petrogurcak/ux-optimization
plugins/ux/skills/ux-optimization/SKILL.md
Diagnoses UX issues and provides concrete, code-ready solutions based on 213 real case studies, covering forms, e-commerce, design, mobile, A/B testing, performance, accessibility, admin dashboards, data tables, CRUD operations, navigation, persuasion patterns, and micro-interactions. Use when form conversion is below 50%, cart abandonment exceeds 70%, users miss CTAs, mobile UX is frustrating, or you need to set up A/B tests. Trigger phrases include "improve conversion", "optimize forms", "fix checkout", "A/B test", "UX audit". NOT for value proposition clarity issues (use uvp-optimization), expert design critique sessions (use ux-expert-dialogue), or writing copy (use web-copy).
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SKILL.md
- name:
- ux-optimization
- description:
- Diagnoses UX issues and provides concrete, code-ready solutions based on 213 real case studies, covering forms, e-commerce, design, mobile, A/B testing, performance, accessibility, admin dashboards, data tables, CRUD operations, navigation, persuasion patterns, and micro-interactions. Use when form conversion is below 50%, cart abandonment exceeds 70%, users miss CTAs, mobile UX is frustrating, or you need to set up A/B tests. Trigger phrases include "improve conversion", "optimize forms", "fix checkout", "A/B test", "UX audit". NOT for value proposition clarity issues (use uvp-optimization), expert design critique sessions (use ux-expert-dialogue), or writing copy (use web-copy).
- author:
- Petr
- version:
- 1.0.0
UX Optimization
Overview
Evidence-based UX optimization from 213 real case studies (ILINČEV blog analysis).
Core principle: Data > opinions. Test everything. Implement proven patterns.
Violating data-driven approach is violating the spirit of UX optimization.
Announce at start: "I'm using the UX optimization skill to improve your [forms/e-shop/design/mobile]."
The Iron Law
NO OPTIMIZATION WITHOUT DATA FIRST
NO DEPLOYMENT WITHOUT A/B TEST
If you haven't identified the problem with data, you cannot optimize. If you haven't A/B tested, you cannot deploy to 100%.
When to Use
Use this skill when optimizing:
- Forms - Low conversion (< 50%), high abandonment, validation errors
- E-commerce - Low add-to-cart, cart abandonment (> 70%), low AOV
- Design - Users miss CTAs, page feels cluttered, no visual hierarchy
- Mobile - Touch targets too small, forms frustrating, poor thumb ergonomics
- A/B Testing - Don't know what to test, when to stop test, how to prioritize
- Performance - Slow page load, images too large
- Accessibility - WCAG compliance, keyboard navigation
Use ESPECIALLY when:
- Manager says "just make it better" (vague = need diagnosis)
- Designer disagrees with data (data wins)
- "Our users are different" (cognitive biases are universal)
- Under time pressure (systematic faster than thrashing)
Don't skip when:
- Changes seem obvious (test anyway - 50% fail)
- Small change (small = big impact)
- Already implemented (rollback costs more than testing)
The Four Phases
Copy this checklist to track progress:
UX Optimization Progress:
- [ ] Phase 1: Diagnose Problem (data-driven identification)
- [ ] Phase 2: Load Practice (route to relevant solution)
- [ ] Phase 3: Implement Solution (concrete code application)
- [ ] Phase 4: Measure Impact (A/B test and validate)
You MUST complete each phase before proceeding to the next.
Phase 1: Diagnose Problem
BEFORE proposing ANY solution:
-
Gather Data
- Google Analytics - where do users drop off?
- Heatmaps (Hotjar, Clarity) - where do they click?
- Session recordings - what do they do?
- Form analytics (Zuko) - which fields cause abandonment?
- Gemini Vision Diagnosis: Upload screenshots of heatmaps/recordings.
- MANDATORY: Anonymize screenshots (remove PII) before uploading.
-
Identify Symptoms
Forms: - Conversion < 50% → investigate field count - Drop-off at validation → check error messages - Mobile abandonment → check keyboard types E-commerce: - Add-to-cart < 3% → check product photos - Cart abandonment > 70% → check checkout flow - AOV declining → investigate cross-sell Design: - Low CTA clicks → check contrast, size, position - High bounce → check visual hierarchy - Long time-on-page but no action → check whitespace Mobile: - Mis-taps → check touch target sizes - Form abandonment → check keyboard types -
Ask Diagnostic Questions
- What metric is underperforming?
