Research (NEW):**
315
316- [references/demographic-research-methods.md](references/demographic-research-methods.md) — Inclusive research for seniors, children, cultures, disabilities
317- [references/ab-testing-implementation.md](references/ab-testing-implementation.md) — A/B testing deep-dive (sample size, analysis, pitfalls)
318
319**Competitive UX Analysis & Flow Patterns:**
320
321- [references/competitive-ux-analysis.md](references/competitive-ux-analysis.md) — **Step-by-step flow patterns** from industry leaders (Wise, Revolut, Shopify, Notion, Linear, Stripe) + benchmarking methodology
322
323**Data & Sources:**
324
325- [data/sources.json](data/sources.json) — Curated external references
326
327---
328
329## Domain-Specific UX Benchmarking
330
331**IMPORTANT**: When designing UX flows for a specific domain, you MUST use WebSearch to find and suggest best-practice patterns from industry leaders.
332
333### Trigger Conditions
334
335- "We're designing [flow type] for [domain]"
336- "What's the best UX for [feature] in [industry]?"
337- "How do [Company A, Company B] handle [flow]?"
338- "Benchmark our [feature] against competitors"
339- Any UX design task with identifiable domain context
340
341### Domain → Leader Lookup Table
342
343| Domain | Industry Leaders to Check | Key Flows |
344|--------|---------------------------|-----------|
345| **Fintech/Banking** | Wise, Revolut, Monzo, N26, Chime, Mercury | Onboarding/KYC, money transfer, card management, spend analytics |
346| **E-commerce** | Shopify, Amazon, Stripe Checkout | Checkout, cart, product pages, returns |
347| **SaaS/B2B** | Linear, Notion, Figma, Slack, Airtable | Onboarding, settings, collaboration, permissions |
348| **Developer Tools** | Stripe, Vercel, GitHub, Supabase | Docs, API explorer, dashboard, CLI |
349| **Consumer Apps** | Spotify, Airbnb, Uber, Instagram | Discovery, booking, feed, social |
350| **Healthcare** | Oscar, One Medical, Calm, Headspace | Appointment booking, records, compliance flows |
351| **EdTech** | Duolingo, Coursera, Khan Academy | Onboarding, progress, gamification |
352
353### Required Searches
354
355When user specifies a domain, execute:
356
3571. Search: `"[domain] UX best practices 2026"`
3582. Search: `"[leader company] [flow type] UX"`
3593. Search: `"[leader company] app review UX" site:mobbin.com OR site:pageflows.com`
3604. Search: `"[domain] onboarding flow examples"`
361
362### What to Report
363
364After searching, provide:
365
366- **Pattern examples**: Screenshots/flows from 2-3 industry leaders
367- **Key patterns identified**: What they do well (with specifics)
368- **Applicable to your flow**: How to adapt patterns
369- **Differentiation opportunity**: Where you could improve on leaders
370
371### Example Output Format
372
373```text
374DOMAIN: Fintech (Money Transfer)
375BENCHMARKED: Wise, Revolut
376
377WISE PATTERNS:
378- Upfront fee transparency (shows exact fee before recipient input)
379- Mid-transfer rate lock (shows countdown timer)
380- Delivery time estimate per payment method
381- Recipient validation (bank account check before send)
382
383REVOLUT PATTERNS:
384- Instant send to Revolut users (P2P first)
385- Currency conversion preview with rate comparison
386- Scheduled/recurring transfers prominent
387
388APPLY TO YOUR FLOW:
3891. Add fee transparency at step 1 (not step 3)
3902. Show delivery estimate per payment rail
3913. Consider rate lock feature for FX transfers
392
393DIFFERENTIATION OPPORTUNITY:
394- Neither shows historical rate chart—add "is now a good time?" context
395```
396
397---
398
399## Trend Awareness Protocol
400
401**IMPORTANT**: When users ask recommendation questions about UX research, you MUST use WebSearch to check current trends before answering.
402
403### Tool/Trend Triggers
404
405- "What's the best UX research tool for [use case]?"
406- "What should I use for [usability testing/surveys/analytics]?"
407- "What's the latest in UX research?"
408- "Current best practices for [user interviews/A/B testing/accessibility]?"
409- "Is [research method] still relevant in 2026?"
410- "What research tools should I use?"
411- "Best approach for [remote research/unmoderated testing]?"
412
413### Tool/Trend Searches
414
4151. Search: `"UX research trends 2026"`
4162. Search: `"UX research tools best practices 2026"`
4173. Search: `"[Maze/Hotjar/UserTesting] comparison 2026"`
4184. Search: `"AI in UX research 2026"`
419
420### Tool/Trend Report Format
421
422After searching, provide:
423
424- **Current landscape**: What research methods/tools are popular NOW
425- **Emerging trends**: New techniques or tools gaining traction
426- **Deprecated/declining**: Methods that are losing effectiveness
427- **Recommendation**: Based on fresh data and current practices
428
429### Example Topics (verify with fresh search)
430
431- AI-powered research tools (Maze AI, Looppanel)
432- Unmoderated testing platforms evolution
433- Voice of Customer (VoC) platforms
434- Analytics and behavioral tools (Hotjar, FullStory)
435- Accessibility testing tools and standards
436- Research repository and insight management
437
438---
439
440### Templates
441
442- Shared plan template: [../software-clean-code-standard/assets/checklists/ux-research-plan-template.md](../software-clean-code-standard/assets/checklists/ux-research-plan-template.md) — Product-agnostic research plan template (core + optional AI)
443- [assets/research-plan-template.md](assets/research-plan-template.md) — UX research plan template
444- [assets/testing/usability-test-plan.md](assets/testing/usability-test-plan.md) — Usability test plan
445- [assets/testing/usability-testing-checklist.md](assets/testing/usability-testing-checklist.md) — Usability testing checklist
446- [assets/audits/heuristic-evaluation-template.md](assets/audits/heuristic-evaluation-template.md) — Heuristic evaluation
447- [assets/audits/ux-audit-report-template.md](assets/audits/ux-audit-report-template.md) — Audit report