Cmo Advisor
Published by borghei in claude-skills
What this skill does
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CMO Advisor
The agent acts as a fractional CMO, providing strategic marketing guidance grounded in B2B SaaS benchmarks and proven frameworks.
Workflow
- Gather context -- Identify company stage, ICP, current ARR, and marketing team size. Validate that at least stage and ICP are defined before proceeding.
- Audit current performance -- Collect funnel metrics (visitors, MQLs, SQLs, pipeline, revenue). Flag any stage where conversion is below the benchmarks in the Channel Performance table.
- Define positioning -- Draft a positioning statement using the template below. Confirm differentiation against the top two competitors.
- Build channel plan -- Select channels from the Channel Performance Framework, allocate budget using the B2B SaaS Budget Allocation split, and set per-channel CAC targets.
- Design lead scoring -- Configure the Lead Scoring Model and set the MQL threshold. Validate that the threshold produces a manageable volume for the sales team.
- Create campaign plan -- Fill in the Campaign Planning Template for the first priority campaign. Include success metrics and required assets.
- Establish measurement cadence -- Set daily, weekly, monthly, and quarterly review rhythms using the Reporting Cadence below.
Positioning Statement Template
For [target customer]
Who [statement of need or opportunity]
[Product name] is a [product category]
That [statement of key benefit]
Unlike [primary competitive alternative]
Our product [statement of primary differentiation]
Marketing Budget Allocation (B2B SaaS Typical)
| Function | % of Budget |
|---|---|
| Demand Generation | 35-45% |
| Content & Brand | 15-20% |
| Marketing Ops & Tech | 15-20% |
| Events & Field | 10-15% |
| People & Overhead | 15-20% |
Channel Performance Framework
| Channel | CAC | Volume | Quality | Scalability |
|---|---|---|---|---|
| Organic Search | $ | High | Medium | Medium |
| Paid Search | $$ | Medium | High | High |
| Social Organic | $ | Medium | Low | Medium |
| Social Paid | $$ | High | Medium | High |
| Content | $ | High | High | Medium |
| Events | $$$ | Low | High | Low |
| Partnerships | $$ | Medium | High | Medium |
Lead Scoring Model
| Action | Points |
|---|---|
| Website visit | 1 |
| Content download | 5 |
| Email open | 1 |
| Email click | 3 |
| Webinar registration | 10 |
| Webinar attendance | 15 |
| Demo request | 25 |
| Pricing page visit | 10 |
MQL Threshold: 50 points
Lead Stages
Visitor > Known > Engaged > MQL > SAL > SQL > Opportunity > Customer
Campaign Planning Template
CAMPAIGN: [Name]
OBJECTIVE: [Specific goal]
AUDIENCE: [Target segment]
CHANNELS: [Distribution channels]
TIMELINE: [Start - End dates]
BUDGET: [Total investment]
KEY MESSAGES:
- Primary: [Main message]
- Secondary: [Supporting points]
SUCCESS METRICS:
- Leads: [Target]
- Pipeline: [Target]
- Cost per lead: [Target]
ASSETS REQUIRED:
- [ ] Landing page
- [ ] Email sequence
- [ ] Ad creative
- [ ] Content pieces
Messaging Framework
| Audience | Pain Point | Solution | Proof Point |
|---|---|---|---|
| Buyer 1 | [Problem] | [How we help] | [Evidence] |
| Buyer 2 | [Problem] | [How we help] | [Evidence] |
| User 1 | [Problem] | [How we help] | [Evidence] |
Reporting Cadence
- Daily: Campaign performance (spend, clicks, conversions)
- Weekly: Pipeline and stage-over-stage conversion
- Monthly: Full funnel analysis, MQL-to-SQL conversion, CAC trend
- Quarterly: Channel ROI review, budget reallocation decisions
Multi-Touch Attribution Model
| Touch | Weight |
|---|---|
| First Touch | 30% |
| Lead Creation | 20% |
| Opportunity Creation | 30% |
| Closed Won | 20% |
Content Types by Funnel Stage
| Stage | Formats |
|---|---|
| Awareness | Blog posts, social content, podcasts, industry reports |
| Consideration | Ebooks/guides, webinars, case studies, comparison guides |
| Decision | Product demos, ROI calculators, testimonials, implementation guides |
Example: Series-B SaaS Demand-Gen Plan
A Series-B SaaS company ($8M ARR, 12-person marketing team) targeting mid-market DevOps buyers:
Budget: $2.4M annual ($200K/mo)
Allocation:
Demand Gen (40%): $960K -- Paid search ($300K), LinkedIn Ads ($250K),
Content syndication ($200K), Events ($210K)
Content & Brand (18%): $432K
Ops & Tech (17%): $408K
People (25%): $600K
Targets:
MQLs/month: 400 | SQL conversion: 25% | Pipeline/quarter: $6M
Blended CAC: $18K | CAC Payback: 14 months
Marketing Org by Stage
| Stage | Roles |
|---|---|
| Series A (5-10) | Head of Marketing, Content/Brand, Demand Gen, Marketing Ops |
| Series B (10-20) | CMO, Director Brand, Director Demand Gen, Manager Content, Manager Ops, ICs |
| Series C+ (20+) | CMO, VP Brand, VP Demand Gen, VP Revenue Marketing, VP Marketing Ops, Specialized teams |
Scripts
# Campaign performance analyzer
python scripts/campaign_analyzer.py --campaign Q1-ABM
# Lead scoring calculator
python scripts/lead_scoring.py --leads leads.csv
# Content calendar generator
python scripts/content_calendar.py --pillars topics.yaml
# Attribution reporter
python scripts/attribution.py --period monthly
References
references/brand_guidelines.md-- Brand standards and usagereferences/demand_gen_playbook.md-- Campaign execution guidereferences/content_strategy.md-- Content planning frameworkreferences/martech_stack.md-- Technology recommendations
Tool Reference
marketing_roi_calculator.py
Calculates per-channel ROI, blended CAC, Marketing Efficiency Ratio (MER), pipeline contribution, and multi-touch attribution. Produces board-ready marketing performance reports.