- Where exactly do users drop off?
- What are common user complaints?
- When did this start? (recent deploy?)
- Is it device-specific? (mobile vs desktop)
-
Route to Category
Based on symptoms, route to:
Forms issues → practices/forms.md E-commerce issues → practices/ecommerce.md Design issues → practices/design.md Mobile issues → practices/mobile.md Testing questions → practices/ab-testing.md Performance → practices/performance.md Accessibility → practices/accessibility.md Admin dashboards → practices/admin-dashboard.md Data tables → practices/data-tables.md CRUD operations → practices/crud-operations.md Navigation → practices/sidebar-navigation.md Enterprise forms → practices/enterprise-forms.md Persuasion/behavioral → practices/persuasion-patterns.md Copy-UX issues → practices/copy-ux-patterns.md Empty states/onboarding → practices/empty-and-first-use.md Micro-interactions → practices/micro-interactions.md
Phase 2: Load Practice
REQUIRED SUB-SKILL: Load relevant practice from practices/
Announce: "Loading practices/[category].md for specific solutions."
For each practice, you get:
- Problem description - What's broken
- Solution - How to fix it
- Implementation - Concrete code
- Examples - GOOD vs BAD
- Expected impact - % improvement from case studies
- Checklist - Verification steps
Phase 3: Implement Solution
From loaded practice file:
-
Get Concrete Code
- Copy-paste ready HTML/CSS/JS
- Mobile-ready by default
- Accessibility included (WCAG AA)
-
See Working Examples
- RECOMMENDED SUB-SKILL: Use examples/ folder for complete code
-
Use Checklist
- Verify each requirement
- Test on real devices
- Check edge cases
-
Apply Pattern
- Don't just copy - understand WHY
- Adapt to your context
- Maintain consistency
Phase 4: Measure Impact
REQUIRED SUB-SKILL: Use practices/ab-testing.md for test setup
Setup A/B test:
-
Baseline Metric
- Current conversion rate
- Current AOV
- Current time-on-task
-
ICE Prioritization
- Impact (1-10): How much will it improve?
- Confidence (1-10): How sure are you?
- Ease (1-10): How easy to implement?
- Score = (I × C × E) / 1000
- Test highest score first
-
Sample Size
- Minimum: 100 conversions per variant
- Statistical significance: 95%+
- P-value: < 0.05
- Duration: 1-2 full business cycles
-
Deploy
- 50/50 traffic split
- Run until significance
- Winner → new baseline
- Iterate
NO full deploy without A/B test validation.
Quick Router
Forms Problems
| Symptom | Practice | Expected Impact | | ---------------------- | ------------------------- | ------------------- | | Low conversion (< 50%) | practices/forms.md #1 | +10-30% | | Validation errors | practices/forms.md #2 | +15-25% | | Password issues | practices/forms.md #3, #4 | +10-20% | | Social login missing | practices/forms.md #5 | +20-40% (18-25 age) | | Mobile frustration | practices/forms.md #6, #7 | +15-30% | | Generic errors | practices/forms.md #8 | +10-15% |
E-commerce Problems
| Symptom | Practice | Expected Impact | | ------------------------- | -------------------------- | --------------- | | Low add-to-cart | practices/ecommerce.md #9 | +20-40% | | "Is this the right size?" | practices/ecommerce.md #10 | +15-25% | | Cart uncertainty | practices/ecommerce.md #11 | +10-20% | | Low AOV | practices/ecommerce.md #12 | +15-35% |
Design Problems
| Symptom | Practice | Expected Impact | | -------------- | ----------------------- | --------------- | | Missed CTAs | practices/design.md #13 | +25-50% | | No focus | practices/design.md #14 | +15-30% | | Cluttered feel | practices/design.md #15 | +10-20% |
Value Proposition / Messaging Problems
| Symptom | Solution | Expected Impact |
| ---------------------------- | ------------------------------------------- | --------------------------- |
| Users don't understand offer | → Use uvp-optimization skill | +40-240% (see case studies) |
| Low homepage conversion | → Define/test UVP with uvp-optimization | +100%+ possible |
| "What do you do?" confusion | → Five-second test (see uvp-optimization) | Clarity baseline |
| Generic messaging | → Choose positioning framework | Differentiation |
Note: UVP clarity is FOUNDATIONAL. If users don't understand your offer in 5 seconds, design optimization won't fix it. Define UVP first, then optimize presentation.
