git:20260326.6cdda8e to git:20260326.a6cd2e8

3 added, 3 removed. Audit A to A.

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name: kai-retention

description: Customer retention system — churn analysis, retention tactics, loyalty programs, and engagement scoring. Use when "retention", "reduce churn", "keep customers", "loyalty program", "customer retention", "churn prevention", "churn analysis", "engagement scoring", "win-back", "customer lifetime value", or any request to analyze, prevent, or reduce customer churn.

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# 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).

+ 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.

+ **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.

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## References

Load these files as context before starting:

- `E:\Dev2\kai-cmo-harness-work\knowledge\playbooks\customer-retention.md`

- `E:\Dev2\kai-cmo-harness-work\knowledge\playbooks\growth-loops-applied.md`

- `E:\Dev2\kai-cmo-harness-work\knowledge\channels\email-lifecycle.md`

- `E:\Dev2\kai-cmo-harness-work\knowledge\personas\_persona-index.md`

## Phase 1 — Discovery

- 1. Read from `marketing.md`. Only ask about things not covered there:

+ 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:

| Signal | Weight | Scoring |

|--------|--------|---------|

| Login frequency (last 14 days) | 25% | Daily=100, Weekly=60, Monthly=20, None=0 |

| Core feature usage | 25% | Used all=100, Used some=50, Used none=0 |

| Support interactions | 15% | Positive=80, Neutral=50, Negative=20 |

| Account expansion signals | 15% | Upgraded=100, Stable=50, Downgraded=10 |

| Referral/advocacy | 10% | Referred=100, NPS promoter=60, Passive=30 |

| Billing health | 10% | Current=100, Late=30, Failed=0 |

**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 E:\Dev2\kai-cmo-harness-work\scripts\quality_gates\banned_word_check.py <file>`

- `python E:\Dev2\kai-cmo-harness-work\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: `E:\Dev2\kai-cmo-harness-work\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.