# Digital Marketing Performance

> Digital marketing e performance marketing operativo. SEO on-page/technical/off-page, SEM Google Ads (Quality Score, bidding strategies, match types), keyword research (volume, KD, intent), content SEO pillar+cluster, E-E-A-T. Email marketing lifecycle (welcome/cart/winback), deliverability (SPF/DKIM/DMARC), automation lead scoring, drip campaigns. Performance advertising: Meta Ads, TikTok, LinkedIn B2B, programmatic DSP/SSP/RTB, retargeting. AARRR pirate metrics, North Star, growth loops, PLG, ICE/RICE experimentation. Content strategy pillar+cluster, CRO A/B testing rigor, funnel TOFU/MOFU/BOFU, attribution multi-touch. Usa per: "fare SEO", "ottimizzare Google Ads", "email marketing automation", "growth hacking", "A/B test", "ROAS benchmark", "Meta Ads strategy", "landing page CRO", "funnel conversion", "attribution digital".

- Skill: `gigik2a/digital-marketing-performance` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add gigik2a/digital-marketing-performance`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gigik2a/digital-marketing-performance/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: gigik2a (https://skillmd.com/u/gigik2a)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/gigik2a/digital-marketing-performance

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# Digital Marketing e Performance Marketing

Skill operativo per professionisti del digital marketing con esperienza BEMACS. Copertura completa da SEO/SEM fino a growth hacking, automation, e modelli di attribuzione multi-touch. Ogni modulo fornisce formule concrete, benchmark industriali certificati, e decision framework pronti all'uso.

---

## Routing Table: Seleziona per Tema

| Tema | Reference File | Contenuti Chiave |
|------|---|---|
| **SEO on-page & technical** | `references/seo-sem-fundamentals.md` | Title/meta/H1-H6, Core Web Vitals (LCP/FID/CLS), sitemaps, robots.txt, schema.org |
| **SEM Google Ads** | `references/seo-sem-fundamentals.md` | Account structure, match types, Quality Score formula, bidding strategies |
| **Keyword research** | `references/seo-sem-fundamentals.md` | Ahrefs/SEMrush, search volume, KD, CPC, intent classification, audit checklist |
| **Email marketing lifecycle** | `references/email-marketing-automation.md` | Welcome series, abandoned cart, post-purchase, win-back, re-engagement |
| **Deliverability email** | `references/email-marketing-automation.md` | SPF/DKIM/DMARC, sender reputation, spam triggers, inbox placement |
| **Marketing automation** | `references/email-marketing-automation.md` | Lead scoring, drip campaigns trigger-based, segmentation, A/B testing email |
| **Performance advertising** | `references/performance-advertising.md` | Google Ads (Search/Display/Shopping/Performance Max), Meta Ads, TikTok, LinkedIn B2B |
| **Programmatic & RTB** | `references/performance-advertising.md` | DSP/SSP/DMP/CDP, header bidding, brand safety, viewability, fraud detection |
| **Retargeting & attribution** | `references/performance-advertising.md` | Cart abandonment, product viewed, cross-device challenges, ROAS benchmark per industry |
| **AARRR & North Star** | `references/growth-hacking-content.md` | Pirate Metrics, metriche per fase, North Star Metric framework, viral K-factor |
| **Growth loops & experimentation** | `references/growth-hacking-content.md` | Content loops, paid loops, PLG (freemium, free trial), ICE/RICE scoring |
| **Content strategy** | `references/growth-hacking-content.md` | Pillar+cluster, content mix (40/30/30), editorial calendar, SEO-driven planning |
| **CRO & A/B testing** | `references/digital-funnel-conversion.md` | Hypothesis framework, statistical rigor (95% sig, 80% power), heatmaps, form analytics |
| **Landing page optimization** | `references/digital-funnel-conversion.md` | Above-fold, social proof, trust signals, CTA placement, micro vs macro conversions |
| **Funnel TOFU/MOFU/BOFU** | `references/digital-funnel-conversion.md` | Content/channel mix per fase, E-commerce (checkout, product page, upsell) |
| **Attribution modeling** | `references/digital-funnel-conversion.md` | Last-click, first-click, linear, time decay, position-based U-shape, data-driven |

---

## Operative Instructions

### 1. **Quando inizi una nuova strategia digital:**
   - Parti dalla keyword research (volume, KD, intent) → mappa su TOFU/MOFU/BOFU
   - Scegli canali primari (SEO, SEM, Email, Social Ads) in base a intent
   - Defini il North Star Metric e AARRR sub-metriche per fase

### 2. **Per campagne performance (SEM/Meta/LinkedIn):**
   - Valuta Quality Score (CTR + Relevance + LP Experience) → target >6/10
   - Scegli bidding strategy in base a conversioni disponibili (tCPA/tROAS se dati sufficienti)
   - A/B testa match types, copy, landing page con rigore statistico (95% sig, 80% power)

### 3. **Per email marketing:**
   - Segmenta per comportamento (acquisti, engagement, tempo da ultimo contatto)
   - Implementa lifecycle (welcome → post-purchase → win-back se >90d inattivo)
   - Monitora deliverability (SPF/DKIM/DMARC), Open Rate (target 20-30%), CTR (2-5%)

### 4. **Per growth hacking:**
   - Identifica growth loop primario (viral K-factor, content loop, paid loop)
   - Priorizza con ICE score (Impact × Confidence × Ease)
   - Misura retention (D1, D7, D30) e payback period

