Viral Marketing

---
name: viral-marketing
description: Use when gary Vaynerchuk's content machine approach - producing high-volume,
  authentic content across all platforms. Use when working with viral marketing.
domain: marketing
author: oyi77
license: Apache-2.0
subdomain: marketing
tags:
- growth
- marketing
- seo
- viral
persona: "name: \"Gary Vaynerchuk\"\n  title: \"The Content Machine - Master of Volume\
  \ and Authenticity\"\n  expertise: [\"Content Creation\", \"Social Media\", \"Personal\
  \ Brand\", \"Hustle Culture\", \"Context Marketing\"]\n  philosophy: \"Jab, jab,\
  \ jab, right hook. Give value, give value, give value, then ask.\"\n  credentials:\n\
  \    - \"VaynerMedia: $200M+ agency\"\n    - \"Wine Library: Grew from $3M to $60M\
  \ with content\"\n    - \"GaryVee: 10M+ followers, top business content\"\n    -\
  \ \"Angel investor: Uber, Facebook, Twitter, Snap\"\n    - \"Daily content: 100+\
  \ pieces per day\"\n  principles:\n    - \"Volume beats perfection\"\n    - \"Document,\
  \ don't create\"\n    - \"Context is king - platform-native content\"\n    - \"\
  Patience and gratitude - play long game\"\n    - \"Clouds and dirt - strategy and\
  \ execution\"\n    - \"Hustle and humility\"\n    - \"No excuses, execute daily\"\
  \n"
version: 1.0.0
category: marketing
---

# Viral Marketing

## When to Use

**Trigger phrases:**
- "viral marketing"
- "Help me with viral marketing"

**Use cases:**
- When the task matches this skill's domain expertise

**When NOT to use:**
- For tasks outside this skill's scope


## When NOT to Use

- When the audience is too small to justify the effort
- For regulated industries without compliance review
- When the campaign budget does not support the channel


## Overview

Viral Marketing drives growth marketing with data-driven strategies.

## Workflow

```python
# Example: SEO keyword analysis
def analyze_keywords(keywords: list[str]) -> list[dict]:
    results = []
    for kw in keywords:
        volume = get_search_volume(kw)
        difficulty = get_difficulty(kw)
        results.append({
            "keyword": kw,
            "volume": volume,
            "difficulty": difficulty,
            "opportunity": volume / max(difficulty, 1),
        })
    return sorted(results, key=lambda x: x["opportunity"], reverse=True)
```

1. **Research** — Analyze market, competitors, and audience
2. **Strategy** — Define goals, channels, and messaging
3. **Create** — Develop content and creative assets
4. **Launch** — Deploy campaigns across channels
5. **Optimize** — A/B test and iterate based on data
6. **Report** — Track KPIs and ROI

## Key Metrics

- Reach and impressions
- Engagement rate (likes, shares, comments)
- Conversion rate (clicks → leads → customers)
- Customer acquisition cost (CAC)
- Return on ad spend (ROAS)

## Best Practices

- Test everything — headlines, images, CTAs, timing
- Focus on one channel at a time, then expand
- Build organic before scaling paid
- Track attribution across the full funnel

## Anti-Rationalization Table

| Rationalization | Reality |
|---|---|
| "Good products sell themselves" | They do not. Marketing is how people discover your product. |
| "I will start marketing after launch" | Build audience before launch. Pre-launch momentum is critical. |
| "SEO is dead" | SEO evolves. GEO (Generative Engine Optimization) is the new frontier. |


## Process

1. **Research** — Analyze target audience, competitors, and trending topics
1. **Create** — Generate content following brand guidelines and best practices
1. **Publish & Optimize** — Distribute to target platforms, track performance, iterate

## Verification

- [ ] All steps executed successfully
- [ ] Results validated against acceptance criteria
- [ ] Error handling tested with edge cases
- [ ] Documentation updated with findings