paid-ads

name	paid-ads
description	Plan, execute, and optimize paid advertising campaigns across Google Ads, Meta Ads, LinkedIn Ads, Twitter/X, and TikTok. Covers campaign structure, audience targeting, budget allocation, bid strategies, retargeting, attribution, and performance optimization. Use when running PPC campaigns, setting up ad accounts, optimizing ROAS/CPA, or when user mentions paid ads, PPC, Google Ads, Meta Ads, LinkedIn Ads, ad campaigns, retargeting, audience targeting, budget optimization, ROAS, CPA, or ad performance.
license	MIT
metadata	{"version":"1.0.0","author":"borghei","category":"marketing","domain":"advertising","updated":"2026-03-09T00:00:00.000Z"}

Paid Ads

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

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Table of Contents

• Keywords
• Quick Start
• Platform Selection Guide
• Campaign Structure Framework
• Audience Targeting by Platform
• Budget Allocation Strategy
• Bid Strategy Progression
• Retargeting Playbook
• Performance Optimization
• Attribution and Measurement
• Pre-Launch Checklist
• Best Practices
• Integration Points

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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

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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

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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

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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

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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

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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, hold
• Never double a budget overnight (disrupts algorithm learning)
• If CPA increases > 30% after scaling, revert and investigate

Budget Minimums by Platform

Platform	Minimum Viable Monthly Budget	Optimal Monthly Budget
Google Search	$1,500	$5,000+
Google Display	$1,000	$3,000+
Meta Ads	$1,000	$3,000+
LinkedIn Ads	$2,000	$5,000+
TikTok Ads	$1,000	$3,000+
Reddit Ads	$500	$2,000+

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Bid Strategy Progression

Strategy Ladder

Stage	Strategy	When to Use	Requirements
1	Manual CPC	Starting out, need control	None
2	Max Clicks	Building traffic data	Budget cap set
3	Target CPA	Optimizing for conversions	30+ conversions/month
4	Target ROAS	Optimizing for revenue	50+ conversions/month + revenue data
5	Value-based	Maximizing revenue	Conversion value tracking, 100+ conversions/month

Bid Strategy Rules

• Start with Manual CPC or Max Clicks until you have conversion data
• Switch to automated bidding after 30+ conversions in 30 days
• Set CPA targets 10-20% above your actual target (give the algorithm room)
• Never change bid strategy and creative at the same time
• Allow 14 days of learning phase after switching strategies

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Retargeting Playbook

Funnel-Based Retargeting

Funnel Stage	Audience	Message	Window	Frequency
Top	Blog readers, video viewers	Educational, social proof	30-90 days	1-2x/week
Middle	Pricing/feature page visitors	Case studies, demos, comparisons	7-30 days	3-5x/week
Bottom	Cart/trial abandoners	Urgency, objection handling, offer	1-7 days	Daily OK

Retargeting Audience Setup

Audience	Source	Platform	Priority
All website visitors (30 days)	Pixel	All platforms	Medium
Pricing page visitors (14 days)	Pixel	All platforms	High
Cart/trial abandoners (7 days)	Pixel + Events	All platforms	Highest
Email subscribers (non-customers)	Email list	Meta, LinkedIn	Medium
Video viewers (50%+ watched)	Platform event	Meta, YouTube	Medium
Blog readers (engaged, 60s+)	Pixel + Events	All platforms	Low-Medium

Exclusions (Critical)

Always exclude:

• Existing paying customers (unless running upsell campaigns)
• Recent converters (7-14 day exclusion window)
• Bounced visitors (under 10 seconds on site)
• Irrelevant page visitors (careers, support, legal)
• Competitor employees (LinkedIn)

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Performance Optimization

Optimization Decision Tree

Is CPA above target?
├── CTR is low (< 1% search, < 0.5% social)
│   ├── Creative fatigue? → Refresh creative
│   ├── Audience mismatch? → Refine targeting
│   └── Ad relevance low? → Improve message match
├── CTR is good, conversion rate low
│   ├── Landing page issue? → Audit page (speed, copy, CTA)
│   ├── Offer mismatch? → Align ad promise with page offer
│   └── Audience too broad? → Narrow targeting
└── CTR and CVR are good, CPA still high
    ├── CPM too high? → Try different placements/platforms
    ├── Competition driving up bids? → Adjust bid strategy
    └── Attribution issue? → Check conversion tracking

