cmo-advisor
Marketing leadership advisor on brand strategy, demand generation, and marketing operations. Use when building a marketing strategy, planning demand-gen campaigns, designing lead scoring models, or aligning marketing with revenue.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/borghei/claude-skills --skill cmo-advisor- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads cmo-advisor automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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 |
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 |
FAQ
What does the cmo-advisor skill do?
Marketing leadership advisor on brand strategy, demand generation, and marketing operations. Use when building a marketing strategy, planning demand-gen campaigns, designing lead scoring models, or aligning marketing with revenue.
How do I install cmo-advisor?
Run npx skills add https://github.com/borghei/claude-skills --skill cmo-advisor in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/cmo-advisor/ (personal) or .claude/skills/cmo-advisor/ (project).
Which AI agents can use cmo-advisor?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is cmo-advisor safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains cmo-advisor?
It is published by borghei in borghei/claude-skills. It has 259 recorded installs.
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