Demand Generation Manager

Expert-level demand generation for pipeline growth.

Core Competencies

• Lead generation

• Campaign management

• Marketing automation

• Funnel optimization

• Account-based marketing

• Channel management

• Attribution modeling

• Revenue marketing

Demand Generation Framework

Demand Funnel

AWARENESS ├── Website visitors ├── Social reach └── Ad impressions │ ▼ INTEREST ├── Content engagement ├── Email subscribers └── Event registrants │ ▼ CONSIDERATION ├── MQLs (Marketing Qualified Leads) ├── Content downloads └── Demo requests │ ▼ INTENT ├── SALs (Sales Accepted Leads) ├── Pricing page visits └── Free trial starts │ ▼ PURCHASE ├── SQLs (Sales Qualified Leads) ├── Opportunities └── Closed Won

Funnel Metrics

Stage Metric Benchmark Target

Awareness Visitors

100K/mo

Interest Engaged 10% 15%

MQL Conversion 5% 8%

SAL Acceptance 60% 75%

SQL Conversion 40% 50%

Won Win Rate 25% 30%

Campaign Management

Campaign Planning Template

Campaign Plan: [Campaign Name]

Overview

• Campaign Type: [Webinar/Content/Event/ABM]
• Launch Date: [Date]
• Duration: [Weeks]
• Budget: $[Amount]

Objectives

• Primary: [Metric] - [Target]
• Secondary: [Metric] - [Target]

Target Audience

• Segment: [Description]
• ICP fit: [Criteria]
• List size: [Number]

Offer

• Value proposition: [What they get]
• CTA: [Action to take]
• Landing page: [URL]

Channels

Timeline

Assets Required

• Landing page
• Email sequence (X emails)
• Ad creative (X variants)
• Content piece
• Follow-up sequence

Success Metrics

• Leads: [Target]
• MQLs: [Target]
• Pipeline: $[Target]
• Cost per lead: $[Target]

Campaign Types

Content Campaigns:

• Ebooks/Whitepapers

• Research reports

• Webinars

• Video series

Event Campaigns:

• Hosted events

• Conferences

• Roadshows

• Virtual events

ABM Campaigns:

• Account-specific content

• Executive outreach

• Custom experiences

• Multi-touch sequences

Nurture Campaigns:

• Onboarding sequences

• Re-engagement

• Cross-sell/upsell

• Lifecycle marketing

Lead Scoring

Scoring Model

LEAD SCORE = Demographic Score + Behavioral Score

DEMOGRAPHIC (Fit) - Max 50 points ├── Company size │ ├── Enterprise (1000+): 15 │ ├── Mid-market (100-999): 10 │ └── SMB (<100): 5 ├── Industry │ ├── Target industry: 10 │ ├── Adjacent industry: 5 │ └── Other: 0 ├── Title/Role │ ├── Decision maker: 15 │ ├── Influencer: 10 │ └── User: 5 └── Geography ├── Primary market: 10 └── Secondary market: 5

BEHAVIORAL (Interest) - Max 50 points ├── Website activity │ ├── Pricing page: 15 │ ├── Product pages: 5 each (max 15) │ └── Blog: 2 each (max 10) ├── Content engagement │ ├── Gated download: 10 │ ├── Webinar attend: 10 │ └── Video view: 5 ├── Email engagement │ ├── Open: 1 │ └── Click: 3 └── Direct request └── Demo/Contact: 25

MQL THRESHOLD: 60 points

Lead Lifecycle

NEW → ENGAGED → MQL → SAL → SQL → OPPORTUNITY → CUSTOMER

Definitions:

• NEW: Known contact, no engagement
• ENGAGED: Has taken meaningful action
• MQL: Meets score threshold
• SAL: Sales accepted, working
• SQL: Sales qualified, opportunity
• OPPORTUNITY: Active deal
• CUSTOMER: Closed won

Marketing Automation

Automation Workflows

Lead Nurture:

Trigger: Downloads ebook ├── Day 0: Thank you email + resource ├── Day 3: Related content ├── Day 7: Case study ├── Day 14: Webinar invite └── Day 21: Demo offer

Exit conditions:

• Requests demo
• Unsubscribes
• Becomes MQL

Re-engagement:

Trigger: No activity 60 days ├── Day 0: "We miss you" + new content ├── Day 7: Product update ├── Day 14: Special offer └── Day 21: Final attempt

Exit conditions:

• Engages with any content
• Unsubscribes

Email Performance Benchmarks

Metric Poor Average Good Excellent

Open Rate <15% 15-20% 20-25%

25%

Click Rate <1% 1-2% 2-4%

4%

CTR <5% 5-10% 10-15%

15%

Unsubscribe

1% 0.5-1% 0.2-0.5% <0.2%

Account-Based Marketing

ABM Program Structure

TIER 1: Strategic (1:1) ├── Account count: 10-25 ├── Investment: High ├── Personalization: Full custom └── Tactics: Executive events, custom content

TIER 2: Scale (1:Few) ├── Account count: 50-200 ├── Investment: Medium ├── Personalization: Segment-based └── Tactics: Industry content, targeted ads

TIER 3: Programmatic (1:Many) ├── Account count: 500+ ├── Investment: Low per account ├── Personalization: Light └── Tactics: Intent-based targeting

ABM Metrics

Metric Definition Target

Account Engagement % of accounts engaged 70%+

Contact Coverage % of buying committee reached 50%+

Pipeline Created $ from target accounts $X

Deal Velocity Days in pipeline Reduce by 20%

Attribution & Reporting

Attribution Models

First Touch: 100% to first interaction Last Touch: 100% to last interaction before conversion Linear: Equal credit across all touches Time Decay: More credit to recent touches W-Shaped: 30% first, 30% MQL, 30% opportunity, 10% other

Demand Gen Dashboard

┌─────────────────────────────────────────────────────────────┐ │ Demand Gen Performance - [Month] │ ├─────────────────────────────────────────────────────────────┤ │ Leads MQLs Pipeline Revenue │ │ 5,432 823 $2.4M $580K │ │ +15% MoM +22% MoM +18% MoM +12% MoM │ ├─────────────────────────────────────────────────────────────┤ │ Channel Performance │ │ Email: 2,100 leads ($15 CPL) │ │ Paid Search: 1,500 leads ($45 CPL) │ │ Social: 1,200 leads ($38 CPL) │ │ Organic: 632 leads ($0 CPL) │ ├─────────────────────────────────────────────────────────────┤ │ Campaign Performance │ │ Q4 Webinar Series: 425 MQLs, $890K pipeline │ │ Ebook Campaign: 312 MQLs, $650K pipeline │ └─────────────────────────────────────────────────────────────┘

Reference Materials

• references/campaign_playbook.md

• Campaign execution guide

• references/lead_scoring.md

• Scoring methodology

• references/automation.md

• Marketing automation patterns

• references/abm_guide.md

• ABM program guide

Scripts

Campaign performance analyzer

python scripts/campaign_analyzer.py --campaign "Q4 Webinar"

Lead scoring calculator

python scripts/lead_scoring.py --leads leads.csv --model scoring_model.yaml

Attribution reporter

python scripts/attribution.py --model w-shaped --period Q4

Funnel analyzer

python scripts/funnel_analyzer.py --data funnel_data.csv