| name | meta-ads-reporting-hub |
| description | Generate and analyze Meta Ads reports for ecommerce - performance reports, metric analysis, attribution insights, executive summaries, and custom KPIs. Use when users ask for reports, dashboards, metrics explanation, attribution help, stakeholder updates, or performance summaries. Triggers include "generate report", "what does this metric mean", "attribution question", "report for my boss", "weekly summary", "monthly performance", "ROAS breakdown", "blended metrics", "MER calculation", "explain my data", "dashboard", or any reporting and analytics request. |
Reporting Hub Skill
Generate comprehensive Meta Ads reports and translate performance data into actionable insights for ecommerce businesses.
Skill Overview
The Reporting Hub skill helps ecommerce businesses understand their Meta Ads performance through standardized reports, metric explanations, attribution clarity, executive-friendly summaries, and custom KPI frameworks. It bridges the gap between raw data and business decisions.
Core Principle: Data Storytelling (2026)
REPORTS SHOULD DRIVE ACTION
COMMON MISTAKE:
"Here are your numbers" (data dump)
→ Stakeholders confused
→ No clear next steps
→ Decisions delayed
BETTER APPROACH:
"Here's what happened, why, and what to do"
→ Context + insight + recommendation
→ Clear narrative
→ Immediate action items
KEY INSIGHT:
The best report is one that answers questions before they're asked.
Every metric should connect to a business outcome.
When to Use This Skill
Use reporting-hub when:
- Generating daily, weekly, or monthly reports
- Explaining what a specific metric means
- Clarifying attribution windows and models
- Creating reports for non-technical stakeholders
- Calculating custom metrics (MER, Blended ROAS, nROAS)
- Building automated report templates
- Answering "how are my ads doing?"
- Translating performance data into business language
Reference Files
When to Load Each Reference
| File | Load When |
|---|
references/report-templates.md | Creating any standardized report (daily/weekly/monthly) |
references/metric-definitions.md | User asks what a metric means, needs clarification |
references/attribution-explained.md | Questions about attribution windows, conversions, tracking |
references/executive-summaries.md | Reports for non-technical stakeholders, leadership updates |
references/custom-metrics.md | Calculating MER, Blended ROAS, nROAS, contribution margin |
Reporting Decision Tree
REPORTING REQUEST RECEIVED
│
├─► What type of report?
│ │
│ ├─► PERFORMANCE REPORT
│ │ │
│ │ ├─► Daily check-in
│ │ │ └─► Load: report-templates.md (daily section)
│ │ │ Quick health metrics, pacing, alerts
│ │ │
│ │ ├─► Weekly summary
│ │ │ └─► Load: report-templates.md (weekly section)
│ │ │ Trend analysis, creative winners, recommendations
│ │ │
│ │ └─► Monthly/Quarterly review
│ │ └─► Load: report-templates.md (monthly section)
│ │ Full performance, benchmarks, strategic insights
│ │
│ ├─► METRIC EXPLANATION
│ │ │
│ │ ├─► Standard Meta metrics (CPM, CTR, CPA, ROAS)
│ │ │ └─► Load: metric-definitions.md
│ │ │
│ │ ├─► Attribution questions
│ │ │ └─► Load: attribution-explained.md
│ │ │
│ │ └─► Custom/blended metrics
│ │ └─► Load: custom-metrics.md
│ │
│ ├─► EXECUTIVE/STAKEHOLDER REPORT
│ │ └─► Load: executive-summaries.md
│ │ High-level, business-focused, minimal jargon
│ │
│ └─► CUSTOM ANALYSIS
│ └─► Load relevant reference based on analysis type
│ May combine multiple references
Quick Report Framework
The 3-Part Report Structure
EVERY GOOD REPORT HAS:
1. WHAT HAPPENED (Performance Summary)
- Key metrics vs targets
- Trend direction (↑↓→)
- Notable changes
2. WHY IT HAPPENED (Analysis)
- Causal factors
- Contributing elements
- Context and comparisons
3. WHAT TO DO (Recommendations)
- Clear action items
- Priority order
- Expected impact
Essential Metrics Hierarchy
TIER 1: BUSINESS METRICS (Report first)
├── Revenue (attributed + total)
├── ROAS / MER
├── Profit / Contribution Margin
└── New Customers / CAC
TIER 2: EFFICIENCY METRICS (Context)
├── CPA / CPP
├── CTR
├── CVR
└── CPM
TIER 3: VOLUME METRICS (Scale)
├── Spend
├── Impressions
├── Reach
├── Clicks
└── Conversions
REPORTING ORDER: Always lead with business impact,
then efficiency, then volume.
