Kai Retention

kai-retention — Customer Retention System

Design a complete retention system: churn diagnostics, retention tactics, engagement scoring, loyalty mechanics, and win-back campaigns.

Phase 0: Load Product Context

Check if MARKETING.md exists in the project root (same directory as CLAUDE.md, README.md, package.json).

If it exists: Read it — skip product discovery questions. It has the product name, ICP, value prop, monetization, brand voice, current channels, and competitive landscape.

If it does NOT exist: Auto-explore the codebase to create it in the project root (next to CLAUDE.md). Do NOT ask the user what the product is. Read CLAUDE.md, README.md, PROJECT.md, package.json, landing pages, and any project files. Search for email/ad/analytics config. Then create MARKETING.md using the template from /kai-email-system. Present draft to user for confirmation.

References

Load these files as context before starting:

• knowledge/playbooks/customer-retention.md
• knowledge/playbooks/growth-loops-applied.md
• knowledge/channels/email-lifecycle.md
• knowledge/personas/_persona-index.md

Phase 1 — Discovery

1. Read from MARKETING.md. Only ask about things not covered there:
   • Business model (SaaS, ecommerce, services, marketplace)
   • Current churn rate (monthly/annual, if known)
   • Customer count and average revenue per customer
   • Current retention efforts (any emails, loyalty program, support)
   • Known churn reasons (from exit surveys, support tickets, cancellation flow)
   • Product usage data availability (do they track feature adoption?)
   • Customer segments (free vs. paid, plan tiers, cohorts)
2. Identify the retention maturity level:
   • Level 0: No retention effort beyond the product itself
   • Level 1: Basic cancellation flow + occasional check-in emails
   • Level 2: Lifecycle emails + usage tracking + support triggers
   • Level 3: Predictive churn scoring + proactive intervention + loyalty program

Phase 2 — Analysis

Churn Diagnostics

1. Categorize churn types:
   • Voluntary: Customer actively cancels (dissatisfaction, budget, switched)
   • Involuntary: Payment failure, expired card, billing issue
   • Passive: Stops using but doesn't cancel (ghost users)
2. Map the churn timeline: when do most customers leave?
   • First 30 days (onboarding failure)
   • 60-90 days (value not realized)
   • At renewal (annual plan decision point)
   • After price increase or feature change
3. Identify leading indicators of churn:
   • Login frequency decline
   • Feature usage drop
   • Support ticket volume spike
   • NPS/CSAT score decline
   • Billing page visits

Engagement Scoring Model

Define a health score (0-100) based on:

Risk tiers: Green (70-100), Yellow (40-69), Red (0-39).

Phase 3 — Produce

Build these deliverables:

Retention Playbook

Intervention strategies by risk tier:

Red (0-39) — Immediate Rescue

• Trigger personal outreach within 24 hours
• Offer concession (discount, extended trial, premium support)
• Escalate to customer success manager
• Deploy win-back email sequence

Yellow (40-69) — Proactive Nurture

• Send usage tips targeting unused features
• Invite to office hours or webinar
• Share relevant case study or success story
• Request feedback (short survey, not NPS)

Green (70-100) — Expansion & Advocacy

• Request referral or testimonial
• Offer early access to new features
• Invite to advisory board or beta program
• Cross-sell or upsell relevant add-ons

Win-Back Campaign

For customers who have already churned:

• 3-email sequence: Day 1, Day 7, Day 30
• Each email addresses a different churn reason
• Include a specific offer or product update
• Run through quality gates before sending

Loyalty Program Design (if applicable)

• Reward mechanics: points, tiers, milestones, or referral credits
• Earning actions mapped to business goals
• Redemption options that drive retention (not margin erosion)
• Communication plan for program launch

Involuntary Churn Prevention

• Dunning email sequence (3-5 emails over 14 days)
• Smart retry logic for failed payments
• Card update reminder before expiration

Phase 4 — Output

1. Deliver the retention playbook and engagement scoring spec.
2. Run all email sequences through quality gates:
   • python scripts/quality_gates/banned_word_check.py <file>
   • python scripts/quality_gates/four_us_score.py <file>
3. Include a 90-day implementation roadmap and monthly metrics to track (churn rate, cohort retention, health score distribution, NPS trend, expansion vs. contraction revenue).

Constraints

• No banned Tier 1 words in any customer-facing copy.
• Win-back emails must comply with CAN-SPAM (reference: harness/references/cold-email-rules.md).
• Loyalty program rewards must not erode margins below profitability.
• Discount offers in rescue plays capped at 20% unless user approves higher.
• All email sequences target 10+/16 on Four U's scoring.
• Max 2 auto-retry cycles on quality gate failures for email content.