Best use case
campaign-analytics is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
It is a strong fit for teams already working in Codex.
Project directory path (default current directory)
Teams using campaign-analytics should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/campaign-analytics/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How campaign-analytics Compares
| Feature / Agent | campaign-analytics | Standard Approach |
|---|---|---|
| Platform Support | Codex | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Project directory path (default current directory)
Which AI agents support this skill?
This skill is designed for Codex.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Marketing
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Best AI Agents for Marketing
A curated list of the best AI agents and skills for marketing teams focused on SEO, content systems, outreach, and campaign execution.
Cursor vs Codex for AI Workflows
Compare Cursor and Codex for AI coding workflows, repository assistance, debugging, refactoring, and reusable developer skills.
SKILL.md Source
# Campaign Analytics Command
Generate comprehensive campaign performance analysis with insights and optimization recommendations.
## What This Command Does
1. **Collects Performance Data**
- Channel-level metrics
- Conversion funnel data
- Attribution analysis
2. **Analyzes Performance**
- KPI achievement
- Trend analysis
- Comparative benchmarks
3. **Generates Recommendations**
- Optimization opportunities
- Budget reallocation suggestions
- Strategic insights
## Orchestration Flow
```
Campaign Analytics Request
↓
[Marketing Analyst] → Performance Analysis
↓
[Data Analyst] → Data Quality & Processing
↓
[Attribution Specialist] → Attribution Analysis
↓
[Reporting Specialist] → Report Generation
↓
[Campaign Strategist] → Strategic Recommendations
↓
Comprehensive Campaign Report
```
## Agents Involved
| Agent | Role | Output |
|-------|------|--------|
| Marketing Analyst | Performance analysis | KPI tracking, insights |
| Data Analyst | Data processing | Clean data, validation |
| Attribution Specialist | Attribution | Channel contribution |
| Reporting Specialist | Reporting | Visualizations, report |
| Campaign Strategist | Strategy | Recommendations |
## Analysis Types
| Type | Scope | Use Case |
|------|-------|----------|
| Daily | Quick metrics snapshot | During launch |
| Weekly | Detailed channel review | Ongoing optimization |
| Final | Complete campaign analysis | Post-campaign |
| Deep-dive | Specific area analysis | Problem solving |
## Output Artifacts
Saved to `.aiwg/marketing/analytics/{campaign-name}/`:
- `performance-summary.md` - Executive summary
- `channel-analysis.md` - Channel-by-channel breakdown
- `attribution-report.md` - Attribution analysis
- `recommendations.md` - Optimization recommendations
- `final-report.md` - Comprehensive final report
## Parameter Handling
### --guidance Parameter
**Purpose**: Provide upfront direction to tailor priorities and approach
**Examples**:
```bash
--guidance "Focus on attribution across paid channels"
--guidance "Need deep-dive on email performance"
--guidance "Benchmark against Q3 results"
```
**How Applied**:
- Parse guidance for keywords: priority, timeline, audience, focus, constraints
- Adjust agent emphasis and output depth based on stated priorities
- Modify deliverable order based on timeline constraints
- Influence scope and detail level based on context
### --interactive Parameter
**Purpose**: Guide through discovery questions for comprehensive input
**Questions Asked** (if --interactive):
1. What specific metrics are you most interested in?
2. What time period should be analyzed?
3. Are there specific channels to focus on?
4. What benchmarks should we compare against?
5. Who is the audience for this report?
## Usage Examples
```bash
# Weekly analysis
/campaign-analytics "Spring Launch" --analysis-type weekly
# Final campaign report
/campaign-analytics "Q1 Awareness" --analysis-type final
# Deep-dive on specific issue
/campaign-analytics "Holiday Campaign" --analysis-type deep-dive
# With strategic guidance
/campaign-analytics "Example" --guidance "Your specific context here"
# Interactive mode
/campaign-analytics "Example" --interactive
```
## Success Criteria
- [ ] All channel data collected
- [ ] KPIs tracked against targets
- [ ] Attribution analysis complete
- [ ] Insights documented
- [ ] Actionable recommendations provided
- [ ] Report delivered to stakeholders
## References
- @$AIWG_ROOT/agentic/code/frameworks/media-marketing-kit/README.md — Media marketing kit framework overview
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Measurable KPI thresholds and analytics criteria
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/subagent-scoping.md — Multi-agent analytics orchestration
- @$AIWG_ROOT/docs/cli-reference.md — CLI referenceRelated Skills
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