email-marketing

# Email Marketing Automation Design, build, and optimize email marketing flows for SaaS GTM. This skill covers drip sequence architecture, deliverability engineering, template design patterns, and provider API integration. ## Email Marketing Architecture ``` Email System ├── Transactional Emails (account confirmations, password resets, receipts) │ └── Triggered by user actions, must send immediately ├── Marketing Emails (newsletters, announcements, product updates) │ └── Sent to segments on a schedule ├── Drip Sequences (automated multi-email flows) │ └── Triggered by events, sent on a delay schedule └── Lifecycle Emails (onboarding, activation, retention, win-back) └── Triggered by user state changes or inactivity ``` ## Core Sequences Every SaaS Needs ### 1. Welcome Sequence (Trigger: user signs up) ``` Day 0 (immediate): Welcome + quick-start guide Day 1: Key feature highlight + "try this" CTA Day 3: Social proof (testimonials, case studies) Day 5: "Need help?" with support links + community invite Day 7: Activation check — if not activated, branch to re-engagement ``` ### 2. Activation Sequence (Trigger: signup but no key action) ``` Day 2: "You're 1 step away" — focus on the activation action Day 4: Video walkthrough of the core feature Day 7: Success story of someone who activated Day 10: Direct offer — "Reply to this email and I'll help you set up" Day 14: Final nudge — "Is [Product] right for you?" ``` ### 3. Trial-to-Paid Sequence (Trigger: trial started) ``` Day 0: Trial confirmation + what to expect Day 3: Feature highlight #1 (most valuable) Day 5: Feature highlight #2 + comparison to alternatives Day 7 (mid-trial): Progress check + premium feature preview Day 10: Customer success story + ROI data Day 12 (2 days before): Urgency — "Your trial ends in 2 days" Day 13 (1 day before): Last chance — clear pricing, FAQ Day 14 (expiry): "Your trial has ended" — extend offer or discount Day 16 (grace): "We saved your data" — final conversion attempt ``` ### 4. Retention/Engagement Sequence (Trigger: no login for 7+ days) ``` Day 7 inactive: "We miss you" + new feature announcement Day 14 inactive: "Here's what you're missing" + activity digest Day 21 inactive: Re-engagement offer (discount, extended trial) Day 30 inactive: "Is everything okay?" — personal outreach feel Day 45 inactive: Win-back offer (significant discount) Day 60 inactive: Final email — "Should we close your account?" ``` ### 5. Upsell/Expansion Sequence (Trigger: usage threshold reached) ``` Day 0: "You're hitting limits" — data on their usage Day 2: Feature comparison (current plan vs next tier) Day 5: ROI calculator or case study of upgrade Day 7: Limited-time upgrade offer Day 10: Follow-up if no action taken ``` ## Key Metrics | Metric | Healthy Range | Action if Below | |--------|--------------|----------------| | Open Rate | 25-45% | Fix subject lines, sender name, send time | | Click Rate | 3-8% | Fix CTA, content relevance, design | | Reply Rate | 1-3% | More personal tone, ask questions | | Unsubscribe Rate | <0.5% per email | Reduce frequency, improve segmentation | | Bounce Rate | <2% | Clean list, verify emails at signup | | Spam Complaint Rate | <0.1% | Critical — fix immediately or domain gets blacklisted | ## Segmentation Strategy ### Behavioral Segments | Segment | Criteria | Use For | |---------|----------|---------| | Power Users | 5+ logins/week, multiple features used | Upsell, referral asks, testimonial requests | | Engaged | 2-4 logins/week | Feature education, community building | | At Risk | 1 login/week, declining | Re-engagement, value reminders | | Dormant | 0 logins for 14+ days | Win-back sequences | | Churned | Cancelled or expired | Win-back with offers | ### Lifecycle Segments | Segment | Stage | Primary Goal | |---------|-------|-------------| | New Signups | Onboarding | Activation (complete key action) | | Activated | Using product | Engagement + habit formation | | Trial Users | Pre-payment | Conversion to paid | | Paying Customers | Retention | Expansion + advocacy | | Churned | Lost | Win-back | ### Enrich Segments with the Persona Substrate + SDV Forecasts Behavioral and lifecycle segments above tell you *what* a user is doing; the **shared persona substrate** (`.gtm/personas/`, `schemas/persona.schema.json`) and **SDV forecasts** (`.gtm/sdv/forecasts/*.forecast.yml`) tell you *what they object to* and *what price they tolerate* — build the persona once, consume it here. Cross the two axes: - **Persona objections → which email handles which objection.** Each persona carries `pain_points`, and each SDV forecast carries structured `top_objections[]` (segment + objection + severity + `blocker_tier` B0/B1/B2 + `revenue_at_risk`). Map the highest-severity objection *for the persona(s) in a segment* to a specific email: the email that names and dissolves that exact objection. A B0 demand-blocker for a paying persona earns its own dedicated email; a B2 polish objection is a PS line. This is the routing rule — **one SDV-discovered objection, one email that answers it** — not generic benefit copy. - **Price tolerance → offer framing per persona.** A persona's `price_sensitivity` (`low`/`medium`/`high`) and any SDV `willingness_to_pay` band (Van Westendorp / Gabor-Granger range) set how an upsell/trial-to-paid email frames price: lead with value and a guarantee for high-sensitivity personas (and the lower offer tier), lead with the premium outcome for low-sensitivity personas. Never send the same discount framing to a `low` and a `high` `price_sensitivity` segment. - **Revenue weighting.** Prioritize sequence build order by the persona's `revenue_pct` and the objection's `revenue_at_risk` — handle the objection costing the most revenue first. If `.gtm/personas/` is empty, recommend `/gtm-personas derive`; if no SDV forecast exists yet, recommend `/gtm-validate` to discover objections before writing the objection-handling emails (the forecast's `top_objections[]` is the input, not a guess). ## A/B Testing Framework ### What to Test (Priority Order) 1. **Subject line** — 40% impact on opens 2. **Send time** — 20% impact on opens 3. **CTA button text and placement** — 30% impact on clicks 4. **Email length** — varies by audience 5. **Personalization level** — first name, company, usage data 6. **From name** — "Juan from Dojo" vs "Dojo Coding" vs "Dojo Team" ### Statistical Requirements - Minimum 1,000 recipients per variant - Run for at least 24 hours (captures all time zones) - 95% confidence level before declaring winner - Test one variable at a time