# /distribution-meta-ads — Meta/Instagram Ads Campaign Playbook

## Usage
```
/distribution-meta-ads                # Full campaign design
/distribution-meta-ads {audience}     # Campaign for specific audience segment
```

## Input
- `$ARGUMENTS` — optional: specific audience segment to target

## Process

### Step 1: Load Context
1. Read `data/positioning.json` — value proposition, target audience, pain points
2. Read `data/business-context.json` — product name, funnels, KPIs
3. Read `data/competitors.json` — competitor ad strategies

### Step 2: Audience Research
Use WebSearch to find audience targeting opportunities:
- `"[product category] facebook ads benchmarks CPM CPC CPA [year]"`
- `"[product category] facebook ads targeting"`
- `"[target audience] interests facebook ads"`

Define audience segments:

**Segment 1: Interest-Based (Cold)**
- Interests: [product category tools], [competitor names], [related technologies]
- Demographics: [age range], [job titles if B2B]
- Estimated audience size

**Segment 2: Behavior-Based (Warm)**
- Behaviors: Technology early adopters, SaaS users, [industry-specific]
- Layered with interests for precision

**Segment 3: Retargeting (Hot)**
- Website visitors (last 30 days) who didn't convert
- Pricing page visitors (last 14 days)
- Blog readers (last 60 days)

**Segment 4: Lookalike**
- Based on existing signups/customers
- 1% lookalike for precision, 3-5% for reach

### Step 3: Campaign Structure
Design campaigns following Meta Ads best practices:

```
Campaign: [Product] — Conversions
├── Ad Set: Interest-Based (Cold)
│   ├── Audience: [interests + demographics]
│   ├── Placement: Feed + Stories (auto)
│   └── Budget: $5/day
├── Ad Set: Retargeting (Hot)
│   ├── Audience: Website visitors 30d, excl. signups
│   ├── Placement: Feed + Stories (auto)
│   └── Budget: $3/day
└── Ad Set: Lookalike 1%
    ├── Audience: Lookalike of signups
    ├── Placement: Feed + Stories (auto)
    └── Budget: $5/day
```

### Step 4: Generate Ad Copy
For each audience segment, queue copy generation:
- `/promo-copy ad-meta {audience}` — generates primary text + headline + CTA
- Match messaging to audience temperature (cold=educate, warm=convince, hot=convert)

### Step 5: Creative Format Recommendations
For each ad set, recommend creative format:
- **Cold audiences:** Carousel (3-5 feature cards) or short video (15-30s)
- **Retargeting:** Single image with social proof / testimonial
- **Lookalike:** Video demo or before/after comparison

If video skills are available, queue `/promo-video ad-{topic}` for video creatives.

### Step 6: Budget & Schedule
- **Total daily budget:** $10-15/day starting
- **Split:** 40% cold, 20% retargeting, 40% lookalike
- **Schedule:** Run 7 days, then evaluate
- **Dayparting:** If relevant, focus on business hours for B2B

### Step 7: A/B Test Plan
For each ad set:
- Test 2-3 ad copy variations
- Test 2 creative formats (image vs carousel vs video)
- Measure for 7 days before declaring winner
- Winning criteria: lowest CPA or highest CTR (depending on objective)

### Step 8: Tracking
- UTM parameters: `utm_source=meta&utm_medium=paid&utm_campaign={campaign-slug}&utm_content={ad-set}`
- Pixel events: ViewContent, Lead, CompleteRegistration
- CAPI (Conversions API) setup recommendation if not configured

### Step 9: Output
For each campaign, create an idea in `data/ideas.json` with:
- Category: "growth"
- Tags: ["growth", "meta-ads", "{audience-segment}"]
- Implementation plan with campaign structure
- Success metrics: impressions, reach, CPM, CPC, CTR, conversions, CPA
- Budget recommendation
- Queue `copy-ad-meta-{audience}` tasks

## Output Files
- `data/ideas.json` — new Meta Ads campaign ideas
- `data/campaigns/` — campaign briefs (optional)