A/B Testing Questions
| Question | Practice | | ------------------- | --------------------------- | | What to test first? | practices/ab-testing.md #16 | | When to stop test? | practices/ab-testing.md #17 |
Mobile Problems
| Symptom | Practice | Expected Impact | | ---------------- | ----------------------- | --------------- | | Mis-taps | practices/mobile.md #18 | +20-35% | | Form abandonment | practices/mobile.md #19 | +25-40% |
Performance Issues
| Symptom | Practice | Expected Impact | | --------- | --------------------------------- | ----------------- | | Slow load | practices/performance.md #20, #21 | -30-50% load time |
Accessibility Issues
| Issue | Practice | | --------------- | ----------------------------------- | | WCAG compliance | practices/accessibility.md #22, #23 |
Admin Dashboard Problems
| Symptom | Practice | Expected Impact | | ------------------- | -------------------------------- | --------------------- | | Cluttered dashboard | practices/admin-dashboard.md #30 | +20-40% clarity | | Wrong chart types | practices/admin-dashboard.md #31 | +30-55% understanding | | Generic widgets | practices/admin-dashboard.md #32 | +25% usability | | No personalization | practices/admin-dashboard.md #33 | +15-25% satisfaction |
Data Table Problems
| Symptom | Practice | Expected Impact | | ------------------- | ---------------------------- | ------------------- | | Hard to scan tables | practices/data-tables.md #34 | +15-25% scan speed | | Can't find data | practices/data-tables.md #35 | +20-35% findability | | Pagination issues | practices/data-tables.md #36 | +15-30% navigation | | Slow loading | practices/data-tables.md #37 | -30-50% load time | | Poor bulk actions | practices/data-tables.md #38 | +60-80% efficiency |
CRUD Problems
| Symptom | Practice | Expected Impact | | -------------------- | -------------------------------- | ------------------------- | | Low create rate | practices/crud-operations.md #39 | +10-25% completion | | Data loss on edit | practices/crud-operations.md #40 | -30-50% incidents | | Accidental deletes | practices/crud-operations.md #41 | -50-80% errors | | Slow bulk operations | practices/crud-operations.md #42 | +60-80% efficiency | | Perceived slowness | practices/crud-operations.md #43 | +200-500% perceived speed |
Navigation Problems
| Symptom | Practice | Expected Impact | | ------------------- | ----------------------------------- | ------------------------- | | Users get lost | practices/sidebar-navigation.md #44 | +20-35% orientation | | Deep nesting issues | practices/sidebar-navigation.md #45 | +15-30% findability | | Icons unclear | practices/sidebar-navigation.md #46 | +25% recognition | | Poor mobile nav | practices/sidebar-navigation.md #47 | +30-50% mobile efficiency |
Enterprise Form Problems
| Symptom | Practice | Expected Impact | | --------------------- | --------------------------------- | ------------------ | | Long form abandonment | practices/enterprise-forms.md #48 | +25-40% completion | | Validation confusion | practices/enterprise-forms.md #49 | +15-25% completion | | Slow data entry | practices/enterprise-forms.md #50 | +40-60% speed | | Unclear form status | practices/enterprise-forms.md #51 | +20% confidence |
Persuasion & Behavioral Patterns
| Symptom | Practice | Expected Impact | | ------------------------------- | ------------------------------------ | --------------- | | Low trust, no reciprocity | practices/persuasion-patterns.md #52 | +20-30% | | Positive framing not converting | practices/persuasion-patterns.md #53 | +30% CTR | | No urgency/scarcity | practices/persuasion-patterns.md #54 | +10-25% | | Users hesitant to commit | practices/persuasion-patterns.md #55 | +17% | | Low opt-in rates | practices/persuasion-patterns.md #56 | 2-3x | | Low retention/engagement | practices/persuasion-patterns.md #57 | +40-60% | | Weak social proof | practices/persuasion-patterns.md #58 | +15-25% |
Copy-UX Patterns
| Symptom | Practice | Expected Impact | | ------------------------- | --------------------------------- | --------------- | | Generic button text | practices/copy-ux-patterns.md #59 | +25-40% | | Weak/uncertain language | practices/copy-ux-patterns.md #60 | +15-20% | | Formal form labels | practices/copy-ux-patterns.md #61 | +5-15% | | Unclear target audience | practices/copy-ux-patterns.md #62 | +20-35% | | Impersonal/corporate feel | practices/copy-ux-patterns.md #63 | +15-25% | | Company-centric messaging | practices/copy-ux-patterns.md #64 | +10-15% | | Dry product descriptions | practices/copy-ux-patterns.md #65 | +15-20% |
Empty States & First Use
