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customer-segmentation
Customer micro-segment identification and propensity scoring for targeted marketing
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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Customer micro-segment identification and propensity scoring for targeted marketing
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
UI/UX design intelligence. 67 styles, 96 palettes, 57 font pairings, 25 charts, 13 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app, .html, .tsx, .vue, .svelte. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient. Integrations: shadcn/ui MCP for component search and examples.
Advanced product comparison skill with spec fetching, unit normalization, and comparison matrix generation
Framework for comparing products to help customers decide
Personalized product recommendation strategies based on customer data
Strategies for effective product catalog search and discovery
Advanced intelligent product search with query deconstruction, constraint extraction, and relevance ranking
| name | customer-segmentation |
| description | Customer micro-segment identification and propensity scoring for targeted marketing |
| Attribute | Value |
|---|---|
| Size | 240,000 customers |
| Time Window | 6:00 AM - 9:00 AM |
| Behavior | Fuel + Food purchase |
| Gap | No drink purchase in last 2 weeks |
| Propensity | HIGH for add-on beverages |
| Best Products | Iced Coffee, Electrolyte Water |
| Best Channels | Pump Screen (at fuel start), App Push (7 AM) |
| Attribute | Value |
|---|---|
| Size | 180,000 customers |
| Time Window | 2:00 PM - 5:00 PM |
| Behavior | Snack purchases |
| Gap | Low beverage attachment rate |
| Propensity | MEDIUM (price-sensitive) |
| Best Products | Fountain Soda, Energy Drinks |
| Best Channels | SMS (1 PM pre-snack), POS Screen |
Score = Base + Weather_Factor + Recency_Factor + Frequency_Factor
WHERE:
Base = Segment baseline (High=0.7, Medium=0.5, Low=0.3)
Weather_Factor = +0.2 if temp > 90°F
Recency_Factor = +0.1 if last visit < 7 days
Frequency_Factor = +0.1 if visits > 4/month
For Heat Wave Campaigns:
For Value Promotions:
For Premium Products:
| Segment | Primary Channel | Secondary | Avoid |
|---|---|---|---|
| Morning Fuelers | Pump Screen | App Push | SMS (too early) |
| Afternoon Snackers | SMS | POS Screen | Pump Screen (not fueling) |
When running multi-segment campaigns: