Use when planning cold outreach campaigns, optimizing email deliverability, building prospect targeting strategies, managing sending infrastructure, designing follow-up sequences, or analyzing outreach performance. Use when the user mentions cold email, outreach, prospecting, lead generation campaigns, email warm-up, deliverability, or reply rates. NEVER for warm introductions or referral-based outreach. NEVER for email marketing to opted-in lists. NEVER for content marketing or social selling. NEVER for transactional email systems.
Claude's default cold outreach advice is generic -- "personalize your emails" and "follow up persistently" -- which produces 1-3% reply rates and deliverability problems. This skill teaches deliverability-first infrastructure decisions, diagnostic positioning over solution-selling, and micro-campaign targeting that achieves 2-5x industry reply rates. The difference is architectural, not cosmetic.
Route every outreach project through these four decisions before writing a single email.
| Offer Type | Outreach Style | Email Length | CTA Design |
|---|---|---|---|
| Free diagnostic / consultation | Problem-awareness → curiosity gap → low-friction ask | 60-100 words | Calendar link or reply-to-book |
| Demo / trial | Specific outcome claim → social proof → time-bounded ask | 80-120 words | Direct demo link with fallback reply |
| Direct product / service | Pain-agitate → solution hint → qualification question |
| 80-130 words |
| Reply with qualifying answer |
| Content / event invite | Value preview → exclusivity signal → single CTA | 50-80 words | Registration link, no reply needed |
Key rule: Diagnostic offers outsell direct pitches 3:1 in cold outreach because they lower commitment and reframe the seller as advisor. Default to diagnostic unless the user has a specific reason not to.
| Segment | Decision Maker | Avg Response Window | Personalization Minimum |
|---|---|---|---|
| SMB (<50 employees) | Owner / GM | 24-72 hours | Industry-specific (Level 2) |
| Mid-market (50-500) | VP / Director | 48-96 hours | Role-specific (Level 3) |
| Enterprise (500+) | Individual contributor champion | 1-2 weeks | Account-specific (Level 4) |
Scaling rule: As company size increases, personalization depth must increase and volume must decrease. A 500-email SMB campaign can work at Level 2 personalization. A 500-email enterprise campaign at Level 2 will get 0 replies.
| Volume | Emails/Campaign | Infrastructure Needed | Personalization Depth |
|---|---|---|---|
| Micro | <50 | Single domain, single account | Level 3-4 (role/account) |
| Scaled | 100-500 | 2-3 sending accounts, dedicated domain | Level 2-3 (industry/role) |
| High-volume | 500+ | Domain rotation, IP warming, multiple accounts | Level 2 minimum + dynamic variables |
Critical: High-volume only works with established infrastructure (30+ days warmed). Never launch high-volume from new domains -- deliverability will collapse within 48 hours.
| State | Daily Limit | What to Do First |
|---|---|---|
| Brand new domains | 0 (not ready) | Set up authentication, begin warm-up ramp. See references/infrastructure-setup.md |
| Warming (days 1-14) | 10-25/account | Small micro-campaigns only, monitor every metric daily |
| Warming (days 15-30) | 25-40/account | Begin scaled campaigns, watch bounce rate closely |
| Established (30+ days, clean history) | 40-60/account | Full campaign operations, monitor weekly |
| Damaged reputation | 0 (pause all sends) | Diagnose cause, pause 7-14 days, restart warm-up |
These are the decisions where mistakes cost weeks or months to recover from. Infrastructure before copy, always.
Why micro-campaigns beat blast campaigns: a 50-contact campaign with Level 3 personalization produces 2.76x the reply rate of a 500-contact campaign with Level 1 personalization. The math always favors precision.
| Level | What's Personalized | Time per Email | Expected Reply Lift |
|---|---|---|---|
| Level 1: Spray | Name + company only | 0 (automated) | Baseline (2-3%) |
| Level 2: Industry | Industry-specific pain points, seasonal context | 30 sec | 1.5-2x baseline |
| Level 3: Role | Role-specific language, title-aware framing, company-size context | 1-2 min | 2.5-3.5x baseline |
| Level 4: Account | Company-specific research, recent news/events, mutual connections | 5-10 min | 4-6x baseline |
Decision rule: Spend personalization time where deal size justifies it. $500 ACV = Level 2 max. $5K ACV = Level 3. $50K+ ACV = Level 4.
These are structural rules, not templates. Templates are in references/campaign-templates.md.
The 4 rules that separate 3% reply-rate emails from 15% reply-rate emails:
Follow-up architecture: See references/campaign-templates.md for full sequence frameworks. The key principle: each follow-up must introduce a genuinely new angle (proof, data, different pain point). Never reference the previous email ("Just following up on my last email...").
| Anti-Pattern | Why It Fails | What To Do Instead |
|---|---|---|
| Sending 200+ emails from a 1-week-old domain | Triggers spam filters immediately, domain may be permanently flagged | Follow 30-day warm-up ramp, start at 10-20/day |
| "Just checking in" follow-ups | Adds zero value, trained as spam signal by filters and humans | Each follow-up introduces new proof, angle, or value |
| HTML-heavy emails with images and buttons | Cold email filters penalize formatting complexity; looks like marketing blast | Plain text, one link max, conversational tone |
| Mixing industries in one campaign | Prevents meaningful A/B testing; generic copy underperforms niche copy | One industry-role combination per micro-campaign |
| Buying pre-built email lists | 20-40% invalid rate typical; destroys bounce rate and domain reputation | Build lists from verified sources, validate every address before send |
| Solution-selling in the first email | Prospect hasn't confirmed the problem exists; feels presumptuous | Lead with problem awareness, offer diagnosis |
| Sending same email copy for 30+ days | Mailbox providers detect repeated content patterns and flag as spam | Rotate copy every 2 weeks, maintain 3-4 active variants |
| Skipping email verification | Even "good" lists have 5-15% invalid addresses that cause bounces | 3-tier verification: MX check, API verification, catch-all detection |
| Including unsubscribe link in cold email | Signals bulk sending to spam filters; cold email is not marketing email | Use breakup email as natural exit; honor opt-out replies immediately |
| Personalizing with obviously scraped data | "I saw your LinkedIn post from 2019..." feels surveillance, not relevance | Use timely signals: recent hires, funding, seasonal patterns |
| Rationalization | When It Appears | Why It's Wrong |
|---|---|---|
| "We need more volume to see results" | Low reply rates after 2-3 weeks | Volume amplifies bad targeting. Fix targeting/copy first, then scale. |
| "Our emails are too short, we need to explain more" | Prospects not engaging | Length is not the problem. Relevance and positioning are. Longer cold emails perform worse. |
| "Let's add more links so they have options" | Low click-through rate | Multiple CTAs create decision paralysis. One clear ask outperforms every time. |
| "We should warm up faster, we're losing time" | Impatience during ramp period | Rushing warm-up risks the domain permanently. A 2-week shortcut can cost 2-month recovery. |
| "The list is fine, our copy must be bad" | High bounce rate (>4%) | List quality causes bounces, not copy. Verify the data before rewriting anything. |
| "Let's send from our main domain to look legitimate" | Low open rates from outreach domain | Burning your main domain destroys ALL business email. The outreach domain exists to absorb risk. |
| "We should follow up more aggressively" | No replies after sequence completes | Aggressive follow-up triggers spam complaints. Test new angles, not more frequency. |
| "Personalization takes too long at scale" | Scaling pressure | Then reduce volume to match personalization capacity. Unpersonalized scale produces negative ROI. |
When campaign metrics are below benchmarks (see references/outreach-benchmarks.md), diagnose in this exact order. Each layer must be healthy before the next matters.
Layer 1: DELIVERABILITY (are emails reaching inboxes?)
Check: inbox placement rate, bounce rate, spam folder rate
Fix: authentication, warm-up status, sending volume, list quality
|
Layer 2: TARGETING (are the right people receiving emails?)
Check: ICP match rate, title accuracy, company fit
Fix: list source, enrichment quality, qualification criteria
|
Layer 3: COPY (is the message compelling?)
Check: open rate (subject line), reply rate (body + CTA)
Fix: subject line testing, body length, CTA clarity, reading level
|
Layer 4: TIMING (is the send time optimal?)
Check: open rate by day/time, industry work patterns
Fix: send window adjustment, timezone targeting, seasonal factors
Critical rule: If Layer 1 is broken, do NOT touch Layers 2-4. Rewriting copy when emails land in spam is wasted effort. Fix infrastructure first, measure again, then move up the stack.