Report Types Overview
Daily Report (Health Check)
PURPOSE: Catch issues early, verify pacing
TIME: 5-minute review
FREQUENCY: Daily
KEY QUESTIONS ANSWERED:
□ Is spend on pace?
□ Is CPA/ROAS within acceptable range?
□ Any delivery issues?
□ Anything needing immediate attention?
METRICS TO INCLUDE:
- Spend (actual vs budget)
- CPA / ROAS (vs target)
- Delivery status
- Any anomalies (>20% deviation)
Weekly Report (Performance Summary)
PURPOSE: Understand trends, identify winners/losers
TIME: 30-minute review
FREQUENCY: Weekly (same day each week)
KEY QUESTIONS ANSWERED:
□ Are we trending in the right direction?
□ What's working? What's not?
□ Any creative fatigue signals?
□ What should we do next week?
METRICS TO INCLUDE:
- Week-over-week comparison
- Campaign/ad set ranking
- Creative performance
- Funnel metrics (CTR, CVR breakdown)
- Recommendations for next week
Monthly Report (Strategic Review)
PURPOSE: Big picture performance, strategic adjustments
TIME: 1-2 hour deep dive
FREQUENCY: Monthly
KEY QUESTIONS ANSWERED:
□ Did we hit our targets?
□ What were the biggest drivers?
□ How does this month compare to last/LY?
□ What's the plan for next month?
METRICS TO INCLUDE:
- Month vs target vs last month vs LY
- Full funnel analysis
- Channel/campaign breakdown
- Customer acquisition summary
- Budget efficiency analysis
- Strategic recommendations
Attribution Quick Reference
Attribution Windows Explained
WHAT IS AN ATTRIBUTION WINDOW?
The time period after someone sees/clicks your ad
where a conversion is credited to that ad.
DEFAULT SETTINGS (2026):
- 7-day click-through
- 1-day view-through (for conversions, not value)
WHAT THIS MEANS:
If someone clicks your ad on Monday
and purchases on Saturday (6 days later),
that purchase is attributed to your ad.
If someone SEES your ad on Monday
and purchases on Tuesday (1 day later)
WITHOUT clicking, that's view-through.
Common Attribution Models
LAST-CLICK (Most Common):
Credit goes to last ad clicked before conversion
Pro: Simple, clear
Con: Ignores awareness touchpoints
FIRST-CLICK:
Credit goes to first ad that introduced customer
Pro: Values discovery
Con: Ignores conversion touchpoints
LINEAR:
Credit split equally across all touchpoints
Pro: Holistic view
Con: May not reflect true impact
DATA-DRIVEN (Platform default):
Algorithm determines credit distribution
Pro: Most sophisticated
Con: Black box, requires volume
Custom Metrics Quick Formulas
MER (Marketing Efficiency Ratio):
Total Revenue / Total Ad Spend
Use: Holistic efficiency across all channels
Note: Includes non-attributed revenue
BLENDED ROAS:
Total Revenue / Total Meta Spend
Use: Overall Meta efficiency including organic halo
Note: Higher than attributed ROAS
nROAS (New Customer ROAS):
New Customer Revenue / Total Ad Spend
Use: True acquisition efficiency
Note: Requires customer tagging
CAC (Customer Acquisition Cost):
Total Ad Spend / New Customers Acquired
Use: Cost to acquire each new customer
Note: Should be less than LTV
LTV:CAC RATIO:
Customer Lifetime Value / CAC
Target: 3:1 or higher for healthy business
CONTRIBUTION MARGIN:
(Revenue - COGS - Ad Spend) / Revenue
Use: True profitability after ads
Note: Most accurate P&L metric
Reporting Patterns
Pattern: Quick Performance Check
User: "How are my ads doing today?"