| Symptom | Practice | Expected Impact | | ----------------------------- | ------------------------------------ | --------------- | | Users confused on first visit | practices/empty-and-first-use.md #66 | +30-50% | | Signup wall kills activation | practices/empty-and-first-use.md #67 | +25-40% | | Low completion of multi-step | practices/empty-and-first-use.md #68 | +15-25% | | Power users feel limited | practices/empty-and-first-use.md #69 | +20-30% | | Users abandon complex flows | practices/empty-and-first-use.md #70 | +15-20% |
Micro-Interactions
| Symptom | Practice | Expected Impact | | ----------------------------- | ----------------------------------- | --------------- | | Jarring UI changes | practices/micro-interactions.md #71 | +10-15% | | Users unsure if action worked | practices/micro-interactions.md #72 | +15-25% | | Too many confirmation dialogs | practices/micro-interactions.md #73 | +20-30% | | Hard to scan item status | practices/micro-interactions.md #74 | +25-35% | | Users miss content below fold | practices/micro-interactions.md #75 | +15-20% |
Key Principles
| Principle | Application | Evidence | | --------------------- | ----------------------------------- | --------------------------------- | | Data > opinions | Always A/B test before 100% deploy | 50% of changes hurt metrics | | Psychology first | Use Cialdini 6 principles | +15-40% avg improvement | | Minimize friction | Each form field = -5-10% conversion | Baymard Institute research | | Mobile-first | 60%+ traffic is mobile | Design for thumb zone | | Test everything | "Best practices" context-dependent | Test in YOUR context | | Small changes | Big impact from tiny tweaks | Case study: one page = 8× revenue | | Continuous | Never done, always iterating | Compound improvements |
Practice Files Pattern
Each practices/*.md follows this structure:
# [Category] Optimization Practices
Based on 213 case studies from ILINČEV blog.
## Practice #X: [Name]
**PROBLÉM:** [Specific issue]
**ŘEŠENÍ:** [Concrete fix]
**IMPLEMENTACE:**
1. [Step-by-step]
2. [With checklists]
**KÓD:**
[Copy-paste ready code with comments]
**PŘÍKLADY:**
❌ ŠPATNĚ: [What not to do]
✅ SPRÁVNĚ: [What to do]
**OČEKÁVANÝ DOPAD:** +X-Y% [metric] (based on case study Z)
**A/B TEST SETUP:**
- Baseline: [current metric]
- Variant: [proposed change]
- Sample: [min 100 conversions]
- Duration: [1-2 weeks]
**CHECKLIST:**
- [ ] [Verification step]
- [ ] [Verification step]
Case Studies (Real Results)
From 20+ documented case studies (ILINČEV, Czech, World-class):
| Client | Change | Result | Source | | ----------------- | ---------------------------------- | ----------------------------------- | -------- | | Spa.cz | Complete redesign + AB tests | +21.5% orders | ILINČEV | | Trenýrkarna.cz | 6-year optimization | 400% revenue growth | ILINČEV | | Anonymous | Single page optimization | 680% revenue increase | ILINČEV | | eBay | Enterprise conversion optimization | +18% uplift | Invesp | | 3M | B2B e-commerce transformation | +50% conversion | Invesp | | Soft Surroundings | Multi-device optimization | +42% desktop, +35% mobile | Invesp | | Z Gallerie | Rapid ROI achievement | 4× ROI in week 1 | Invesp | | GoodUI Modal | Signup optimization | +191% signups | GoodUI | | GoodUI Homepage | Simplification | +232% signups | GoodUI | | GoodUI Pricing | Page optimization | +48% purchases | GoodUI | | Baymard | Checkout field reduction | 22% abandon from complexity | Research | | Baymard | Phone field explanation | 14% abandon without explanation | Research | | Čeština 2.0 | Navigation naming | +40% page views | Czech | | Key4You.cz | Cart cross-sell | +5% AOV | Czech | | ČT edu | Carousel elimination | 3× CTR increase | Czech | | Dima Melnik | Pricing psychology (18 tips) | 11% → 52% premium acceptance | Expert |
See CASE-STUDIES.md for 21 detailed breakdowns
Common Rationalizations
| Excuse | Reality | Evidence | | --------------------------- | ---------------------------- | ----------------------------- | | "Too simple to optimize" | Small changes = big ROI | +10-30% avg | | "Our users are different" | Cognitive biases universal | Cialdini research | | "No time for A/B tests" | One bad deploy costs more | 50% changes hurt | | "We need more features" | Fewer fields > more features | Each field -5-10% | | "Designer knows best" | Data knows best | Design without data = opinion | | "I already tested it" | Manual ≠ systematic | A/B = proof | | "That can't matter" | Everything matters | Micro-optimizations compound | | "Just this once, skip test" | One shortcut = many bugs | Systematic = faster |
All of these mean: Go back to Phase 1. Gather data.