Key Metrics by Objective

Objective	Primary Metrics	Benchmarks (B2B SaaS)
Awareness	CPM, Reach, Video View Rate	CPM: $5-15, VVR: 15-25%
Consideration	CTR, CPC, Time on Site	CTR: 1-3%, CPC: $2-8
Conversion	CPA, ROAS, Conversion Rate	CPA: $50-200, CR: 2-5%
Retargeting	CPA, ROAS, Frequency	CPA: 30-50% lower than prospecting

Creative Fatigue Detection

Signal	Threshold	Action
CTR declining week over week	20%+ decline over 2 weeks	Refresh creative
Frequency above threshold	> 3 (display), > 5 (retargeting)	Expand audience or refresh
CPA increasing with stable CTR	15%+ increase over 2 weeks	Test new creative angles
Engagement rate dropping	30%+ decline	Full creative overhaul

Weekly Optimization Routine

Task	Time	What to Check
Budget pacing	5 min	Spend vs. plan, daily/weekly trends
CPA/ROAS check	10 min	Performance vs. targets, by campaign
Top/bottom performers	10 min	Pause worst, scale best
Audience analysis	10 min	Which segments are converting?
Creative performance	10 min	CTR by creative, fatigue signals
Frequency check	5 min	Any audiences over-exposed?
Landing page CVR	5 min	Post-click conversion rate
Competitor check	5 min	New competitors in auction?

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Attribution and Measurement

Attribution Reality Check

What Platforms Report	Reality
"This campaign drove 100 conversions"	Platform attribution is inflated by 20-50%
"ROAS is 5x"	Likely includes assisted conversions that would have converted anyway
Last-click attribution	Ignores all touchpoints before the final click
View-through conversions	Often just people who would have converted regardless

Practical Attribution Approach

1. Use UTM parameters consistently — Tag every campaign, ad, and link
2. Track in GA4 as source of truth — Compare platform data to GA4
3. Calculate blended CAC — Total marketing spend / Total new customers
4. Use incrementality testing — Hold-out tests to measure true lift
5. Compare platform data vs. CRM data — The gap is your attribution inflation

UTM Standards

utm_source: google | meta | linkedin | twitter | tiktok | reddit
utm_medium: cpc | paid-social | display | video | sponsored
utm_campaign: [campaign-name-lowercase-hyphenated]
utm_content: [ad-variant-identifier]
utm_term: [keyword] (search only)

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Pre-Launch Checklist

Tracking

• Pixel/tag installed and firing correctly
• Conversion events defined and tested with real test conversion
• UTM parameters added to all ad destination URLs
• GA4 goals/events configured to match conversion events
• Attribution window set appropriately (7 or 28 day)

Landing Page

• Page loads under 3 seconds on mobile
• Page is mobile-responsive
• Headline matches the ad message
• CTA is above the fold on mobile
• Form works and submits to CRM/email system
• Thank you page/event fires conversion tracking

Campaign Setup

• Budget set correctly (daily or lifetime)
• Bid strategy selected and configured
• Audience targeting reviewed (not too broad or narrow)
• Negative keywords added (Google Search)
• Exclusions configured (existing customers, competitors)
• Ad schedule set (if time-specific targeting needed)
• Geographic targeting verified
• Device targeting reviewed

Creative

• 3+ creative variants per ad group/set
• All creative meets platform specifications
• Copy validated against platform policies
• Landing page URL correct for each ad

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Best Practices

1. Tracking first, creative second — Never launch without verified conversion tracking. A campaign without attribution is guesswork.

2. Start narrow, expand gradually — Begin with your highest-intent, most-defined audience. Expand after proving the funnel works.

3. One change at a time — Changing audience, creative, and bid strategy simultaneously makes it impossible to know what worked.

4. Give algorithms time — Do not judge campaign performance before the learning phase completes (typically 50 conversions or 7 days).

