# Effect Monitoring

Use when monitoring Xiaohongshu marketing campaign performance, tracking promotion...

- Repository: https://github.com/vivy-yi/xiaohongshu-skills (520 stars)
- Category: Marketing
- License: see repository
- Last updated: 2026-01-23
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add vivy-yi/xiaohongshu-skills --skill effect-monitoring -g -a claude-code -y`
Codex: `npx skills add vivy-yi/xiaohongshu-skills --skill effect-monitoring -g -a codex -y`
Cursor: `npx skills add vivy-yi/xiaohongshu-skills --skill effect-monitoring -g -a cursor -y`
Gemini CLI: `npx skills add vivy-yi/xiaohongshu-skills --skill effect-monitoring -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add vivy-yi/xiaohongshu-skills`

## Description

Use when monitoring Xiaohongshu marketing campaign performance, tracking promotion effectiveness, analyzing advertising ROI, measuring influencer collaboration results, evaluating activity success rates, or optimizing marketing spend allocation

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Effect Monitoring (效果监测)

## Overview

Effect monitoring is the systematic tracking and analysis of marketing campaign performance on Xiaohongshu, measuring ROI, engagement, conversion, and overall impact to optimize future marketing investments and strategy decisions.

## When to Use

**Use when**:
- Running marketing campaigns (ads, KOL collaborations, activities)
- Tracking promotion performance and effectiveness
- Analyzing marketing ROI and cost per acquisition
- Evaluating influencer collaboration results
- Optimizing marketing spend and budget allocation
- Comparing performance across different campaigns
- Generating marketing performance reports

**Do NOT use when**:
- Monitoring daily content performance (use data-analytics)
- Tracking account growth metrics (use data-analytics)
- Analyzing organic engagement (use data-analytics)
- Monitoring non-marketing activities

## Core Pattern

**Before** (blind marketing, no measurement):
```
❌ "Launched campaign, spent ¥10,000, not sure how it performed"
❌ "Influencer posted, got some likes, unclear if it drove sales"
❌ "Multiple campaigns running, can't tell which is working"
❌ "No tracking, just hoping for the best"
```

**After** (data-driven monitoring and optimization):
```
✅ "Campaign A: ¥10,000 spend, ¥50,000 revenue, 5x ROAS, 12% conversion"
✅ "Influencer B: ¥5,000 fee, 100,000 views, 2.3% CTR, 350 conversions"
✅ "Campaign B outperformed A by 40% - reallocate budget next month"
✅ "Real-time dashboard shows campaign C underperforming, paused immediately"
```

**3-Level Monitoring Framework**:
1. **Exposure Level** - Views, impressions, reach, CPM
2. **Engagement Level** - Likes, comments, shares, saves, engagement rate
3. **Conversion Level** - Clicks, leads, sales, ROAS, CPA, customer acquisition cost

## Quick Reference

The rest: https://github.com/vivy-yi/xiaohongshu-skills/blob/HEAD/skills/07-营销推广/effect-monitoring/SKILL.md