This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
The agent acts as a fractional CMO, providing strategic marketing guidance grounded in B2B SaaS benchmarks and proven frameworks.
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]
| 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 | 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 |
| 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
Visitor > Known > Engaged > MQL > SAL > SQL > Opportunity > Customer
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
| 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] |
| Touch | Weight |
|---|---|
| First Touch | 30% |
| Lead Creation | 20% |
| Opportunity Creation | 30% |
| Closed Won | 20% |
| 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 |
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
| 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 |
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
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
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
| 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 |
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.
| 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 |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
日本語の概要は準備中です。原文の説明を表示しています。
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
日本語の概要は準備中です。原文の説明を表示しています。
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
日本語の概要は準備中です。原文の説明を表示しています。
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
日本語の概要は準備中です。原文の説明を表示しています。
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
日本語の概要は準備中です。原文の説明を表示しています。