| name | business-analysis |
| description | Analyze SpaceLaunchNow business environment, monetization, costs, and performance. Use when: reviewing subscription revenue model, CI/CD spend, ad monetization, app store strategy, analytics tracking, premium feature gating, release cadence, or RevenueCat integration health. |
Business Analysis for SpaceLaunchNow
When to Use
- Evaluate or optimize the monetization strategy (subscriptions, ads, premium features)
- Analyze CI/CD pipeline costs and identify savings opportunities
- Review RevenueCat subscription integration health and entitlement mapping
- Assess analytics/observability coverage (Datadog RUM, Firebase)
- Plan app store release strategy or review release cadence
- Audit premium feature gating and conversion funnel
- Compare revenue tiers (monthly vs annual vs lifetime) or plan pricing changes
- Investigate ad network configuration (AdMob, SKAdNetwork)
Business Model Overview
SpaceLaunchNow uses a freemium model with three revenue streams:
- Subscriptions (RevenueCat) — Monthly, Annual, Lifetime plans granting the
premium entitlement
- Advertising (AdMob) — Banner, interstitial, and rewarded ads for free-tier users
- Premium Features — Ad removal, premium widgets, premium themes gated behind subscription
Procedure
1. Identify the Analysis Domain
Determine which business area the question covers:
| Domain | Reference | Data Source |
|---|
| Monetization & Subscriptions | monetization.md | RevenueCat MCP (live) + docs/billing/ |
| Analytics & Observability | analytics.md | analytics/DatadogConfig.kt |
| App Store & Distribution | app-store.md | docs/release-notes/, fastlane |
2. Gather Live Data (RevenueCat MCP)
The RevenueCat MCP integration (RC_MCP, exposed as mcp__claude_ai_RC_MCP__* tools)
provides live access to subscription data. Tool schemas are loaded on demand — use
ToolSearch with select:<tool> (or a keyword query like revenuecat overview) before
calling, then invoke the tool.
| Tool | Purpose | When to Use |
|---|
mcp__claude_ai_RC_MCP__get-overview-metrics | MRR, revenue, active subs, trials, active users, new customers | Start here for any revenue question |
mcp__claude_ai_RC_MCP__list-projects | Confirm the project ID (projbe17841f) and metadata | Needed as input to other calls |
mcp__claude_ai_RC_MCP__list-apps | List apps (iOS: app70aaf33046, Android: appb9bf4f1820) | Platform-specific analysis |
mcp__claude_ai_RC_MCP__list-entitlements | Active entitlements (Pro, Lifetime, Legacy) | Feature gating audit |
mcp__claude_ai_RC_MCP__list-offerings | Current + legacy offerings | Offering structure review |
mcp__claude_ai_RC_MCP__list-products | All products across both stores | Product catalog audit |
mcp__claude_ai_RC_MCP__list-packages | Packages within an offering | Package structure review |
mcp__claude_ai_RC_MCP__get-chart-data | Historical chart data for trends | Trend/churn analysis |
mcp__claude_ai_RC_MCP__get-chart-options-schema | Available chart types | Discover what trends are available |
Project ID: projbe17841f (required for most calls)
Quick start for any revenue question:
1. Call mcp__claude_ai_RC_MCP__get-overview-metrics with project_id=projbe17841f
2. Parse: MRR, revenue (28d), active_subscriptions, active_trials, active_users, new_customers
3. Calculate conversion rate: active_subscriptions / active_users
3. Gather Static Data
- Read the relevant reference doc for architecture and implementation details
- Review
docs/billing/ for subscription architecture decisions
- Review
docs/cicd/ for pipeline cost data and optimization history
- Review
docs/premium/ for feature gating and premium feature definitions
- Check the source files listed in each reference for code-level details
For broad code sweeps ("where is every premium gate?"), delegate to the Explore agent
rather than reading files one at a time.
4. Analyze
When analyzing, consider:
- Revenue: Which subscription tier drives the most value? Is lifetime cannibalizing recurring?
- Conversion: Are premium feature gates compelling enough? Is the SupportUsScreen effective?
- Retention: Does analytics coverage capture enough user journey data for retention analysis?
- Compliance: Are ad networks (SKAdNetwork) properly configured? Privacy implications?
5. Recommend
Provide actionable recommendations grounded in the codebase and live data. Reference specific files, configurations, or docs when suggesting changes. Quantify impact using real metrics from RevenueCat MCP where possible (e.g., "$X/month savings", "Y% of 27K active users affected").
Key Business Metrics to Track
- MRR/ARR: Monthly/Annual recurring revenue from subscriptions
- Conversion Rate: Free → Paid conversion from SupportUsScreen
- Release Cadence: Tracked via
version.properties and CHANGELOG.md
- Ad Revenue: AdMob impressions/clicks for non-premium users
- Churn: Subscription cancellations tracked via RevenueCat dashboard
Live Data Access
RevenueCat MCP (mcp__claude_ai_RC_MCP__*) provides real-time access to:
- Revenue metrics (MRR, 28-day revenue, transaction counts)
- Subscriber counts (active subscriptions, trials)
- User metrics (active users, new customers)
- Product catalog, entitlements, offerings, packages
- Chart data for historical trends
GitHub data — use the gh CLI (this repo's primary GitHub interface) for:
- Repository issues and pull requests (
gh pr list, gh issue list)
- Workflow runs for CI/CD cost estimation (
gh run list)
- Release history and tags (
gh release list, git tag --list 'v*')
Important Context
- RevenueCat Project ID:
projbe17841f
- iOS App ID:
app70aaf33046 | Android App ID: appb9bf4f1820
- Entitlements: Pro (
entl9fe2b6018c), Lifetime (entleb14c06f19), Legacy (entl3ad15261a3)
- RevenueCat integration is 100% complete (6 phases) — see
docs/billing/REVENUECAT_COMPLETE_PROGRESS_SUMMARY.md
- Datadog RUM tracks user sessions with subscription state attributes
- Version and build numbers are in
version.properties (monotonically increasing for Play Store)
