13-data-analysis-global

# Marketing Data Analysis (Global)

> Insight before numbers. Lead with judgment, illustrate with data — never list numbers without interpretation.

---

## Information Gathering

Ask up to 4 questions:

1. **Data source?** Meta Ads, TikTok Ads, GA4, Shopify, Triple Whale/Hyros/Northbeam, Google Sheets — single source or combined?
2. **Time window?** This week, this month, A vs B (e.g. March vs April)?
3. **Current business goal?** Increase leads, lower CPL, raise ROAS, or a specific issue to fix?
4. **Paste data here** — drop a table, or describe core metrics (spend, impressions, clicks, leads, revenue).

---

## Analysis Principles

### Reading Order

```
1. DESCRIPTIVE   — What happened? (numbers, trends)
2. DIAGNOSTIC    — Why? (root cause)
3. PREDICTIVE    — What's next? (forecast)
4. PRESCRIPTIVE  — What to do? (concrete actions)
```

### Presentation Rules

| Rule | Explanation |
|------|-------------|
| Insight first, numbers second | "CPL up 40% due to creative fatigue" — not "CPL went from $5 to $7" |
| Compare, don't quote absolutes | Always compare with: prior week (WoW), prior month (MoM), or industry benchmark |
| Flag anomalies | Any metric moving > 20% vs prior period → flag for investigation |
| Recommendations have deadlines | Each recommendation specifies: action, when, owner, success metric |

---

## Analysis Frameworks by Source

### Meta Ads

| Level | Primary metrics | Secondary metrics |
|-------|-----------------|-------------------|
| Account | Spend, ROAS, CPA | Frequency, Reach |
| Campaign | CPM, CPL, Conv rate | Budget utilization |
| Ad Set | CPC, CTR, CPM | Audience size, overlap |
| Ad (Creative) | Hook rate (3s view), Hold rate, CTR | Engagement rate, save rate |

**Reading Meta Ads:**

```
High spend + low impressions → CPM high → audience too narrow or auction-pressured
High impressions + low clicks → CTR low → creative not compelling
High clicks + low leads → LP problem or form too long
High leads + low bookings → poor lead quality or weak nurture
```

### TikTok Ads

| Level | Primary metrics | Secondary metrics |
|-------|-----------------|-------------------|
| Account | Spend, CPA, ROAS | Total impressions |
| Campaign | CPM, Cost per result | Campaign type performance |
| Ad Group | CPC, CTR, Conv rate | Audience size, age/gender split |
| Ad (Video) | 2s view rate, 6s view rate, completion rate | Like, comment, share |

**Reading TikTok Ads:**

```
2s view rate low → weak hook — first 3 seconds aren't strong enough
6s view rate low → losing attention after the hook
Completion rate low + CTR low → video doesn't drive action
CPV high → wrong audience, or video doesn't fit TikTok format
```

### Google Analytics 4

| Metric group | Metric | Meaning |
|--------------|--------|---------|
| Acquisition | Users, Sessions, Source/Medium | Traffic origin |
| Engagement | Engagement rate, Time on page, Pages/session | Traffic quality |
| Conversion | Conv rate, Events (form submit, click CTA) | Conversion effectiveness |
| Retention | Returning users, User retention | Stickiness |

**Reading GA4:**

```
Traffic up + engagement down → low-quality traffic, filter sources
Traffic up + conversions down → LP problem or wrong-intent traffic
Bounce rate high (>70%) on one page → mismatch with ad copy or slow load
```

### E-commerce Attribution Tools (Dropshipping/DTC)

For dropshipping or DTC stores, native ad-platform metrics often diverge from real revenue. Use one of these:

| Tool | Best for | Key feature |
|------|----------|-------------|
| **Triple Whale** | Shopify DTC | Pixel-based attribution, blended ROAS, AI insights |
| **Hyros** | Info products + DTC | Server-side tracking, long-window attribution |
| **Northbeam** | High-spend DTC ($100K+/mo) | MTA + MMM, incrementality testing |
| **Polar Analytics** | Mid-market DTC | All-in-one dashboards, source-of-truth tracking |
| **Wicked Reports** | Email-heavy DTC | Multi-touch attribution including email |

**Cross-checking:** when Meta reports 5x ROAS but Shopify reports 2x ROAS, trust the platform-of-record (Shopify). The gap is usually iOS 14+ attribution loss.

### Spreadsheet Data (Manual)

When user pastes data from a sheet:

1. Identify core columns: date, channel, spend, units (impressions/clicks/leads/orders), revenue
2. Compute derived metrics: CPL, CPA, ROAS, conversion rate
3. Sort by time to surface trends
4. Group by channel/campaign for comparison

---

## Trend Detection

### Week over Week (WoW)

| Metric | Prior week | This week | Change | Status |
|--------|-----------|-----------|--------|--------|
| [Metric] | [Value] | [Value] | [+/- %] | [Normal / Watch / Alert] |

**Alert thresholds:**
- 10–20% change → monitor, no action yet
- 20–40% change → investigate, prepare a response
- > 40% change → act now

### Month over Month (MoM)

| Metric | Prior month | This month | Change | vs Industry benchmark |
|--------|------------|-----------|--------|----------------------|
| [Metric] | [Value] | [Value] | [+/- %] | [Above/Below industry avg] |

### Seasonality (Global)

| Period | Impact | Adjustment |
|--------|--------|-----------|
| Q4 holiday (US: Black Friday → Christmas) | CPM +30–50%, conversion up | Increase budget; book inventory early; lock LPs |
| Chinese New Year | Asia logistics paused, CPM +20% in APAC | Move launches before/after; warn customers about shipping |
| Back-to-school (US: Aug; UK: Sep) | CPM +10–15% (education/electronics) | Plan from June |
| Valentine's, Mother's Day, Father's Day | CPM +15–25% (gifting niches) | Run campaigns 1 week before |
| Summer (Northern hemisphere: Jun–Aug) | CPM dips 10–15% in many verticals | Test creative, scale new channels |
| Ramadan / Eid (varies by year) | MENA conversion shifts | Adjust tone, timing — engagement spikes after iftar |

---

## Anomaly Detection (Decision Trees)

### CPL Spike

```
CPL up
├── CTR down? → Creative fatigue → Refresh creative
├── CTR normal + Conv rate down? → LP issue
│   ├── Slow load? → Check