# Churn risk detector Human Guide

## What This Is For
Surface accounts at risk of churning before it's too late. It gives the agent a clearer input/output frame for go-to-market work: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Churn risk detector agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for churn risk detector.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Churn risk detector guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- "Which customers are at risk of churning?"
- "Run the weekly churn risk scan"
- "Flag accounts I should worry about"
- "Who haven't we heard from in a while?"
- "Produce a customer health report"
- **Customer list** — CSV or sheet with: company name, primary contact email, contract value (MRR/ARR), contract start date, renewal date (if known)
- **Product/service type** — What are they paying for? (Helps calibrate expected engagement)
- **Support tickets** — Export from Intercom, Zendesk, or email (CSV with: customer, date, subject, status, resolution time)
- **Slack channel history** — Customer Slack channel or shared channel messages
- **NPS/CSAT scores** — Recent survey results with scores and comments
- **Usage data** — Any metrics you track: logins, API calls, features used, active users (CSV export)
- **Email/communication log** — Last touchpoints per account (dates + context)

## Decision Points And Nuance
The original skill emphasizes: When to Use, Phase 0: Intake, Account Data, Signal Sources (provide what you have), Calibration, Phase 1: Signal Extraction, 1A: Support Signal Analysis, 1B: Communication Signal Analysis, 1C: Usage Signal Analysis (if data available), 1D: Commercial Signal Analysis.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- | **Yellow** | 20-39 | Early warning — monitor closely | Within 30 days |
- | 🟡 Yellow (Early Warning) | [N] | $[X] |
- 🟡 Early Warning Accounts

## Copy-And-Paste Prompt
```text
Use the Churn risk detector human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the gooseworks-ai/goose-skills skill entry for `churn-risk-detector`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# Churn Risk Detector

Surface accounts at risk of churning before it's too late. Aggregates signals from support, communication, and usage patterns into a scored risk report with specific save actions.

**Built for:** Early-stage teams with no CS platform (no Gainsight, no ChurnZero). You have a spreadsheet of customers, a Slack channel, and a support inbox. This skill turns those raw signals into an actionable churn risk list.

## When to Use

- "Which customers are at risk of churning?"
- "Run the weekly churn risk scan"
- "Flag accounts I should worry about"
- "Who haven't we heard from in a while?"
- "Produce a customer health report"

## Phase 0: Intake

### Account Data
1. **Customer list** — CSV or sheet with: company name, primary contact email, contract value (MRR/ARR), contract start date, renewal date (if known)
2. **Product/service type** — What are they paying for? (Helps calibrate expected engagement)

### Signal Sources (provide what you have)
3. **Support tickets** — Export from Intercom, Zendesk, or email (CSV with: customer, date, subject, status, resolution time)
4. **Slack channel history** — Customer Slack channel or shared channel messages
5. **NPS/CSAT scores** — Recent survey results with scores and comments
6. **Usage data** — Any metrics you track: logins, API calls, features used, active users (CSV export)
7. **Email/communication log** — Last touchpoints per account (dates + context)
8. **Billing data** — Payment failures, downgrades, discount requests

### Calibration
9. **What does "healthy" look like?** — Describe a healthy customer (e.g., "logs in daily, uses 3+ features, responds to emails within 24h")
10. **Known churn reasons** — Why have customers churned in the past? (helps weight signals)

## Phase 1: Signal Extraction

### 1A: Support Signal Analysis

From support ticket data, calculate per account:

| Signal | Calculation | Risk Weight |
|--------|-------------|-------------|
| **Ticket volume spike** | >2x their average in last 30 days | High |
| **Unresolved tickets** | Open tickets older than 7 days | High |
| **Escalation language** | Keywords: "cancel", "frustrated", "alternative", "not working", "disappointed" | Critical |
| **Response time degradation** | Your avg response time to this customer trending up | Medium |
| **Repeat issues** | Same problem reported 2+ times | High |

### 1B: Communication Signal Analysis

From Slack/email history:

| Signal | Calculation | Risk Weight |
|--------|-------------|-------------|
| **Gone silent** | No messages in 30+ days (was previously active) | High |
| **Decreasing frequency** | Message frequency dropped >50% vs prior 90 days | Medium |
| **Negative sentiment shift** | Tone changed from positive to neutral/negative | Medium |
| **Champion disengagement** | Primary contact stopped responding | Critical |
| **New stakeholder questions** | New person asking basic "what does this do?" questions | Medium (potential reorg) |

### 1C: Usage Signal Analysis (if data available)

| Signal | Calculation | Risk Weight |
|--------|-------------|-------------|
| **Login drop** | Active users down >30% vs prior month | High |
| **Feature abandonment** | Stopped using a key feature they previously used regularly | High |
| **Shallow usage** | Only using 1 feature when they're paying for many | Medium |
| **No growth** | Same number of seats/users for 6+ months | Low |
| **Export spike** | Sudden increase in data exports | Critical (may be migrating) |

### 1D: Commercial Signal Analysis

| Signal | Calculation | Risk Weight |
|--------|-------------|-------------|
| **Discount request** | Asked for pricing reduction | High |
| **Downgrade inquiry** | Asked about lower tier | Critical |
| **Payment failure** | Failed payment not resolved in 7+ days | High |
| **Contract approaching renewal** | <60 days to renewal with no renewal discussion | Medium |
| **Competitor mention** | Mentioned a competitor in any channel | High |

## Phase 2: Risk Scoring