diegosouzapw 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)
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
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
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
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
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