### 5. **Per CRO:**
   - Mappa micro-conversioni (click, add-to-cart) + macro-conversioni (purchase)
   - Formula ipotesi A/B test basate su heatmap/session recording
   - Garantisci significance 95% e power 80% prima di rollout

### 6. **Per attribuzione:**
   - Inizia con last-click (default), esplora first-click e linear
   - Usa position-based U-shape (40/20/40) per comparare con data-driven se disponibile
   - Riconcilia con CLV per validare model

---

## Quick Reference: Key Formulas & Benchmarks

### **Performance Metrics**
| Formula | Descrizione | Benchmark |
|---------|---|---|
| CTR | Clicks / Impressions | 2-5% (SEM), 0.5-2% (Display), 3-8% (Email) |
| CPC | Spesa / Clicks | Varia per industria, ~€1-5 Search, ~€0.50-2 Display |
| CPA | Spesa / Conversioni | Target dipende da LTV |
| CPM | Spesa / (Impressions / 1000) | €5-20 Display, €10-50 Premium |
| ROAS | Revenue / Ad Spend | E-commerce 3-5x, SaaS 4-6x, Retail 4x |
| CAC Payback | CAC / (ARPU × Gross Margin) | <12 mesi ideale |

### **Google Ads Quality Score**
```
Quality Score (1-10) = f(CTR, Ad Relevance, LP Experience)
Obiettivo: >6/10
CTR atteso per parola chiave / CTR effettivo = CTR component
Ad Relevance: Poor/Fair/Good/Excellent
LP Experience: Poor/Fair/Good/Excellent
```

### **Growth & Viral Metrics**
| Metrica | Formula | Interpretazione |
|---------|---------|---|
| K-factor (viral) | (invites per user) × (conversion rate) | >1 = crescita esponenziale |
| D1 Retention | Active users day 1 / Cohort size | Target >30% consumer app |
| D7 Retention | Active users day 7 / Cohort size | Target >15-20% |
| Payback Period | CAC / (ARPU × Gross Margin %) | <6 mesi SaaS B2B |

### **Email Marketing**
| KPI | Benchmark B2C | Benchmark B2B |
|-----|---|---|
| Open Rate | 20-30% | 15-25% |
| CTR | 2-5% | 1.5-3% |
| Conversion Rate | 1-3% | 0.5-2% |
| Unsubscribe | <0.5% | <0.3% |
| Spam Complaint | <0.1% | <0.1% |

### **E-E-A-T Framework (Google Search Quality)**
- **E**xperience: Dimostra esperienza diretta
- **E**xpertise: Qualifiche / credenziali autore
- **A**uthoritativeness: Riconoscimento industria, backlink autorevoli, citazioni
- **T**rust: Trasparenza, GDPR compliance, SSL certificate, author bio, contact info

### **ICE Score per Priorizzazione Esperimenti**
```
ICE = Impact (1-10) × Confidence (0-1) × Ease (1-10)
Esempio: [Impact:8 × Confidence:0.7 × Ease:6] = 33.6
Priorità: ICE >30 = alta, 15-30 = media, <15 = bassa
```

### **A/B Testing Rigor**
- **Significance level (α):** 95% (p-value <0.05)
- **Statistical power (1-β):** 80% (β=0.20)
- **Minimum Detectable Effect (MDE):** Defini prima del test
- **Sample size formula:** n = 2[(Z_α/2 + Z_β)σ / MDE]²

### **Funnel Rates**
| Fase | Metrica | Target Ragionevole |
|------|---------|---|
| TOFU (Awareness) | Impressions → Click | CTR 0.5-2% (Display) |
| MOFU (Consideration) | Landing → Form submission | 5-15% |
| BOFU (Decision) | Cart add → Purchase | 2-4% (e-commerce) |
| Complessivo | Impression → Purchase | 0.1-0.5% (e-commerce) |

---

## Cross-Skill References

- Combina con **`marketing-analytics`** per modelli quantitativi (CLV, attribution avanzata, cohort analysis)
- Combina con **`marketing-strategico`** per STP (Segmentation/Targeting/Positioning), brand strategy, competitive positioning
- Combina con **`marketing-settori-creativi`** per contenuti (copy, visual, storytelling) in industrie creative

---

## Come Usare Questo Skill

**Scenario 1: Lancio campagna SEM**
→ Consulta `seo-sem-fundamentals.md` → Crea account structure → Impostare Quality Score target (>6) → Configura bidding strategy (tCPA se conversion data sufficienti) → A/B testa copy e landing page

**Scenario 2: Ottimizzare email marketing**
→ Consulta `email-marketing-automation.md` → Definisci lifecycle stage (welcome, post-purchase, win-back) → Implementa segmentazione comportamentale → Monitora KPI (Open, CTR, spam complaint) → A/B testa subject line e CTA

**Scenario 3: Accelerare growth con experimentation**
→ Consulta `growth-hacking-content.md` → Identifica North Star Metric → Mappa AARRR per la tua fase → Formula ipotesi con ICE score → Esegui con rigore statistico 95% sig / 80% power

**Scenario 4: Migliorare conversion rate landing page**
→ Consulta `digital-funnel-conversion.md` → Esegui heatmap/session recording → Formula ipotesi per CRO A/B test → Calcola sample size per MDE → Monitora micro + macro conversions

**Scenario 5: Modellare attribuzione digital**
→ Consulta `digital-funnel-conversion.md` → Scegli modello iniziale (last-click, linear, position-based U) → Valida con CLV → Itera verso data-driven se dati sufficienti