Lookalike Audience Plan
lookalike-audience-plan
Designs lookalike audience strategies with source audience selection, percentage tiers, and testing framework. Use when planning paid ad targeting to find new customers similar to your best existing ones.
- This skill, packaged and ready to upload. lookalike-audience-plan.zip
- In claude.ai or Claude desktop: Customize → Skills (+) → Create skill → Upload a skill, select the zip and toggle it on. Greyed out? Enable code execution under Settings → Capabilities.
- It’s live in your chats — no code, no setup. Want every Marketing skill at once? Add the whole plugin from the Marketing page (Customize → Personal plugins → Create plugin → Upload plugin).
/plugin marketplace add Salah-XD/equipt
/plugin install equipt-marketing Installs the whole equipt-marketing plugin — this skill included.
npx @equipt/cli init
npx @equipt/cli add lookalike-audience-plan Adds just this skill to your Claude Code project.
When to Use This Skill
Use this skill when you need to:
- Build a lookalike audience strategy for Facebook, Google, or other ad platforms
- Select the best source audiences from your existing customer data
- Plan percentage tiers and testing sequences for lookalike expansion
- Create a structured rollout plan for scaling ad spend with lookalikes
DO NOT use this skill for interest-based targeting, retargeting setup, or organic audience building. This is specifically for lookalike/similar audience strategies on paid platforms.
Core Principle
THE QUALITY OF A LOOKALIKE AUDIENCE IS ONLY AS GOOD AS THE SOURCE AUDIENCE — START WITH YOUR HIGHEST-VALUE CUSTOMERS, NOT YOUR LARGEST LIST.
Phase 1: Source Audit
Before building lookalikes, identify and evaluate available source audiences.
Required Inputs
| Input | What to Ask | Default |
|---|---|---|
| Ad platform | "Which platform? (Meta, Google, TikTok, LinkedIn)" | Meta (Facebook/Instagram) |
| Available customer data | "What customer lists or pixel data do you have? (email lists, purchasers, leads, website visitors)" | No default — must be provided |
| Average order value / LTV | "What is your average customer value or lifetime value?" | Unknown |
| Monthly ad budget | "What is your monthly ad spend budget?" | $2,000/month |
| Geographic targets | "Which countries or regions are you targeting?" | United States |
GATE: Do not proceed until the user confirms their available data sources and platform.
Phase 2: Source Audience Strategy
Rank and recommend source audiences based on quality signals.
Source Audience Hierarchy (Best to Weakest)
- Top 25% customers by LTV — highest value, clearest signal
- All purchasers — proven buyers, strong signal
- Repeat purchasers — loyalty signal, smaller but potent
- High-intent leads — booked calls, started checkout, requested demos
- Email subscribers (engaged) — opened/clicked in last 90 days
- All email subscribers — weaker signal, larger pool
- Website visitors (key pages) — pricing page, product pages
- All website visitors — weakest signal, largest pool
Minimum Source Size Requirements
| Platform | Minimum Source | Recommended Source |
|---|---|---|
| Meta | 100 people | 1,000-5,000 |
| 100 people | 1,000+ | |
| TikTok | 100 people | 1,000+ |
| 300 people | 1,000+ |
Present recommended source audiences with rationale before proceeding.
GATE: Confirm source audience selections with the user.
Phase 3: Lookalike Build Plan
Design the tiered lookalike strategy with testing framework.
Percentage Tier Strategy
## Lookalike Tiers
### Tier 1: Precision (1-2%)
- Closest match to source audience
- Highest expected conversion rate
- Smallest reach, highest CPM
- Use for: Initial testing, limited budgets
### Tier 2: Balanced (3-5%)
- Good match with broader reach
- Strong conversion potential with scale
- Use for: Scaling after Tier 1 validation
### Tier 3: Expansion (6-10%)
- Broadest reach, weakest signal
- Lower conversion rate but lowest CPM
- Use for: Top-of-funnel awareness, large budgets
Testing Sequence
- Start with best source audience at 1% lookalike
- Test 1% vs 3% vs 5% of the same source
- Test winning percentage across different source audiences
- Layer interest targeting on top of broader lookalikes (5%+)
- Exclude existing customers and active retargeting audiences
Budget Allocation
| Phase | Budget Split | Duration |
|---|---|---|
| Testing | 70% Tier 1, 20% Tier 2, 10% Tier 3 | 2 weeks |
| Scaling | 40% Tier 1, 40% Tier 2, 20% Tier 3 | Ongoing |
Phase 4: Deliverable
Output the complete lookalike audience plan document.
Plan Format
## Lookalike Audience Plan
**Platform:** [Platform]
**Source Audiences:** [List]
**Geographic Target:** [Regions]
**Monthly Budget:** [Amount]
### Source Audience Details
[For each source: name, size, quality score, upload instructions]
### Lookalike Build Matrix
| Source Audience | 1% | 3% | 5% | 10% |
|----------------|----|----|----|----|
| [Source 1] | Build | Build | Test later | Skip |
### Testing Calendar
Week 1-2: [Specific tests]
Week 3-4: [Optimization actions]
Month 2+: [Scaling plan]
### Exclusion Lists
[Audiences to exclude from each campaign]
### Success Metrics
[KPIs and benchmarks for each tier]
Example: E-commerce Store Selling Skincare
Source audiences available: 3,200 purchasers, 800 repeat purchasers, 12,000 email subscribers, 45,000 monthly website visitors.
Recommendation: Lead with repeat purchasers (800) as primary source at 1% — strongest signal despite smaller size. Test all purchasers (3,200) at 1% simultaneously. Skip email subscribers until purchaser lookalikes are validated.
Anti-Patterns
- Using "all website visitors" as the primary source — too broad, weak signal. Start with purchasers or high-intent actions.
- Testing all tiers simultaneously — burns budget without learning. Test sequentially.
- Ignoring source audience freshness — a 3-year-old email list produces worse lookalikes than a 90-day purchaser list.
- Skipping exclusions — always exclude existing customers and active retargeting pools.
- Assuming one source fits all — different products may need different source audiences.
Recovery
- Source audience too small: If under platform minimums, combine related audiences (e.g., merge purchasers with high-intent leads). Note the quality tradeoff.
- No purchaser data: Use highest-intent available signal — email engaged subscribers or key page visitors. Recommend building a purchaser list for future use.
- Multiple products/services: Create separate source audiences per product line. Do not mix unrelated customer types.
- No existing customer data at all: This skill requires some data. Recommend running interest-based campaigns first to build a pixel audience of 500+ converters, then return to build lookalikes.