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Automatic Matching

Figr’s pattern recognition ensures design consistency without manual effort. Learn how automatic matching works and how to leverage it for better design systems.

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How Automatic Matching Works

1

Pattern Recognition

Figr analyzes your existing designs:
Interface showing Figr analyzing existing designs and identifying common patterns
Analysis capabilities:
Visual pattern detection:
- Color usage frequency and combinations
- Typography hierarchies and relationships
- Spacing patterns and rhythms
- Component shapes and styling
- Layout structures and grids

Interaction pattern recognition:
- Button behaviors and states
- Form validation approaches
- Navigation interaction models
- Hover and focus effects
- Animation and transition styles
2

Pattern Classification

Organizing discovered patterns:
  • Component Patterns
  • Layout Patterns
  • Content Patterns
Identified components:

Button variations:
- Primary: Blue background, white text
- Secondary: White background, blue border
- Danger: Red background, white text
- Ghost: Transparent background, blue text

Card patterns:
- Standard: White background, subtle shadow
- Elevated: Higher shadow, slight border
- Flat: No shadow, border only
- Highlighted: Colored left border accent
3

Pattern Application

Automatic pattern matching in new designs:
Smart pattern selection:

Button context matching:
Form submission → Primary button pattern
Destructive action → Danger button pattern
Secondary action → Secondary button pattern
Navigation link → Ghost button pattern

Layout context matching:
User management → Settings layout pattern
Data visualization → Dashboard layout pattern
Content browsing → List view pattern

Pattern match confidence:

High confidence (90%+):
- Exact color and typography matches
- Identical component structures
- Perfect spacing alignments

Medium confidence (70-89%):
- Similar but not identical patterns
- Minor variations in implementation
- Close but not exact measurements

Low confidence (50-69%):
- Conceptually similar patterns
- Different implementation approaches
- Potential pattern variations

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Pattern Enhancement Suggestions

  • Consistency Improvements
  • Pattern Evolution
  • Missing Pattern Detection
Identifying and fixing inconsistencies:
Interface showing suggestions for improving design consistency across components
Common improvement areas:
Color consistency:
Issue: "Using #1a73e8 and #1976d2 for primary actions"
Suggestion: "Standardize on single primary blue: #1a73e8"
Impact: "Affects 23 components across 8 pages"

Spacing inconsistency:
Issue: "Card padding varies between 16px, 20px, and 24px"
Suggestion: "Standardize card padding to 20px"
Impact: "Creates uniform visual rhythm"

Typography hierarchy:
Issue: "Section headers use 22px, 24px, and 26px"
Suggestion: "Use consistent 24px for all section headers"
Impact: "Improves content hierarchy clarity"

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Advanced Matching Features

1

Semantic Pattern Understanding

Beyond visual matching to purpose recognition:
Purpose-based pattern recognition:

Primary actions: "Get Started", "Save Changes", "Submit"
Secondary actions: "Cancel", "Back", "Edit"
Destructive actions: "Delete", "Remove", "Clear"
Informational actions: "Learn More", "View Details", "Help"

Context understanding:
- Form submission buttons (primary style)
- Navigation buttons (ghost style)
- Confirmation dialogs (secondary + primary)
- Error states (danger styling)

Content context recognition:

User-generated content: Flexible containers, overflow handling
System messages: Consistent alert styling, icon usage
Marketing content: Brand-forward styling, engaging visuals
Data displays: Information density, scanning optimization
2

Cross-Platform Pattern Adaptation

Intelligent pattern translation across platforms:
  • Web to Mobile
  • Platform-Specific Patterns
Adaptive pattern translation:

Desktop hover states → Mobile press states
Click interactions → Touch gestures
Tooltips → Contextual panels
Dropdown menus → Bottom sheets
Multi-column layouts → Stacked layouts
3

Pattern Performance Optimization

Suggest performance-optimized pattern implementations:
Performance improvements:

Image optimization:
Pattern: Hero image backgrounds
Suggestion: WebP format with fallbacks
Impact: 40% faster page loads

Animation efficiency:
Pattern: Button hover effects
Suggestion: Transform-based animations
Impact: Smoother 60fps animations

Layout optimization:
Pattern: Grid-based layouts
Suggestion: CSS Grid over flexbox for complex layouts
Impact: Better rendering performance

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Customizing Automatic Matching

  • Pattern Priorities
  • Pattern Exceptions
  • Learning Controls
Control which patterns take precedence:
Interface for setting pattern matching priorities and preferences
Priority configuration:
Matching preferences:

Brand consistency: High priority
- Always use brand colors over generic
- Maintain brand typography hierarchy
- Apply brand-specific spacing

Accessibility: Critical priority
- Override patterns that fail accessibility
- Prioritize WCAG-compliant variations
- Suggest accessibility improvements

Platform conventions: Medium priority
- Follow iOS/Android design guidelines
- Respect web usability conventions
- Consider cross-platform consistency

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Pattern Quality Assurance

1

Automated Pattern Validation

Quality checks for pattern consistency:
Validation checks:

Accessibility compliance:
- Color contrast ratio verification
- Touch target size validation
- Keyboard navigation support
- Screen reader compatibility

Visual consistency:
- Typography scale adherence
- Color palette compliance
- Spacing system alignment
- Component proportion harmony

Technical feasibility:
- Implementation complexity assessment
- Performance impact evaluation
- Cross-browser compatibility
- Responsive behavior validation
2

Pattern Usage Analytics

Track pattern effectiveness:

Usage Metrics

Pattern adoption tracking:
  • Frequency of pattern application
  • Success rate of automatic matching
  • User satisfaction with suggestions
  • Time saved through automation

Performance Impact

Pattern performance analysis:
  • Loading time impact
  • User interaction success rates
  • Conversion rate improvements
  • Accessibility score improvements
3

Continuous Improvement

Evolve patterns based on data:
Improvement cycle:

Data collection:
- User behavior analytics
- Design system usage patterns
- Performance monitoring
- Accessibility audits

Pattern refinement:
- Identify underperforming patterns
- Test pattern variations
- Update pattern definitions
- Document improvement rationale

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Best Practices

Pattern Definition

Create clear, reusable patterns:✅ Define patterns with specific contexts ✅ Document pattern usage guidelines ✅ Include accessibility requirements ✅ Plan for responsive variations ✅ Consider cross-platform adaptations

System Evolution

Grow your pattern library strategically:✅ Regular pattern audits and cleanup ✅ Gradual pattern evolution over revolution ✅ Team consensus on pattern changes ✅ Clear deprecation and migration paths ✅ Documentation of pattern decisions

Phase 3 Complete!

Congratulations! You’ve completed the advanced designing features. Ready to move to precise editing and export capabilities.Precise Edits →
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