5. Creative is the biggest lever — On most platforms, creative quality matters more than targeting precision. Test creative aggressively.

6. Match ad to landing page — The #1 conversion killer is mismatched expectations between ad and landing page.

7. Budget concentration beats distribution — $3,000 on one proven platform outperforms $500 spread across six platforms.

8. Build retargeting from day one — Install pixels and build audiences even before you spend on retargeting.

9. Compare platform data to reality — Platform-reported conversions are always higher than actual. Use CRM and GA4 as the source of truth.

10. Document everything — Every campaign change, test result, and learning should be recorded. Institutional knowledge prevents repeating mistakes.

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Integration Points

• Ad Creative — Use for writing ad copy, generating headlines, and creating creative variations. Paid Ads handles the campaign strategy; Ad Creative handles the copy.
• Landing Page Generator — Use for building the landing pages ads drive traffic to.
• Campaign Analytics — Use for measuring campaign performance, attribution analysis, and ROI calculation.
• Marketing Context — Use as foundation for audience targeting and messaging alignment.
• Marketing Psychology — Apply psychological principles to improve ad creative and landing page conversion.
• Copywriting — Use for optimizing landing page copy to improve post-click conversion rates.

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Troubleshooting

Symptom	Likely Cause	Fix
CPA above target with low CTR	Creative fatigue or audience mismatch	Refresh creative. Use ad_copy_scorer.py to validate new copy.
CPA above target with good CTR	Landing page conversion issue	Audit post-click experience: message match, page speed, form friction.
CTR dropping week over week	Creative fatigue (>3 frequency)	Refresh creative every 2-4 weeks. Expand audience to reduce frequency.
Budget not spending	Audience too narrow or bid too low	Check audience size with audience_sizer.py. Increase bid 10-20%.
Platform reports inflated conversions	Attribution window too wide	Compare platform data to GA4/CRM. Use incrementality testing for true lift.
Performance Max underperforming	Insufficient conversion data	Need 30+ conversions in 30 days for PMax to optimize. Start with Search campaigns.
CPA spikes after budget increase	Algorithm learning disrupted	Never increase budget more than 20-30% at a time. Wait 3-5 days between changes.

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Success Criteria

• CPA within target range for campaign objective (B2B SaaS: $50-200 for qualified leads)
• ROAS above 3x for revenue-focused campaigns
• CTR above platform benchmarks: 2-5% search, 0.5-2% social
• Conversion tracking verified with test conversion before launch
• Budget allocation: 70% proven / 20% expansion / 10% testing (at scale)
• All campaigns have proper UTM tagging and GA4 attribution configured
• Weekly optimization routine completed with documented changes

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Scope & Limitations

In Scope: Campaign strategy, platform selection, audience targeting, budget allocation, bid strategies, retargeting, performance optimization, attribution, pre-launch checklists.

Out of Scope: Ad copy writing (use ad-creative), landing page design (use landing-page-generator), creative design/production, marketing automation, CRM configuration.

Limitations: Budget minimums and CPC benchmarks are directional estimates. Actual costs vary by industry, geography, and competition. Platform-reported metrics are typically 20-50% inflated versus CRM truth.

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Python Automation Tools

1. Ad Copy Scorer (scripts/ad_copy_scorer.py)

Scores ad copy against platform specs, compliance rules, and conversion best practices.

python scripts/ad_copy_scorer.py --headline "Cut churn by 30%" --description "See how 1200 SaaS teams reduced churn" --platform google
python scripts/ad_copy_scorer.py --file ads.json --json

2. CPC / CPA / ROAS Calculator (scripts/cpc_calculator.py)

Calculates key advertising metrics from campaign data with industry benchmarks.

python scripts/cpc_calculator.py --spend 5000 --clicks 1200 --conversions 45 --revenue 12000 --platform meta
python scripts/cpc_calculator.py --file campaign.json --json

3. Audience Sizer (scripts/audience_sizer.py)

Estimates target audience size and recommends budget based on platform and targeting criteria.

python scripts/audience_sizer.py --platform linkedin --targeting "CMOs at SaaS companies 50-500 employees"
python scripts/audience_sizer.py --file targeting.json --json