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Zhongwei Li
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---
name: ab-testing
description: Use when designing experiments for subject lines, offers, cadences, or
journeys.
---
# Experimentation & A/B Testing Skill
## When to Use
- Validating new subject lines or creative.
- Testing segmentation hypotheses (persona vs behavior).
- Optimizing cadence, timing, or automation triggers.
## Framework
1. **Hypothesis** define expected uplift + rationale.
2. **Metric Selection** primary (open/click/conv) + guardrails (unsubs, spam).
3. **Sample Sizing** ensure stat significance (min 500 recipients per variant or use power calculator).
4. **Execution** randomize, keep variants isolated, limit simultaneous tests.
5. **Analysis** use z-test or Bayesian uplift; document learnings.
## Templates
- Experiment brief (hypothesis, segments, KPI, risk guardrails).
- Variant table (control vs test inputs, creative asset links, owner).
- Calculator sheet for minimum detectable effect + sample size.
- Post-test debrief doc capturing learnings + rollout plan.
## Experiment Ideas
- Subject line vs preview text combos.
- CTA placement (hero vs footer).
- Personalization depth (basic vs dynamic modules).
- Wait times between touches.
## Tips
- Run no more than two tests per journey simultaneously.
- Recycle learnings into playbooks + automation templates.
- Segment results by persona to catch hidden signals.
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---
name: deliverability-ops
description: Use when investigating inbox placement, reputation, and compliance signals
across senders.
---
# Deliverability Operations Skill
## When to Use
- Inbox placement drops or spam-folder complaints.
- Preparing for IP/domain warmups or volume ramps.
- Auditing authentication, feedback loops, or compliance settings.
## Framework
### Signals to Monitor
1. **Engagement** opens, clicks, unsubscribes, spam complaints by ISP.
2. **Reputation** Google Postmaster, Microsoft SNDS, Talos/Barracuda, Spamhaus, Validity.
3. **Infrastructure** SPF/DKIM/DMARC alignment, BIMI, TLS, reverse DNS, dedicated vs shared IP.
4. **List Health** bounce types, spam traps, opt-in provenance, inactivity thresholds.
### Playbook Steps
1. Snapshot key metrics over last 7/30 days.
2. Identify affected mailbox providers (Gmail, Outlook, Yahoo, etc.).
3. Validate authentication + sending domains.
4. Segment audiences by engagement tier; limit sends to VIP/high intent.
5. Recommend remediation actions (warmup plan, content refresh, list cleaning, cadence adjustment).
## Templates
- Deliverability diagnostic worksheet (reputation + infrastructure + content).
- IP/domain warmup tracker (volume ramp table).
- Compliance checklist (CAN-SPAM, CASL, GDPR/CCPA, unsubscribe handling).
## Tips
- Pair with `segmentation` skill to isolate healthy cohorts.
- Document every remediation change to correlate with future reputation shifts.
- Align marketing, security, and legal teams on consent language.
---

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---
name: drip-campaigns
description: Use when you need to map sequenced nurture flows with pacing, storytelling
arcs, and value ladders.
---
# Drip Campaign Design Skill
## Framework
1. **Objective Mapping** each touch must have a single job (educate, qualify, convert).
2. **Value Ladder** sequence benefits from awareness → consideration → decision.
3. **Cadence** balance urgency with fatigue (2448h early, 72h+ later).
4. **Signal-Based Branching** accelerate for high intent, slow for low engagement.
## Templates
```
Touch | Timing | Objective | Content Angle | CTA | Personalization
```
- Message hierarchy worksheet
- Cadence testing checklist
- Personalization matrix (firmographic + behavioral signals)
## Tips
- Alternate between insight, proof, and offer touches to keep attention high.
- Use soft CTAs early, stronger CTAs after value delivered.
- Add progressive profiling questions to capture more data per touch.
- Mirror messaging across ads + sales outreach so the drip feels orchestrated.
## When to Use
- Launching a new nurture series and need a cadence blueprint.
- Translating product education journeys into sequenced content.
- Reworking underperforming drips with better pacing and offers.
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---
name: segmentation
description: Use when designing filters, suppression logic, and personalization cohorts
for campaigns or automations.
---
# Advanced Segmentation Playbooks
## When to Use
- Planning campaigns requiring persona, lifecycle, or behavioral splits.
- Creating suppression logic to protect deliverability and compliance.
- Building engagement tiers for experimentation and reporting.
## Framework
1. **Lifecycle Grid** axis of lifecycle stage vs engagement level.
2. **Data Integrity** confirm consent, field completeness, and recency.
3. **Priority Scoring** route high-value segments to premium workflows.
## Checklist
- ✅ Primary filter (persona, stage, product usage)
- ✅ Secondary filters (intent, region, business size)
- ✅ Suppress: unsubscribed, bounced, low engagement, legal blocks
- ✅ Personalization fields: {{first_name}}, {{company}}, dynamic modules
## Templates
- **Segmentation Matrix**: See `assets/segmentation_matrix.md` for tier definitions and logic examples.
- **Launch Tiering** VIP, Prospects, Dormant with separate cadence and pacing table.
- **Signal-Driven** product milestones trigger micro-segments; includes trigger → audience matrix.
- **Compliance Safe** CASL/GDPR consent matrix + suppression filters by region.
## Tips
- Keep segment definitions in a shared schema doc for consistency.
- Use dashboards to monitor size changes week over week.
- Pair segmentation with A/B testing to validate hypotheses.