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Design Trend Mapping Reference

Problem

When a user says "I want a modern tech startup look" or "something bold for an indie game studio", how do we translate this to a specific design system?

Solution: Keyword-Based Trend Matching

The match-trend.ts script uses a keyword dictionary to map natural language to our catalog of 24 design trends.

Trend-to-Keyword Mappings

Swiss Modern (Tech, SaaS, Developer Tools)

Triggers: clean, minimal, grid, professional, tech, saas, dashboard, developer, linear, figma, stripe Anti-patterns: decorative, maximalist, experimental Best for: B2B software, developer tools, enterprise dashboards

Neobrutalism (Indie, Creative, Memorable)

Triggers: bold, stark, dramatic, raw, contrasting, indie, gumroad, creative, memorable, anti-design Anti-patterns: soft, blur, gradient, subtle, elegant Best for: Indie products, creative agencies, portfolios

Glassmorphism (Modern, Apple-style, Premium)

Triggers: modern, transparent, blur, frosted, glass, elegant, ios, macos Anti-patterns: bold, stark, raw, hard Best for: iOS apps, premium products, modern dashboards

Terminal Aesthetic (Developer, Hacker, Code)

Triggers: monospace, cli, hacker, green, developer, code, terminal Best for: Developer tools, CLI products, code editors

Web3/Crypto (Fintech, Blockchain, Futuristic)

Triggers: gradient, blockchain, crypto, fintech, futuristic, glow, nft Best for: Crypto platforms, fintech, NFT marketplaces

Claymorphism (Friendly, Playful, 3D)

Triggers: clay, soft, rounded, playful, friendly, approachable, 3d Best for: Consumer apps, family products, educational platforms

Dark Mode (Developer, Media, Modern)

Triggers: dark, night, oled, eye strain, developer, coding Best for: Media apps, developer tools, night-focused products

Maximalism (Entertainment, Creative, Energy)

Triggers: vibrant, colorful, rich, busy, entertainment, creative, expressive Best for: Entertainment, events, creative portfolios

Algorithm Behavior

  1. Positive Match (1.0 points): Full keyword in description
  2. Partial Match (0.5 points): Word contains keyword (min 4 chars)
  3. Negative Match (-0.5 points): Incompatible keyword present
  4. Description Match (0.3 points): Word appears in trend's description

Confidence Scoring

confidence = min(0.95, 0.5 + (gap / topScore) * 0.5)
  • If only one trend matches: 95% confidence
  • If two trends are close: Lower confidence suggests blend
  • If many trends match equally: Consider asking user to clarify

Example Queries → Results

QueryPrimary MatchConfidence
"clean dashboard for developers"swiss-modern85%
"bold indie game landing page"neobrutalism90%
"modern iOS app design"glassmorphism80%
"crypto trading platform"web3-crypto88%
"friendly kids education app"claymorphism82%

Handling Ambiguity

When confidence < 60%, consider:

  1. Presenting top 2-3 options to user
  2. Blending elements from related trends
  3. Asking clarifying questions about brand values