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Get Started Free →Creates demand generation campaigns, optimizes paid ad spend across LinkedIn, Google, and Meta, develops SEO strategies, and structures partnership programs for Series A+ startups scaling internationally. Use when planning marketing strategy, growth marketing, advertising campaigns, PPC optimization, lead generation, pipeline generation, or startup marketing budgets. Covers multi-channel acquisition (Google Ads, LinkedIn Ads, Meta Ads), CAC analysis, MQL/SQL workflows, attribution modeling, tech
.claude/skills/marketing-demand-acquisition/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | — | — |
| case-19 | ✗→✓ | ▲ Improved | — | — |
| case-22 | ✗→✓ | ▲ Improved | — | — |
| case-20 | ✗→✓ | ▲ Improved | — | — |
| case-10 | ✗→✓ | ▲ Improved | — | — |
Acquisition playbook for Series A+ startups scaling internationally (EU/US/Canada) with hybrid PLG/Sales-Led motion.
Demand Gen: MQL/SQL volume, cost per opportunity, marketing-sourced pipeline $, MQL→SQL rate
Paid Media: CAC, ROAS, CPL, CPA, channel efficiency ratio
SEO: Organic sessions, non-brand traffic %, keyword rankings, technical health score
Partnerships: Partner-sourced pipeline $, partner CAC, co-marketing ROI
| Stage | Tactics | Target | |-------|---------|--------| | TOFU | Paid social, display, content syndication, SEO | Brand awareness, traffic | | MOFU | Paid search, retargeting, gated content, email nurture | MQLs, demo requests | | BOFU | Brand search, direct outreach, case studies, trials | SQLs, pipeline $ |
utm_source={channel} // linkedin, google, meta
utm_medium={type} // cpc, display, email
utm_campaign={campaign-id} // q1-2025-linkedin-enterprise
utm_content={variant} // ad-a, email-1
utm_term={keyword} // [paid search only]| Channel | Best For | CAC Range | Series A Priority | |---------|----------|-----------|-------------------| | LinkedIn Ads | B2B, Enterprise, ABM | $150-400 | High | | Google Search | High-intent, BOFU | $80-250 | High | | Google Display | Retargeting | $50-150 | Medium | | Meta Ads | SMB, visual products | $60-200 | Medium |
| Channel | Budget | Expected SQLs | |---------|--------|---------------| | LinkedIn | $15k | 10 | | Google Search | $12k | 20 | | Google Display | $5k | 5 | | Meta | $5k | 8 | | Partnerships | $3k | 5 |
See campaign-templates.md for detailed structures.
| Tier | Type | Volume | Priority | |------|------|--------|----------| | 1 | High-intent BOFU | 100-1k | First | | 2 | Solution-aware MOFU | 500-5k | Second | | 3 | Problem-aware TOFU | 1k-10k | Third |
| Tier | Type | Effort | ROI | |------|------|--------|-----| | 1 | Strategic integrations | High | Very high | | 2 | Affiliate partners | Medium | Medium-high | | 3 | Customer referrals | Low | Medium | | 4 | Marketplace listings | Medium | Low-medium |
See international-playbooks.md for regional tactics.
| Model | Use Case | |-------|----------| | First-Touch | Awareness campaigns | | Last-Touch | Direct response | | W-Shaped (40-20-40) | Hybrid PLG/Sales (recommended) |
| Metric | Target | |--------|--------| | MQLs | Weekly target | | SQLs | Weekly target | | MQL→SQL Rate | >15% | | Blended CAC | <$300 | | Pipeline Velocity | <60 days |
See attribution-guide.md for detailed setup.
| Script | Purpose | Usage | |--------|---------|-------| | calculate_cac.py | Calculate blended and channel CAC | python scripts/calculate_cac.py --spend 40000 --customers 50 |
See hubspot-workflows.md for workflow templates.
| File | Content | |------|---------| | hubspot-workflows.md | Lead scoring, nurture, assignment workflows | | campaign-templates.md | LinkedIn, Google, Meta campaign structures | | international-playbooks.md | EU, US, Canada market tactics | | attribution-guide.md | Multi-touch attribution, dashboards, A/B testing |
| Metric | LinkedIn | Google Search | SEO | Email | |--------|----------|---------------|-----|-------| | CTR | 0.4-0.9% | 2-5% | 1-3% | 15-25% | | CVR | 1-3% | 3-7% | 2-5% | 2-5% | | CAC | $150-400 | $80-250 | $50-150 | $20-80 | | MQL→SQL | 10-20% | 15-25% | 12-22% | 8-15% |
Required:
✅ Job title: Director+ or budget authority
✅ Company size: 50-5000 employees
✅ Budget: $10k+ annual
✅ Timeline: Buying within 90 days
✅ Engagement: Demo requested or high-intent action| Handoff | Target | |---------|--------| | SDR responds to MQL | 4 hours | | AE books demo with SQL | 24 hours | | First demo scheduled | 3 business days |
Validation: Test lead through workflow, verify notifications and routing.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-02 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-01 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-03 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-19 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-22 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-20 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-24 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-06 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-10 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-13 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-18 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-07 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-21 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-12 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-14 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-25 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-09 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-23 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-08 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-05 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-11 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-15 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-04 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-16 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-17 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 25 cases were attempted. The headline lift of +52 percentage points is the difference between those two pass rates over the 25 comparable cases.
The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.
Other measured skills in the registry, with their headline benchmark lift.