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performance-marketer

performance-marketer

github.com/ncklrsMarketing & growth53221 installsUpdated 35w ago
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About performance-marketer

A performance marketing guidance skill for teams working on paid acquisition and conversion optimization. It organizes rules around ads, landing pages, testing, analytics, and budget allocation.

Key features

  1. 01Paid advertising strategy and creative guidance
  2. 02Landing page optimization
  3. 03A/B testing frameworks
  4. 04Attribution and conversion analytics
  5. 05Budget allocation and scaling guidance

Use cases

  1. 01Planning paid acquisition campaigns
  2. 02Improving landing page conversion
  3. 03Structuring A/B tests and experiments
  4. 04Reviewing attribution and campaign budgets

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/ncklrs/startup-os-skills --skill performance-marketer

After installing, type/performance-marketerin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

rules/
_sections.md
analytics-attribution.md
analytics-cac-ltv.md
analytics-conversion-tracking.md
budget-allocation.md
creative-ad-copy.md
creative-visual-guidelines.md
landing-page-optimization.md
paid-ads-strategy.md
retargeting-strategy.md
testing-ab-framework.md

Details

From the project README

Performance Marketer

Expert performance marketing guidance for paid acquisition, conversion rate optimization, and data-driven growth — from ad creative to attribution modeling.

Philosophy

Great performance marketing is a system, not a series of tactics:

  1. Measure what matters — Vanity metrics kill budgets
  2. Test with intention — Random A/B tests waste time and traffic
  3. Optimize the full funnel — A great ad to a bad landing page burns money
  4. Compound learnings — Every test teaches something for the next

How This Skill Works

When invoked, apply the guidelines in rules/ organized by:

  • paid-* — Paid advertising strategy, creative, and copy
  • landing-* — Landing page optimization
  • testing-* — A/B testing and experimentation frameworks
  • analytics-* — Attribution, CAC/LTV, and conversion tracking
  • budget-* — Budget allocation and scaling

Core Frameworks

The Performance Marketing Loop
┌─────────────────────────────────────────────────────────┐
│                                                         │
│   ┌──────────┐    ┌──────────┐    ┌──────────┐         │
│   │   ADS    │───▶│  LANDING │───▶│ CONVERT  │         │
│   │ (Reach)  │    │  (Hook)  │    │ (Action) │         │
│   └──────────┘    └──────────┘    └──────────┘         │
│        ▲                                │               │
│        │          ┌──────────┐          │               │
│        └──────────│ ANALYZE  │◀─────────┘               │
│                   │ (Learn)  │                          │
│                   └──────────┘                          │
│                                                         │
└─────────────────────────────────────────────────────────┘
The CAC/LTV Equation
MetricFormulaTarget
CACTotal Acquisition Cost / New CustomersLower is better
LTVAvg Revenue × Avg LifespanHigher is better
LTV:CACLTV / CAC3:1 or higher
Payback PeriodCAC / Monthly Revenue< 12 months
Funnel Math
Impressions × CTR = Clicks
Clicks × CVR = Conversions
Conversions × Close Rate = Customers
Customers × ARPU = Revenue
Channel Selection Matrix
ChannelBest ForTypical CACIntent Level
Google SearchHigh-intent capture$50-200High
Google DisplayRetargeting, awareness$20-80Low
Meta (FB/IG)B2C, visual products$30-100Medium
LinkedInB2B, enterprise$100-500Medium-High
Twitter/XTech audiences, awareness$40-150Low-Medium
TikTokGen Z, viral potential$20-60Low

Key Metrics by Stage

StagePrimary MetricSecondary Metrics
AwarenessImpressions, CPMFrequency, Reach
InterestCTR, CPCTime on site, Bounce rate
ConsiderationConversion rateMicro-conversions, Scroll depth
PurchaseCPA, ROASAOV, Conversion value
RetentionLTV, Repeat rateNPS, Churn rate

Budget Allocation Framework

The 70-20-10 Rule
  • 70% — Proven channels and campaigns (scale what works)
  • 20% — Optimization tests (improve what's working)
  • 10% — Experimentation (test new channels/approaches)
Scaling Checklist

Before scaling a campaign:

  • LTV:CAC ratio ≥ 3:1
  • Consistent performance over 2+ weeks
  • Statistical significance on key metrics
  • Landing page handles traffic spikes
  • Tracking verified on all conversion events

Anti-Patterns

  • Scaling too fast — Doubling budget overnight breaks algorithms
  • Testing everything at once — Can't learn what caused the change
  • Ignoring attribution — Last-click lies, multi-touch tells the truth
  • Copy-paste ads — Same creative across channels fails
  • Optimizing for clicks — Clicks don't pay bills, conversions do
  • Set and forget — Ads fatigue, audiences shift, competition changes
  • Vanity metrics — Impressions feel good, revenue feels better

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