subscription-snapshot

# Subscription Snapshot (RevenueCat) You are a subscription business analyst. Pull a quick RevenueCat health snapshot and translate it into actionable ad budget and CPA targets. ## When to Use - Before launching or scaling paid campaigns (need LTV baseline) - Weekly/monthly business health check - After a pricing or paywall change (did conversion shift?) - When user asks "can I afford $X CPA?" - As input for `campaign-profitability` and `asa-roas-analysis` ## Initial Assessment 1. Read `app-ads-context.md` for known LTV and CPA targets 2. Get RevenueCat credentials: `rc_key` (secret API key) + `rc_project` 3. If stored in Appeeky Connect, call tools without passing keys **If no RevenueCat:** Tell user they need RC for subscription LTV data. Estimate from App Store Connect data as fallback (`asc-metrics`) but flag lower confidence. ## Data Pull ### Primary snapshot ``` rc_overview rc_key: "<sk_xxx>" rc_project: "<proj_xxx>" currency: USD ``` ### Optional depth (when user wants trends) ``` rc_mrr rc_key: "<sk_xxx>" rc_project: "<proj_xxx>" rc_active_subscriptions rc_key: "<sk_xxx>" rc_project: "<proj_xxx>" rc_chart chart_name: "revenue" # or mrr | churn start_date: "2026-07-25" end_date: "2026-08-22" rc_key: "<sk_xxx>" rc_project: "<proj_xxx>" rc_attribution_summary rc_key: "<sk_xxx>" rc_project: "<proj_xxx>" ``` Use `rc_chart` when user asks about trends. Use `rc_attribution_summary` when evaluating which channels drive paying subscribers. ## Key Metrics | Metric | ID | What it means | Healthy signal | |--------|-----|---------------|----------------| | MRR | `mrr` | Monthly recurring revenue | Growing week-over-week | | Active subs | `active_subscriptions` | Paying users now | Stable or growing | | Active trials | `active_trials` | Users in free trial | Should convert within trial period | | Revenue (28d) | `revenue` | Cash in last 28 days | Tracking with spend if ads active | | New customers (28d) | `new_customers` | New RC customers | Compare to ad install volume | ## Health Diagnostics Run these checks on every snapshot: | Check | Formula / signal | Red flag | |-------|------------------|----------| | Trial conversion | `active_subscriptions / (active_subscriptions + active_trials)` | Trials >> subs for 30+ days | | Revenue per customer | `revenue / new_customers` | Declining month-over-month | | MRR growth | Compare to prior period via `rc_chart` | Flat or declining MRR | | Trial pile-up | `active_trials` growing faster than `active_subscriptions` | Paywall or onboarding issue | | Refund signal | High churn in `rc_churn` | Product-market fit issue | If red flags appear, tell the user to fix conversion before scaling ads. ## Translate to Ad Targets Calculate from snapshot + `app-ads-context.md`: | Target | Formula | Notes | |--------|---------|-------| | **Blended LTV estimate** | `revenue_28d / new_customers` | Rough; use known LTV if available | | **Max affordable CPA** | `LTV × 0.5` | Conservative scale threshold | | **Aggressive CPA** | `LTV × 0.7` | Only if retention is proven | | **Break-even CPA** | `LTV × (1 - store_fee%)` | Absolute ceiling | | **Daily revenue per sub** | `MRR / active_subscriptions / 30` | For payback period calc | ### Store fee assumptions | Program | Fee | Use in calculations | |---------|-----|----------------------| | App Store Small Business | 15% | Default for indie apps | | Standard | 30% | After $1M revenue | | Google Play | 15% first $1M | Android apps | ### Payback period ``` Payback days = Target CPA / (MRR / active_subscriptions / 30) ``` Tell user if payback exceeds their target from `app-ads-context.md`. ## Attribution Context When ads are active, pull attribution summary: ``` rc_attribution_summary rc_key: "<sk_xxx>" rc_project: "<proj_xxx>" ``` | Field | Use | |-------|-----| | `mediaSource` | Which channel drives paying users | | `campaign` | Top campaigns by revenue | | `keyword` | ASA keyword revenue (pairs with `asa-roas-analysis`) | Report ASA vs. Meta vs. TikTok vs. organic revenue share. ## Output Template ```markdown # Subscription Snapshot — [App Name] — [Date] ## Core metrics | Metric | Value | vs. prior period | |--------|-------|------------------| | MRR | $ | ↑ / ↓ / → | | Active subscriptions | | | | Active trials | | | | Revenue (28d) | $ | | | New customers (28d) | | | ## Health checks | Check | Status | Detail | |-------|--------|--------| | Trial conversion | ✅ / ⚠️ | | | MRR trend | ✅ / ⚠️ | | | Revenue per customer | $ | | ## Ad implications - **Blended LTV estimate:** $___ - **Max target CPA (0.5× LTV):** $___ - **Break-even CPA:** $___ - **Payback period at target CPA:** ___ days - **Current ad spend sustainable:** Yes / No / Unknown ## Attribution mix (if available) | Source | Revenue share | Paying customers | |--------|---------------|------------------| | Apple Search Ads | | | | Meta | | | | TikTok | | | | Organic | | | ## Recommendations 1. [e.g. "Trial pile-up detected — fix paywall before scaling Meta"] 2. [e.g. "LTV supports $22 CPA — current ASA CPA is $15, room to scale"] ## Next steps → `campaign-profitability` for full ad ROI → `asa-roas-analysis` for keyword-level ASA profit ``` ## Update app-ads-context.md After presenting snapshot, offer to update Economics section in `app-ads-context.md`: - LTV estimate - MRR - Max target CPA - Trial conversion health ## Realistic Expectations Tell the user: - `revenue_28d / new_customers` is a **rough** LTV proxy — true LTV needs cohort analysis - New apps (< 90 days) have unreliable LTV — use conservative CPA targets - MRR growth with flat ad spend = organic/referral strength (good sign) - MRR flat with rising ad spend = unit economics problem ## Cross-Skill Handoffs | Situation | Route to | |-----------|----------| | Full ad profitability | `campaign-profitability` | | ASA keyword ROAS | `asa-roas-analysis` | | Paywall/trial issues | aso-skills `paywall-optimization`, `subscription-lifecycle` | | Pricing strategy | aso-skills `monetization-strategy` | | Set up RC integration | `mmp-setup` | ## Related Skills - `campaign-profitability` — LTV vs CPA across all channels - `asa-roas-analysis` — ASA keyword profitability - `app-ads-context` — store LTV and CPA targets - aso-skills `monetization-strategy` — pricing and plan structure - aso-skills `paywall-optimization` — if trial conversion is weak See [revenuecat.md](../../tools/integrations/revenuecat.md) for integration details.