Initial commit: moreminimore-service content pipeline
- 9 mm* skills (orchestrator, article, social, publish, analytics) - 6 dependency skills (content-writer, geo-optimizer, etc.) - 3 analytics scripts (GSC, Google Ads, Meta Ads) - Config template + setup guide - SOUL-MM.md persona extension - OrbitOS integration reference
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Kunthawat Greethong
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skills/mm-analytics/SKILL.md
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skills/mm-analytics/SKILL.md
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---
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name: mm-analytics
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description: >
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Analyze website SEO performance (Google Search Console) and ad campaign
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performance (Google Ads, Meta Ads) for a client. Produces insights and
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recommendations for content and marketing strategy.
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Use when: "analytics", "วิเคราะห์", "ดูสถิติ", "performance report",
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"seo report", "ad performance", "mm analytics", "ดูผล".
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---
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# mm-analytics
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Analyzes SEO and ad performance for a client, produces insights and recommendations.
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## When This Must Trigger
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- "analytics", "วิเคราะห์", "ดูสถิติ", "performance report"
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- "seo report", "ad performance", "mm analytics", "ดูผล"
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- "วิเคราะห์เว็บ", "ดู traffic", "ดู campaign"
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## Scripts Location
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All scripts are in `~/Gitea/moreminimore-service-system/scripts/`:
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- `mm_gsc.py` — Google Search Console analytics
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- `mm_google_ads.py` — Google Ads analytics
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- `mm_meta_ads.py` — Meta Ads analytics
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## Process
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### Step 1: Determine client and analysis type
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```
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ต้องการวิเคราะห์อะไร?
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1. 🌐 SEO (Google Search Console) — traffic, queries, rankings
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2. 📢 Google Ads — campaign performance, keywords
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3. 📱 Meta Ads — Facebook/Instagram ad performance
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4. 📊 ทั้งหมด — comprehensive report
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```
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### Step 2: Run analytics scripts
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#### 2a. SEO Analytics (GSC)
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```bash
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cd ~/Gitea/moreminimore-service-system/scripts
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python3 mm_gsc.py --client <client-id> --days 90
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```
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Output:
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- Top queries by impressions, clicks, CTR
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- Top pages by traffic
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- Position distribution (top 3, 4-10, 11-20, 21+)
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- Traffic trends (increasing/decreasing)
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- Content gap opportunities
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#### 2b. Google Ads Analytics
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```bash
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cd ~/Gitea/moreminimore-service-system/scripts
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python3 mm_google_ads.py --client <client-id> campaigns
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python3 mm_google_ads.py --client <client-id> keywords
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python3 mm_google_ads.py --client <client-id> stats --days 30
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```
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Output:
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- Active campaigns with performance metrics
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- Keyword performance (impressions, clicks, CTR, CPC, QS)
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- Campaign stats with cost per conversion
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#### 2c. Meta Ads Analytics
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```bash
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cd ~/Gitea/moreminimore-service-system/scripts
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python3 mm_meta_ads.py --client <client-id> campaigns
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python3 mm_meta_ads.py --client <client-id> stats --days 30
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```
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Output:
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- Active campaigns with objectives and budgets
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- Performance stats (impressions, clicks, spend, reach, CTR, CPC)
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### Step 3: Analyze and produce insights
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After collecting data, analyze for:
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**SEO Insights:**
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- Queries with high impressions but low CTR → title/description optimization
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- Queries ranking 4-10 → quick win opportunities
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- Pages losing traffic → content refresh needed
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- Content gaps → new article topics
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- GEO opportunities → AI search optimization
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**Ad Insights:**
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- Campaigns with high CPA → optimize targeting/creative
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- Keywords with low QS → improve ad relevance
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- Ad fatigue signals → refresh creative
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- Budget allocation → shift spend to better performers
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**Cross-channel Insights:**
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- SEO queries that match ad keywords → organic vs paid synergy
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- Content topics that perform well in ads → create organic content
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- Landing page performance → conversion optimization
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### Step 4: Generate recommendations
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Produce actionable recommendations:
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```
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📋 Analytics Report: [Client Name]
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📅 Period: [date range]
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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🌐 SEO Performance
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Top Queries: [list]
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Top Pages: [list]
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Traffic Trend: [↑/↓/→]
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⚡ Quick Wins:
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1. [Query] — position [X], [Y] impressions → optimize title
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2. [Page] — losing traffic → refresh content
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📝 Content Opportunities:
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1. [Topic] — high search volume, no content → write article
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2. [Topic] — ranking 11-20 → expand existing content
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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📢 Google Ads Performance
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Campaigns: [N] active
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Total Spend: ฿[X]
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Avg CPA: ฿[X]
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ROAS: [X]x
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⚡ Recommendations:
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1. [Campaign] — high CPA → adjust targeting
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2. [Keyword] — low QS → improve ad relevance
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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📱 Meta Ads Performance
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Campaigns: [N] active
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Total Spend: ฿[X]
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Reach: [X]
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CTR: [X]%
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⚡ Recommendations:
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1. [Campaign] — low CTR → refresh creative
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2. [Ad Set] — high frequency → new audience
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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📋 Next Actions
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Content:
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1. Write article about [topic] (from SEO gap)
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2. Refresh [page] (losing traffic)
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Ads:
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1. Optimize [campaign] (high CPA)
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2. Refresh [ad creative] (fatigue)
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Strategy:
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1. [Recommendation based on cross-channel data]
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```
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### Step 5: Save report
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Save analytics report to:
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```
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~/vault/60_Articles/<client-id>/analytics/YYYY-MM-DD-report.md
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```
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## Integration with Content Pipeline
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The analytics feed back into the content pipeline:
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1. **SEO gaps** → become new article topics (mm-article-idea-extract)
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2. **Top performing content** → inform future content strategy
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3. **Ad performance** → inform CTA and messaging for ad copy
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4. **Cross-channel insights** → optimize overall marketing strategy
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## Error Handling
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If a script fails:
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- Check if credentials are configured in clients-config.json
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- Check if the API is enabled (Google Ads API, Meta Marketing API)
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- Check if the access token is valid
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```
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❌ [Script] failed: [error]
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สาเหตุที่เป็นไปได้:
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- Credentials ไม่ถูกต้อง → ตรวจสอบ clients-config.json
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- API ไม่ได้เปิดใช้งาน → เปิดใช้ใน Google Cloud / Meta Developer
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- Token หมดอายุ → ต่ออายุ token
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ต้องการ:
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1. ลองใหม่
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2. ข้าม → วิเคราะห์เฉพาะส่วนที่ใช้ได้
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```
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## Notes
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- All scripts read from `~/vault/99_System/clients-config.json`
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- GSC uses service account key from `global.google.service_account_key`
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- Google Ads uses developer_token + gcloud ADC for authentication
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- Meta Ads uses page_token or system_user_token from config
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- Reports are saved to the client's vault folder for reference
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