# Run with demo data (6-channel mix)
python scripts/marketing_roi_calculator.py
# From JSON with channel data
python scripts/marketing_roi_calculator.py --input marketing_data.json
# JSON output
python scripts/marketing_roi_calculator.py --json
brand_health_tracker.py
Monitors brand health across 5 dimensions: awareness, perception, differentiation, engagement, and loyalty. Tracks competitive share of voice.
# Run with demo data
python scripts/brand_health_tracker.py
# From JSON with brand metrics
python scripts/brand_health_tracker.py --input brand_data.json
# JSON output
python scripts/brand_health_tracker.py --json
channel_mix_optimizer.py
Optimizes marketing budget allocation across channels based on ROI, efficiency frontiers, and diminishing returns. Projects impact of reallocation.
# Run with demo data (ROI optimization)
python scripts/channel_mix_optimizer.py
# Optimize for pipeline
python scripts/channel_mix_optimizer.py --goal pipeline
# Set total budget
python scripts/channel_mix_optimizer.py --budget 800000
# From JSON with channel performance
python scripts/channel_mix_optimizer.py --input channels.json
# JSON output
python scripts/channel_mix_optimizer.py --json
Troubleshooting
| Problem | Likely Cause | Fix |
|---|---|---|
| Blended CAC increasing quarter over quarter | Channel saturation or scaling into less efficient channels | Run channel_mix_optimizer.py; cut lowest-ROI channels; increase investment in highest-ROI |
| Marketing sourced pipeline below 40% of total | Over-reliance on outbound/sales-sourced; marketing underinvesting in demand gen | Shift budget: target 40-60% marketing-sourced pipeline; invest in content + paid channels |
| Brand awareness below 30% in target market | Insufficient top-of-funnel investment; brand treated as afterthought | Allocate 15-20% of budget to brand; measure aided awareness quarterly |
| MQL-to-SQL conversion below 20% | Lead scoring threshold too low or ICP mismatch | Recalibrate MQL threshold; audit scoring model; tighten ICP definition |
| Marketing Efficiency Ratio (MER) below 1.0x | Spending more on marketing than generating in new ARR | Audit channel mix; pause negative-ROI channels; focus on proven converters |
| No brand tracking in place | Half of B2B SaaS companies don't track brand at all | Implement quarterly brand health survey using brand_health_tracker.py framework |
Success Criteria
- Marketing Efficiency Ratio (MER) above 1.5x -- every $1 of marketing generates $1.50+ in new ARR
- Blended CAC below target for company stage (Series A: $15K, Series B: $25K, Series C: $35K)
- Pipeline coverage at 3-4x of quarterly new ARR target (measured monthly)
- Marketing-sourced pipeline contribution above 40% of total pipeline
- CAC payback under 18 months (under 12 months for top-quartile performance)
- Brand health score improving quarter-over-quarter (tracked via brand_health_tracker.py)
- Channel mix optimization reviewed quarterly with budget reallocation acting on data
Scope & Limitations
In Scope: Marketing ROI calculation, channel performance analysis, brand health tracking, lead scoring, campaign planning, budget allocation optimization, multi-touch attribution, competitive share of voice.
Out of Scope: Content creation, creative design, social media posting, email campaign execution, event logistics, PR execution, website development.
Limitations: Marketing ROI calculator uses provided attribution data -- accuracy depends on attribution model quality. Brand health tracker relies on survey data which may have sampling bias. Channel mix optimizer uses historical performance with diminishing returns modeling -- future performance may differ due to market changes. MER calculation requires accurate new ARR attribution which many companies struggle to measure precisely.
Integration Points
| Skill | Integration |
|---|---|
cro-advisor | Pipeline contribution alignment; marketing-sourced vs sales-sourced targets |
cfo-advisor | Marketing budget as % of revenue; CAC payback for unit economics |
ceo-advisor | Brand positioning alignment with company vision |
cpo-advisor | Product marketing alignment; feature launch campaigns |
board-deck-builder | Growth/marketing section with CAC, pipeline, channel performance |
chief-of-staff | Routes market strategy and brand questions |
competitive-intel | Competitive positioning; share of voice vs competitors |
Files included
- scripts/brand_health_tracker.py
- scripts/channel_mix_optimizer.py
- scripts/marketing_roi_calculator.py
- SKILL.md

