Account-Based Marketing Specialist
Strategic expertise in account-based marketing for enterprise growth.
Core Competencies
ABM Strategy
- •Account selection
- •Tier definition
- •Persona mapping
- •Play development
- •Sales alignment
Campaign Orchestration
- •Multi-channel coordination
- •Personalization at scale
- •Timing and sequencing
- •Content mapping
- •Touchpoint optimization
Measurement
- •Account engagement scoring
- •Pipeline attribution
- •ABM ROI
- •Coverage metrics
- •Influence tracking
ABM Tier Framework
Tier 1: Strategic (1:1)
- •Accounts: 10-50
- •Investment: High
- •Personalization: Fully custom
- •Content: Bespoke for each account
- •Plays: Executive engagement, custom events
Tier 2: Scale (1:Few)
- •Accounts: 50-500
- •Investment: Medium
- •Personalization: Industry/segment
- •Content: Templated with personalization
- •Plays: Industry campaigns, webinars
Tier 3: Programmatic (1:Many)
- •Accounts: 500+
- •Investment: Lower per account
- •Personalization: Automated
- •Content: Dynamic fields
- •Plays: Targeted advertising, sequences
ABM Plays
Executive Engagement
- •Executive briefings
- •Advisory boards
- •VIP events
- •Executive sponsorship
Digital Engagement
- •Personalized ads
- •Custom landing pages
- •Targeted content
- •Retargeting
Direct Engagement
- •Direct mail
- •Personalized gifts
- •Custom experiences
- •Field events
Account Selection Framework
ICP (Ideal Customer Profile)
code
Firmographic Criteria: - Industry: SaaS, FinTech, Healthcare - Company size: 500-5000 employees - Revenue: $50M-$500M - Geography: North America, Europe Technographic Criteria: - Current tech stack alignment - Integration compatibility - Digital maturity level Intent Signals: - Researching solution category - Competitor engagement - Content consumption patterns
Account Scoring Model
python
def calculate_account_score(account):
score = 0
# Firmographic fit (40%)
score += firmographic_score(account) * 0.4
# Technographic fit (20%)
score += technographic_score(account) * 0.2
# Intent signals (25%)
score += intent_score(account) * 0.25
# Engagement history (15%)
score += engagement_score(account) * 0.15
return score
def assign_tier(score):
if score >= 80:
return "Tier 1"
elif score >= 60:
return "Tier 2"
else:
return "Tier 3"
Account Engagement Scoring
| Activity | Points |
|---|---|
| Website visit | 1 |
| Content download | 5 |
| Event registration | 10 |
| Demo request | 25 |
| Meeting scheduled | 50 |
| Opportunity created | 100 |
Multi-Threading Strategy
Persona Map
code
C-Suite: - CEO: Business outcomes, ROI - CFO: Cost reduction, efficiency - CTO: Technical capabilities, security Directors: - VP Sales: Revenue impact - VP Marketing: Pipeline contribution - VP Operations: Process improvement Users: - Managers: Day-to-day workflow - End users: Ease of use, adoption
Engagement Sequence
code
Week 1: Research & mapping - Identify all stakeholders - Map reporting structure - Find common connections Week 2-4: Initial outreach - LinkedIn engagement - Personalized emails - Content sharing Week 5-8: Value delivery - Custom content - Industry insights - Peer introductions Week 9-12: Meeting conversion - Multi-threading emails - Executive referrals - Event invitations
ABM Tech Stack
- •Orchestration: 6sense, Demandbase, Terminus
- •Intent Data: Bombora, G2
- •Advertising: LinkedIn, Display
- •Personalization: Mutiny, PathFactory
- •Gifting: Sendoso, Postal
- •CRM: Salesforce, HubSpot
- •Analytics: Tableau, Looker
Measurement Framework
Leading Indicators
- •Account coverage (% of personas engaged)
- •Account engagement score
- •Content consumption
- •Meeting conversion rate
Lagging Indicators
- •Pipeline generated
- •Pipeline velocity
- •Win rate by tier
- •Average deal size
- •Customer acquisition cost
ROI Calculation
code
ABM ROI = (Revenue from ABM accounts - ABM investment) / ABM investment ABM Investment includes: - Technology costs - Content creation - Advertising spend - Events & gifts - Headcount allocation
Best Practices
- •Start small - Pilot with 10-20 accounts before scaling
- •Align with sales - Weekly syncs on target accounts
- •Personalize genuinely - Generic personalization backfires
- •Multi-thread early - Don't rely on single champion
- •Measure incrementally - Compare ABM vs non-ABM cohorts
- •Iterate plays - Test and optimize continuously