Analyze subscription business health for Autostay — MRR breakdown, conversion funnel, churn analysis, and revenue forecasting. Use when reviewing subscription metrics, diagnosing churn, planning growth initiatives, or preparing investor/board updates.
From autostay-pmnpx claudepluginhub autostay-kr/autostay-skills --plugin autostay-pmThis skill uses the workspace's default tool permissions.
Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Migrates code, prompts, and API calls from Claude Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, updating model strings on Anthropic, AWS, GCP, Azure platforms.
Details PluginEval's skill quality evaluation: 3 layers (static, LLM judge), 10 dimensions, rubrics, formulas, anti-patterns, badges. Use to interpret scores, improve triggering, calibrate thresholds.
Provide a comprehensive health check of Autostay's subscription business across revenue, conversion, churn, unit economics, and overall health scoring. Delivers actionable recommendations to improve subscription performance.
Autostay — O2O 세차 구독 서비스
Given the following context and data: $ARGUMENTS
If the user provides data files (CSV, Excel, dashboards, or metrics summaries), read and analyze them directly. If no data is provided, ask the user for the key metrics or generate a template for them to fill in.
Calculate and present the five components of MRR movement:
| MRR Component | Definition | Amount | % of Starting MRR |
|---|---|---|---|
| Starting MRR | MRR at the beginning of the period | - | 100% |
| New MRR | Revenue from newly acquired subscribers | + | |
| Expansion MRR | Revenue from upgrades (월간 → 연간, add-on services) | + | |
| Contraction MRR | Revenue lost from downgrades | - | |
| Churned MRR | Revenue lost from cancelled subscriptions | - | |
| Net New MRR | New + Expansion - Contraction - Churned | = | |
| Ending MRR | Starting + Net New | = |
Visualize as a waterfall chart. Flag if Net New MRR is negative (business is shrinking).
Key ratios to calculate:
4 = Very healthy, 2-4 = Good, 1-2 = Needs attention, <1 = Shrinking
Map the full subscriber journey and calculate conversion rates at each stage:
App Download → Registration → First Booking → Paid Subscription → 3-Month Retained → 12-Month Retained
| Stage | Count | Conversion Rate | Drop-off Rate | Benchmark |
|---|---|---|---|---|
| App Download | 100% | - | - | |
| Registration | % of downloads | % drop | >30% | |
| First Booking (trial/free wash) | % of registrations | % drop | >20% | |
| Paid Subscription | % of first bookings | % drop | >15% | |
| 3-Month Retained | % of paid subs | % drop | >60% | |
| 12-Month Retained | % of paid subs | % drop | >35% |
For each drop-off point, identify:
Analyze churn across three dimensions:
By Plan Type:
| Plan Type | Subscribers | Churned | Churn Rate | Avg Tenure |
|---|---|---|---|---|
| 월간 (Monthly) | ||||
| 연간 (Annual) | ||||
| Total |
By Tenure (subscriber age):
| Tenure | Churned | Churn Rate | Key Churn Reason |
|---|---|---|---|
| Month 1 (0-30 days) | |||
| Month 2-3 | |||
| Month 4-6 | |||
| Month 7-12 | |||
| Month 12+ |
By Churn Reason:
| Reason | Count | % of Total Churn | Preventable? |
|---|---|---|---|
| Price too high | Yes — test pricing/plans | ||
| Not using enough | Yes — engagement campaigns | ||
| Service quality issues | Yes — partner QA | ||
| Moved / no nearby partner | Partially — coverage expansion | ||
| Switched to competitor | Yes — competitive positioning | ||
| Payment failure (involuntary) | Yes — dunning optimization | ||
| Other |
Calculate and evaluate key unit economics:
| Metric | Value | Benchmark | Status |
|---|---|---|---|
| LTV (Lifetime Value) | ARPU / Monthly Churn Rate | >3x CAC | |
| CAC (Customer Acquisition Cost) | Marketing Spend / New Subscribers | Decreasing trend | |
| LTV:CAC Ratio | LTV / CAC | >3:1 healthy, >5:1 excellent | |
| CAC Payback Period | CAC / Monthly ARPU | <12 months | |
| Per-Wash Economics | Revenue per wash - Cost per wash | Positive margin | |
| Gross Margin | (Revenue - COGS) / Revenue | >50% |
Per-Wash Economics Detail:
Assign a health score to each dimension:
| Dimension | Score | Key Indicator | Action Required |
|---|---|---|---|
| Revenue Growth | 🟢 / 🟡 / 🔴 | MRR trend, Quick Ratio | |
| Conversion Efficiency | 🟢 / 🟡 / 🔴 | Funnel conversion rates | |
| Churn Control | 🟢 / 🟡 / 🔴 | Monthly churn rate, churn trend | |
| Unit Economics | 🟢 / 🟡 / 🔴 | LTV:CAC, payback period | |
| Engagement | 🟢 / 🟡 / 🔴 | Wash frequency, DAU/MAU |
Scoring Criteria:
Overall Health: [🟢 Healthy / 🟡 Needs Attention / 🔴 Critical] with a 1-sentence summary.
Provide 3-5 prioritized recommendations based on the analysis:
For each recommendation:
| # | Recommendation | Addresses | Expected Impact | Effort | Priority |
|---|---|---|---|---|---|
| 1 | [Specific action] | [Which health dimension] | [Quantified if possible] | [Low/Med/High] | [P0/P1/P2] |
| 2 | ... | ... | ... | ... | ... |
Each recommendation should include:
Save the full analysis as a markdown document with all six sections. Include: