paid-ads

What this skill does

# Paid Ads

Campaign strategy, audience targeting, budget optimization, and performance management across all major advertising platforms.

---

## Table of Contents

- [Keywords](#keywords)
- [Quick Start](#quick-start)
- [Platform Selection Guide](#platform-selection-guide)
- [Campaign Structure Framework](#campaign-structure-framework)
- [Audience Targeting by Platform](#audience-targeting-by-platform)
- [Budget Allocation Strategy](#budget-allocation-strategy)
- [Bid Strategy Progression](#bid-strategy-progression)
- [Retargeting Playbook](#retargeting-playbook)
- [Performance Optimization](#performance-optimization)
- [Attribution and Measurement](#attribution-and-measurement)
- [Pre-Launch Checklist](#pre-launch-checklist)
- [Best Practices](#best-practices)
- [Integration Points](#integration-points)

---

## Keywords

paid ads, PPC, pay-per-click, Google Ads, Meta Ads, Facebook Ads, Instagram Ads, LinkedIn Ads, Twitter Ads, TikTok Ads, paid media, ROAS, CPA, CPC, CPM, audience targeting, retargeting, remarketing, budget optimization, bid strategy, ad campaigns, conversion tracking, lookalike audiences, campaign structure, ad performance, paid search, paid social

---

## Quick Start

### Launch a Campaign

1. Define campaign goal (leads, sales, traffic, awareness)
2. Select platform based on audience and intent
3. Set up conversion tracking and verify with test conversion
4. Build campaign structure with proper naming conventions
5. Define audience targeting
6. Set budget and bid strategy
7. Create ad creative (use Ad Creative skill)
8. Launch and monitor for 7 days before making changes

### Optimize an Existing Campaign

1. Pull performance data for last 14-30 days
2. Identify primary issue (high CPA, low CTR, low ROAS)
3. Use the optimization levers in the Performance Optimization section
4. Make one change at a time, wait 3-5 days between changes
5. Document every change and its impact

---

## Platform Selection Guide

### Platform Comparison

| Platform | Best For | Audience Signal | Typical CPC | Minimum Budget |
|----------|----------|----------------|-------------|----------------|
| **Google Search** | High-intent demand capture | Search keywords (what they want now) | $1-8 (B2B: $5-20) | $1,500/mo |
| **Google Display** | Awareness, retargeting | Browsing behavior, interests | $0.30-1.50 | $1,000/mo |
| **Google Performance Max** | Multi-format automation | Mixed signals, Google's ML | Varies | $2,000/mo |
| **Meta (FB/IG)** | Demand generation, B2C, visual products | Interests, behaviors, lookalikes | $0.50-3.00 | $1,000/mo |
| **LinkedIn** | B2B, decision-maker targeting | Job title, company, industry, seniority | $5-15 | $2,000/mo |
| **Twitter/X** | Tech audiences, thought leadership | Followers, interests, keywords | $0.50-3.00 | $500/mo |
| **TikTok** | 18-34 demographics, brand awareness | Interests, behaviors, creator affinity | $0.30-1.50 | $1,000/mo |
| **Reddit** | Niche communities, tech/gaming | Subreddit targeting | $0.50-2.00 | $500/mo |

### Platform Selection Decision Tree

```
Is the audience actively searching for your solution?
├── Yes → Google Search Ads
└── No → Do you know their job title or company?
    ├── Yes → LinkedIn Ads (B2B) or Meta Ads (B2C)
    └── No → Is your product visual or lifestyle?
        ├── Yes → Meta Ads (Instagram) or TikTok
        └── No → Is your audience technical?
            ├── Yes → Reddit Ads or Twitter/X
            └── No → Meta Ads (Facebook) or Google Display
```

---

## Campaign Structure Framework

### Account Hierarchy

```
Account
├── Campaign 1: [Objective] - [Product/Offer]
│   ├── Ad Group/Set 1: [Audience Segment A]
│   │   ├── Ad 1: [Creative Variant 1]
│   │   ├── Ad 2: [Creative Variant 2]
│   │   └── Ad 3: [Creative Variant 3]
│   └── Ad Group/Set 2: [Audience Segment B]
│       ├── Ad 1: [Creative Variant 1]
│       └── Ad 2: [Creative Variant 2]
└── Campaign 2: [Objective] - [Product/Offer]
```

### Naming Conventions

```
[Platform]_[Objective]_[Audience]_[Offer]_[Date]

Examples:
GOOG_Search_Brand_FreeTrial_2026Q1
META_Conv_Lookalike-Customers_Demo_Mar26
LI_LeadGen_CMOs-SaaS-500_Whitepaper_2026Q1
TIKTOK_Aware_18-34-Tech_BrandVideo_Mar26
```

### Campaign Types by Objective

| Objective | Google | Meta | LinkedIn |
|-----------|--------|------|----------|
| Awareness | Display, YouTube, PMax | Reach, Video Views | Brand Awareness |
| Consideration | Search, Display | Traffic, Engagement | Website Visits |
| Conversion | Search, PMax | Conversions, Leads | Lead Gen Forms |
| Retargeting | Display, Search (RLSA) | Custom Audiences | Matched Audiences |

---

## Audience Targeting by Platform

### Google Ads Targeting

| Targeting Type | Use When | How |
|---------------|----------|-----|
| Keyword targeting | Capturing search intent | Exact, phrase, and broad match keywords |
| Audience targeting | Layering intent signals | In-market, affinity, custom intent |
| RLSA | Retargeting in search | Website visitor lists on search campaigns |
| Customer Match | Targeting known contacts | Upload email lists for matched targeting |
| Similar audiences | Expanding from known customers | Google's lookalike from customer lists |

**Keyword match type strategy:**
- **Exact match** [keyword]: Highest intent, lowest volume, highest CPC
- **Phrase match** "keyword": Medium intent, medium volume
- **Broad match** keyword: Lowest intent, highest volume, lowest CPC (use with smart bidding)

### Meta Ads Targeting

| Targeting Type | Use When | How |
|---------------|----------|-----|
| Interest targeting | Cold prospecting | Layer 2-3 related interests |
| Lookalike audiences | Expanding from customers | 1-3% lookalike from best customers (by LTV) |
| Custom audiences | Retargeting | Website visitors, email lists, video viewers |
| Broad targeting | Trusting Meta's ML | No targeting restrictions, let the algorithm find converters |
| Detailed targeting | Narrow audience needed | Combine demographics + interests + behaviors |

**Lookalike best practices:**
- Seed with best customers (by LTV), not all customers
- Start with 1% lookalike (most similar), expand to 3-5% once proven
- Create separate lookalikes from different seeds (customers, trial users, email subscribers)

### LinkedIn Ads Targeting

| Targeting Type | Use When | How |
|---------------|----------|-----|
| Job title | Targeting decision-makers | Specific titles (CMO, VP Marketing, Head of Growth) |
| Job function | Broader role targeting | Marketing, Engineering, Finance |
| Company size | Enterprise vs. SMB | Employee count ranges |
| Industry | Vertical-specific campaigns | LinkedIn's industry categories |
| Seniority | C-suite vs. individual contributor | Manager, Director, VP, CXO |
| Skills | Technical targeting | Listed skills on profiles |
| Company list | ABM targeting | Upload target account lists |

**LinkedIn targeting rules:**
- Minimum audience size: 50,000 for awareness, 20,000 for conversion
- Layer 2-3 targeting dimensions maximum (more layers = too narrow)
- Exclude competitors, agencies, and job seekers if not relevant

---

## Budget Allocation Strategy

### Budget by Campaign Phase

**Phase 1: Testing (Weeks 1-4)**

| Allocation | Purpose |
|-----------|---------|
| 40% | Proven/safe campaigns (brand search, retargeting) |
| 40% | Testing new audiences and creative |
| 20% | Experimental channels or formats |

**Phase 2: Optimization (Weeks 5-8)**

| Allocation | Purpose |
|-----------|---------|
| 60% | Winning combinations from testing |
| 25% | Iterating on promising but unproven |
| 15% | New tests |

**Phase 3: Scaling (Weeks 9+)**

| Allocation | Purpose |
|-----------|---------|
| 70% | Proven performers |
| 20% | Expansion (new audiences, lookalikes, broader targeting) |
| 10% | Ongoing testing |

### Budget Scaling Rules

- Increase budget by 20-30% at a time, never more
- Wait 3-5 days between increases for algorithm learning
- Monitor CPA for 48 hours after increase — if CPA spikes,