# Performance Evaluation — US Variant

> Region: United States, Canada
> Currency: USD
> Locale notes: Mature ad market, high CPM, strong conversion intent, many sub-niches saturated.

---

## US-specific benchmarks (2025–2026)

### Paid ads benchmarks

| Metric | Poor | Average | Good | Excellent | Your data |
|--------|------|---------|------|-----------|-----------|
| **Meta — CPM** | >$20 | $7–$15 | $5–$7 | <$5 | [#] |
| **Meta — CPC** | >$2 | $1–$2 | $0.50–$1 | <$0.50 | [#] |
| **Meta — CPL** | >$30 | $15–$30 | $7–$15 | <$7 | [#] |
| **Meta — CTR** | <0.8% | 0.8–1.5% | 1.5–3% | >3% | [#]% |
| **Meta — CPA (e-com)** | >$50 | $25–$50 | $15–$25 | <$15 | [#] |
| **Google Search — CPC** | >$8 | $1–$5 | $0.50–$1 | <$0.50 | [#] |
| **Google Search — CTR** | <2% | 2–5% | 5–10% | >10% | [#]% |
| **Google Display — CPM** | >$5 | $2–$5 | $1–$2 | <$1 | [#] |
| **TikTok Ads — CPM** | >$15 | $5–$12 | $3–$5 | <$3 | [#] |
| **TikTok Ads — CPC** | >$2 | $1–$2 | $0.50–$1 | <$0.50 | [#] |
| **TikTok Ads — CTR** | <0.5% | 0.5–1.2% | 1.2–2.5% | >2.5% | [#]% |
| **LinkedIn — CPM** | >$50 | $25–$50 | $15–$25 | <$15 | [#] |
| **LinkedIn — CPC (B2B)** | >$15 | $7–$15 | $4–$7 | <$4 | [#] |
| **LinkedIn — CPL (B2B SaaS)** | >$200 | $100–$200 | $50–$100 | <$50 | [#] |

### Funnel conversion

| Step | Average | Good | Your data |
|------|---------|------|-----------|
| Impression → Click | 1–2% | 3%+ | [#]% |
| Click → Lead | 8–15% | 20%+ | [#]% |
| Lead → Sales-qualified | 25–40% | 50%+ | [#]% |
| SQL → Customer (B2C) | 15–25% | 30%+ | [#]% |
| SQL → Customer (B2B) | 10–20% | 25%+ | [#]% |
| Customer → Repeat (90d) | 20–35% | 45%+ | [#]% |

### Email + organic

| Metric | Poor | Average | Good | Excellent | Your data |
|--------|------|---------|------|-----------|-----------|
| Email open rate | <12% | 18–25% | 25–35% | >35% | [#]% |
| Email click-through | <1.5% | 2–4% | 4–6% | >6% | [#]% |
| Email conversion (e-com) | <0.5% | 1–3% | 3–5% | >5% | [#]% |
| TikTok engagement rate | <2% | 3–6% | 6–10% | >10% | [#]% |
| Instagram engagement | <0.5% | 1–2% | 2–4% | >4% | [#]% |
| LinkedIn engagement (B2B) | <1% | 2–4% | 4–8% | >8% | [#]% |

### Industry-specific CAC / LTV

| Industry | Typical CAC | Typical LTV | Healthy LTV:CAC |
|----------|------------|-------------|-----------------|
| DTC e-commerce (apparel) | $25–$60 | $100–$400 | 3:1+ |
| DTC e-commerce (beauty) | $35–$80 | $150–$600 | 4:1+ |
| SaaS (SMB) | $200–$800 | $2K–$15K | 5:1+ |
| SaaS (Enterprise) | $5K–$50K | $50K–$500K | 4:1+ |
| Education/coaching | $80–$300 | $500–$5K | 4:1+ |
| Lead-gen services (legal, finance) | $100–$500 | $2K–$20K | 5:1+ |
| Subscription box | $30–$80 | $200–$800 | 3:1+ |

---

## Common pitfalls — US market

| Pitfall | Why it hurts | Fix |
|---------|--------------|-----|
| **Auction peaks Q4** | CPM rises 40-80% Oct-Dec | Front-load Sep, scale back ROAS targets in Q4 |
| **iOS 14.5+ tracking loss** | 30-40% data loss from iOS users | Setup CAPI + server-side tracking |
| **Privacy-first cookie depreciation** | Less retargeting power | First-party data + email list + SMS |
| **Saturated DTC niches** | Skincare, supplements, athleisure CPMs sky-high | Differentiate with creative angle, not just product |
| **High AOV expectation** | $30 AOV = hard to scale on Meta | Target $50+ AOV minimum |
| **Refund/chargeback** | Stripe blocks accounts at 1%+ CB | Strict QC, clear shipping ETAs |
| **Black Friday creative fatigue** | Promo blends in with everyone | Distinct hook, not just "X% off" |
| **Influencer over-reliance** | One bad batch = revenue cliff | Diversify: 5-10 micro vs. 1 macro |
| **Email deliverability** | Gmail spam filtering aggressive | Authenticate (DKIM/SPF/DMARC), warm IP |