RESPONSE STRUCTURE:
1. Today's spend vs daily budget ($X of $Y, XX%)
2. CPA/ROAS vs target (performing at Xx vs Yx target)
3. Any issues? (Learning Limited, delivery problems)
4. Quick assessment (on track / needs attention / issue)
Pattern: Weekly Stakeholder Update
User: "I need to update my team on our Meta performance"
LOAD: executive-summaries.md
RESPONSE STRUCTURE:
1. One-sentence summary (how did we do?)
2. Key numbers (spend, revenue, ROAS)
3. Wins and challenges
4. Next week priorities
Keep under 5 bullet points
Pattern: Attribution Question
User: "Why does my ROAS look different in Meta vs Shopify?"
LOAD: attribution-explained.md
RESPONSE STRUCTURE:
1. Explain attribution window difference
2. Clarify what each platform counts
3. Explain why discrepancy exists
4. Recommend which to trust and why
Pattern: Custom Metric Calculation
User: "What's my true MER?"
LOAD: custom-metrics.md
RESPONSE STRUCTURE:
1. Define MER and why it matters
2. Calculate: Total Revenue / Total Ad Spend
3. Compare to attributed ROAS
4. Interpret the gap
5. Recommend which to use when
Report Output Formats
Metric Card Format
┌─────────────────────────────────┐
│ METRIC NAME │
│ ═══════════════ │
│ Value: $X,XXX (or X.Xx) │
│ vs Target: +/-XX% (↑/↓) │
│ vs Last Period: +/-XX% (↑/↓) │
│ │
│ Status: ● On Track / ○ Warning │
└─────────────────────────────────┘
Trend Table Format
WEEKLY TREND
W1 W2 W3 W4 Trend
Spend $X,XXX $X,XXX $X,XXX $X,XXX →
Revenue $X,XXX $X,XXX $X,XXX $X,XXX ↑
ROAS X.Xx X.Xx X.Xx X.Xx ↓
CPA $XX $XX $XX $XX →
New Customers XXX XXX XXX XXX ↑
Executive Summary Format
META ADS PERFORMANCE SUMMARY
Period: [Date Range]
Prepared for: [Stakeholder]
═══════════════════════════════════
ONE-LINER:
[One sentence: How did we do?]
KEY NUMBERS:
• Spend: $X,XXX (X% of budget)
• Revenue: $X,XXX
• ROAS: X.Xx (vs X.Xx target)
• New Customers: XXX
HIGHLIGHTS:
✓ [Win 1]
✓ [Win 2]
CHALLENGES:
⚠ [Challenge 1]
⚠ [Challenge 2]
NEXT STEPS:
→ [Action 1]
→ [Action 2]
═══════════════════════════════════
Integration with Other Skills
| Skill | Integration Point |
|---|
| performance-optimizer | Reports identify issues for optimization |
| campaign-launcher | Reports inform future campaign setup |
| media-planner | Reports validate media plan assumptions |
| creative-studio | Creative performance feeds creative briefs |
| account-auditor | Reporting reveals audit opportunities |
Reporting Best Practices
1. CONSISTENCY: Same metrics, same format, same cadence
2. CONTEXT: Numbers without context are meaningless
3. COMPARISON: Always show vs target and vs prior period
4. ACTION: Every report should suggest next steps
5. AUDIENCE: Tailor depth to who's reading
6. TIMELINESS: Fresh data > perfect formatting
7. HONESTY: Report bad news clearly, with solutions
8. SIMPLICITY: If you can cut a metric, cut it
Error Handling
| Scenario | Response |
|---|
| Data not available | Explain what's needed, suggest alternatives |
| Attribution confusion | Load attribution-explained.md, clarify |
| Metric not understood | Load metric-definitions.md, explain simply |
| Unrealistic expectations | Set appropriate benchmarks, show context |
| Report too complex for audience | Load executive-summaries.md, simplify |
| Missing historical data | Use available data, note limitations |
