# Analyze Influencer Campaign Performance

Influencer results are difficult to compare across creators, platforms, and attribution methods. This skill converts campaign data into scorecards, rankings, insights, and recommendations.

## Install

```bash
npx skillstore add aaron-he-zhu/performance-analyzer
```

## Metadata

- Status: approved
- Slug: aaron-he-zhu-performance-analyzer
- Version: 17.0.0
- Author version: 17.0.0
- Skillstore revision: r1
- Version status: valid
- Tree hash: df181fa721e44f4cd8de60d32df8fc8c5ad68b787e527dca83d59b88d5326394
- Author: aaron-he-zhu
- GitHub username: aaron-he-zhu
- License: Apache-2.0
- Repository: https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/influencer/measure/performance-analyzer
- Ref: d71c7417a35d5c2624161bd2fe8de8a41a362128
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: confirmation\_required
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: filesystem, external\_commands, network, env\_access
- Quality score: 38
- Quality tier: warning
- Public page: https://skillstore.pages.dev/skills/aaron-he-zhu-performance-analyzer
- Manifest: https://skillstore.pages.dev/api/skills/aaron-he-zhu-performance-analyzer/manifest

## Capabilities

- Scores campaign metrics against supplied targets and benchmarks.
- Ranks platforms, creators, content formats, and themes.
- Analyzes engagement quality, comment sentiment, and purchase intent signals.
- Maps conversions across promo codes, UTM links, direct attribution, and estimates.
- Identifies winning content patterns and underperformance causes.
- Produces prioritized learnings, roster decisions, and future campaign recommendations.

## Use Cases

- Review a completed campaign: Compare final results with targets and identify the strongest creators, platforms, and content.
- Optimize an active campaign: Find early underperformance and decide where to adjust creators, formats, or platform allocation.
- Build reusable benchmarks: Capture performance patterns and creator baselines for future planning and selection.

## Prompt Templates

### Score one campaign

```
Analyze [campaign] using these results, targets, and benchmarks: [data]. Summarize performance and list the three most important actions.
```

### Compare creators

```
Compare [creator list] for [campaign]. Rank them by reach, engagement, conversions, and efficiency. Explain each renewal recommendation.
```

### Find winning content

```
Analyze these post-level results and comments: [data]. Compare formats, themes, hooks, sentiment, and purchase intent. Identify patterns worth testing again.
```

### Run a full attribution review

```
Evaluate [campaign] across platforms and creators using [data]. Separate measured, user-provided, and estimated outcomes. Apply [significance criteria] before declaring winners.
```

## Limitations

- Requires campaign exports, screenshots, analytics, or metrics supplied by the user.
- Cannot verify missing benchmarks, attribution assumptions, or creator-reported data.
- Does not calculate complete dollar-level ROI or final C3 scores.
- YouTube retrieval requires an external connector and API key not included here.

## Best Practices

- Label every metric as measured, user-provided, calculated, or estimated.
- Supply campaign targets, comparison periods, and creator-level source data.
- Apply statistical and practical thresholds before declaring a winner.

## Anti Patterns

- Do not compare creators using totals when audience size and spend differ materially.
- Do not combine promo, UTM, and estimated conversions without checking overlap.
- Do not treat sentiment samples or screenshots as complete population data.

## Security Audit

- Audited at: 2026-07-12T13:24:17.252\+00:00
- Summary: Most alerts are false positives caused by Markdown links, code fences, placeholders, and metadata URLs. However, SKILL.md line 58 directs execution of an out-of-package Python connector and use of environment-held API credentials. Publication should require connector review, explicit network consent, and documented credential handling.

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