business-analysis

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:

1. Subscriptions (RevenueCat) — Monthly, Annual, Lifetime plans granting the premium entitlement
2. Advertising (AdMob) — Banner, interstitial, and rewarded ads for free-tier users
3. 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)