---

## Regional case study — US DTC apparel

**Brand:** Mid-tier women's athleisure DTC. AOV $85. Margin 38%.

**Symptoms:**
- ROAS dropped from 2.8x to 1.6x over 6 weeks
- Meta CPM up from $11 to $19
- CTR down from 1.4% to 0.7%

**5-Whys:**
| Round | Why? | Answer |
|-------|------|--------|
| 1 | ROAS drop? | CPM doubled, conv rate flat |
| 2 | CPM up? | Frequency hit 5.2 across all ad sets |
| 3 | High frequency? | Same 3 LAL audiences, 6 weeks no rotation |
| 4 | No rotation? | Team running same evergreen creatives |
| 5 | Same creatives? | No SOP for creative refresh, only 1 designer |

**Action plan (48h):**
1. Pause ad sets with frequency > 4 (saved $2K/day immediately)
2. Brief 5 new UGC angles with pre-approved creators
3. Add 2 new LAL audiences (3% based on top 25% LTV customers)
4. Setup CAPI (was missing — 35% iOS data loss)

**Result (4 weeks later):**
- ROAS recovered to 2.5x
- CPM stabilized at $13
- Process: 3 new creatives/week minimum

---

## Dropshipping context — US

US dropshipping faces unique dynamics:

| Factor | Impact | Tactics |
|--------|--------|---------|
| Fast shipping expectation | Amazon-trained 2-day | US warehouse OR clear ETA + premium feel |
| AOV pressure | Margin gets eaten by ad costs | $40+ AOV minimum, bundles |
| Tariffs / customs | China direct ships face delays | US-based 3PL, ShipBob, Easyship |
| Stripe / PayPal scrutiny | Chargeback rate matters | Clear refund policy, fast support |
| Competition with Amazon/Temu | Race to bottom on price | Brand story + niche + community |

**US dropshipping ROAS targets:**

| Margin | BE-ROAS | Healthy ROAS | Scale ROAS |
|--------|---------|--------------|------------|
| 25% | 4.0x | 4.8x | 6.0x+ |
| 30% | 3.33x | 4.0x | 5.0x+ |
| 40% | 2.5x | 3.0x | 4.0x+ |
| 50% | 2.0x | 2.4x | 3.2x+ |

---

## US-specific compliance flags

| Area | Rule | Impact on ads |
|------|------|---------------|
| FTC endorsement guidelines | Disclose paid partnerships #ad/#sponsored | Required on all influencer/UGC ads |
| Meta restricted categories | Health, finance, dating, employment | Limited targeting, no LAL of customer list |
| Google ads policy (health) | No "before/after" weight loss claims | Use lifestyle, not transformation |
| HIPAA (health/medical) | No retargeting on health symptoms | Use broad interest targeting |
| State privacy laws (CA, VA, CO) | CCPA/CPRA opt-out required | Add Do Not Sell My Info link |
| TCPA (SMS) | Express written consent required | Double opt-in for SMS |
| CAN-SPAM (email) | Unsubscribe required, sender ID accurate | All compliant ESPs handle this |

---

## US-specific channel mix recommendations

For most US brands:

| Channel | Recommended split | Why |
|---------|------------------|-----|
| Meta (FB+IG) | 35-50% | Still highest volume + best targeting |
| Google (Search + Shopping + YouTube) | 20-35% | High intent, SEO compounds |
| TikTok | 10-25% | Viral reach, especially Gen Z |
| Email + SMS | 5-15% | Highest ROI but post-acquisition |
| LinkedIn (B2B only) | 30-50% (if B2B) | B2B-dominant in US |
| Pinterest | 5-15% (DTC home/fashion/beauty) | Long buyer journey, evergreen |
| Reddit/X | 0-10% (community/niche brands) | Niche communities, harder to scale |

---

## Quality checklist — US variant

Before delivering US performance evaluation:

- [ ] Numbers in USD, no FX confusion
- [ ] iOS attribution gap acknowledged (CAPI status checked)
- [ ] Q4 seasonality factored if dates overlap Oct-Dec
- [ ] CCPA/CPRA compliance verified for retargeting
- [ ] LTV:CAC ratio computed (target 3:1 minimum)
- [ ] If dropshipping: BE-ROAS calculated, US shipping plan confirmed
- [ ] Channel mix matches industry (B2C vs B2B vs DTC)
- [ ] Influencer/UGC FTC disclosure verified
- [ ] Email auth (DKIM/SPF/DMARC) confirmed
- [ ] Stripe/PayPal CB rate <1% verified

---

## Cross-reference

- Full SKILL.md router: `../SKILL.md`
- Other regions: `02-eu.md`, `03-sea.md`, `04-latam.md`
- Reverse KPI calculation: `../../10-reverse-kpi-global/variants/01-us.md`
- Channel setup: `../../11-channel-setup-global/variants/01-us.md`
