journeys-scoring

SKILL.md

Lead Scoring & Customer Journeys

Design intelligent lead scoring systems and automated customer journeys that identify sales-ready prospects, nurture leads through the funnel, and maximize conversion rates through behavioral triggers and personalized automation.

Core Objectives

  • Identify sales-ready leads through behavioral and demographic scoring
  • Automate nurturing journeys based on lead behavior and interests
  • Segment audiences for personalized messaging and offers
  • Reduce manual work through intelligent automation
  • Maximize conversion rates through timely, relevant touchpoints

Mandatory Elements

1. Lead Scoring Model

  • Demographic Score: Firmographics (company size, industry, title)
  • Behavioral Score: Engagement actions (email opens, page views, downloads)
  • Scoring Thresholds: Minimum scores for "Marketing Qualified Lead" (MQL) and "Sales Qualified Lead" (SQL)
  • Negative Scoring: Deduct points for unengaged behavior (unsubscribes, inactivity)

2. Journey Mapping

  • Entry Points: Where leads enter the journey (form submission, webinar, etc.)
  • Stages: Awareness → Consideration → Decision → Retention
  • Triggers: Behavioral events that advance leads through stages
  • Content: Stage-appropriate content and offers

3. Automation Rules

  • If/Then Logic: Conditional automation based on score or behavior
  • Timing: Appropriate delays between touchpoints
  • Personalization: Dynamic content based on lead attributes
  • Suppression: Rules to prevent over-communication

Structure & Frameworks

The "Score & Nurture" Framework

  1. Score Leads: Quantify lead quality and readiness
  2. Segment: Group leads by score, behavior, or attributes
  3. Automate: Trigger journeys based on segments and triggers
  4. Optimize: Test and refine scoring and journey performance

Lead Scoring Example

"Scoring Model (Total: 100 points):

Demographic (40 points max):
• Company size: 10-50 employees (+10), 50-200 (+15), 200+ (+20)
• Job title: Manager (+5), Director (+10), VP/C-Level (+15)
• Industry match: Target industry (+10)

Behavioral (60 points max):
• Email open: +2 per open (max +10)
• Email click: +5 per click (max +15)
• Page view: +3 per view (max +12)
• Content download: +8 per download (max +16)
• Demo request: +20 (one-time)
• Pricing page visit: +15 (one-time)

Thresholds:
• MQL: 40+ points (send to marketing nurture)
• SQL: 70+ points (notify sales team)"

Voice & Tone Guidelines

  • Strategic & Data-Driven: Focus on metrics and optimization
  • Process-Oriented: Clear workflows and decision trees
  • Automation-Focused: Emphasize efficiency and scale
  • Formatting: Use flowcharts for journeys, tables for scoring models

Concrete Examples

Customer Journey Example

"Welcome Journey (New Subscriber):

Day 0: Welcome email + lead magnet delivery
Day 2: Educational email (if opened Day 0)
Day 5: Case study email (if clicked Day 2)
Day 10: Product demo offer (if scored 40+)
Day 14: Sales outreach (if scored 70+)

Exit Conditions:
• Unsubscribe → Remove from all journeys
• Purchase → Move to customer onboarding journey
• Inactive 30 days → Re-engagement journey"

Quality Checklist

For every scoring/journey plan, ask:

  • Are scoring criteria aligned with ideal customer profile?
  • Do journey stages match the buyer's decision process?
  • Are automation triggers specific and measurable?
  • Is there suppression logic to prevent over-communication?
  • Will this system identify and nurture leads effectively?
Weekly Installs
5
GitHub Stars
3
First Seen
Feb 7, 2026
Installed on
opencode5
claude-code5
codex5
gemini-cli4
github-copilot4
kimi-cli4