Red Flags - STOP and Diagnose First
- Proposing solution before seeing data
- "I think users want..." without evidence
- Skipping A/B test "this time"
- "It's obvious" (nothing is obvious)
- "Our case is special" (it isn't)
- Deploying 100% immediately
- Not tracking metrics
- Can't articulate expected impact
- "We'll measure later" (you won't)
All of these = violation of Iron Law. Return to Phase 1.
Verification Checklist
Before marking optimization complete:
Phase 1 - Diagnosis:
- [ ] Data gathered (Analytics, heatmaps, recordings)
- [ ] Problem identified with specific metric
- [ ] Symptom matched to category
- [ ] Relevant practice file identified
Phase 2 - Practice Loading:
- [ ] Correct practice file loaded
- [ ] Problem description matches
- [ ] Expected impact noted
Phase 3 - Implementation:
- [ ] Code implemented from examples
- [ ] Mobile-tested (real device, not just Chrome DevTools)
- [ ] Accessibility checked (keyboard nav, screen reader, contrast)
- [ ] Edge cases handled
- [ ] All checklist items verified
Phase 4 - Measurement:
- [ ] Baseline metric captured
- [ ] A/B test setup (50/50 split)
- [ ] Sample size calculated
- [ ] Monitoring dashboard created
- [ ] Success criteria defined
Post-Deploy:
- [ ] Test reached significance (95%+, p < 0.05)
- [ ] Minimum 100 conversions per variant
- [ ] Winner documented
- [ ] Learnings shared with team
- [ ] Next optimization identified
Can't check all boxes? Return to appropriate phase.
When Stuck
| Problem | Solution | | ------------------------ | --------------------------------- | | Don't know what's broken | Use Analytics + heatmaps first | | Multiple issues | Prioritize with ICE framework | | Test inconclusive | Run longer (min 100 conversions) | | Change hurt metrics | Rollback, analyze why, iterate | | Team disagrees | Let data decide (A/B test both) | | No traffic for A/B | Optimize high-traffic pages first |
Integration with Other Skills
This skill works with:
- superpowers:test-driven-development - Write tests for form validation
- superpowers:verification-before-completion - Verify all metrics before claiming done
- superpowers:systematic-debugging - Debug failed A/B tests
- superpowers:brainstorming - Brainstorm alternative approaches before implementing
Example Workflow
User: "Our registration has 12% completion rate"
Assistant: "I'm using the UX optimization skill to improve your registration.
Phase 1: Diagnose Looking at symptoms: 12% completion (< 50% baseline) → Routing to practices/forms.md
Phase 2: Load Practice Loading forms.md #1 (Minimize fields)
Analysis:
- Current: Probably 8-12 fields
- Problem: Each field -5-10% conversion
- Solution: Reduce to 2 fields (email + password)
Phase 3: Implement [Provides concrete code from examples/]
Phase 4: Measure Setting up A/B test:
- Baseline: 12% conversion
- Expected: 18-36% (+50-200% relative)
- Sample: Run until 100 registrations per variant
- Duration: 1-2 weeks
Deploy 50/50 split, monitor, report results."
Final Rule
Optimization → data exists and test completed
Otherwise → not UX optimization, just changes
No exceptions without your human partner's permission.
Remember: "I think" < "I tested" < "I proved with data"
Based on 213 case studies from ILINČEV.com blog All practices backed by real results Use with confidence
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