Lead Scoring & Customer Journeys

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

• 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?