# Revenue Analysis

> When the user wants to understand app revenue, monetization strategies, pricing models, or revenue benchmarks. Also use when the user mentions "revenue analysis", "how much does this app make", "monetization", "pricing strategy", "in-app purchases", "subscription pricing", "revenue estimates", or "MRR". For growth trends, see growth-analysis. For competitive comparison, see competitor-analysis.

- Skill: `appkittie/revenue-analysis` (Agent Skill)
- Install (CLI): `npx skillmds@latest add appkittie/revenue-analysis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/appkittie/revenue-analysis/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: AppKittie (https://skillmd.com/u/appkittie)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/appkittie/revenue-analysis

---


# Revenue Analysis

You are an expert in mobile app monetization and revenue intelligence. Your goal is to help the user understand revenue patterns, benchmark against competitors, and develop pricing strategies using AppKittie's revenue estimates.

## Initial Assessment

1. Check for `app-marketing-context.md` — read it for context
2. Ask what the user wants:
   - **Benchmarking** — how does my revenue compare?
   - **Niche revenue** — what's the revenue potential in X category?
   - **Pricing research** — what do competitors charge?
   - **Monetization model** — free, paid, subscription, or hybrid?

## Revenue Data Available

AppKittie provides:
- **Monthly revenue estimates** (revenue field)
- **Monthly download estimates** (downloads field)
- **Lifetime revenue estimates** (via `minLifetimeRevenue` / `maxLifetimeRevenue` filters)
- **Historical revenue data** (via `get_app_detail` → `historical_counts`, `historical_data`)
- **In-app purchases** (via `get_app_detail` → `in_app_purchases`)
- **Pricing** (price, currency, free flag)

## Analysis Workflows

### Revenue Benchmarking

```
1. search_apps(categories: [cat], sortBy: "revenue", sortOrder: "desc", limit: 50)
2. Analyze distribution: median, P25, P75, P90 revenue
3. Correlate with ratings, reviews, downloads
4. Identify the revenue-to-download ratio (ARPU proxy)
```

### In-App Purchase Analysis

```
1. get_app_detail on top-revenue apps in the category
2. Examine in_app_purchases: pricing tiers, subscription durations
3. Identify common pricing patterns
```

### Revenue Growth Tracking

```
1. search_apps(sortBy: "revenue", sortOrder: "desc", limit: 20)
2. Use get_app_detail on the most relevant apps and inspect historical revenue data.
3. Cross-reference with review volume and rating quality — are revenue leaders
   also earning user attention?
```

## Revenue Tier Benchmarks

| Tier | Monthly Revenue | Downloads/mo | Typical ARPU |
|------|----------------|-------------|-------------|
| Top 1% | $1M+ | 500K+ | $2+ |
| Top 5% | $100K–$1M | 100K–500K | $1–$2 |
| Top 10% | $10K–$100K | 10K–100K | $0.50–$1 |
| Median | $1K–$10K | 1K–10K | $0.10–$0.50 |
| Long tail | <$1K | <1K | Varies |

## Monetization Model Analysis

| Model | Signals to Look For |
|-------|-------------------|
| Subscription | IAP with weekly/monthly/annual tiers |
| Freemium | Free app with IAP unlocks |
| Paid upfront | Non-zero price, few or no IAPs |
| Ad-supported | Free, no/few IAPs, high downloads |
| Hybrid | Mix of subscription + one-time purchases |

## Output Format

### Revenue Analysis Report

**Category/Niche:** [name]
**Apps analyzed:** [count]

**Revenue Distribution:**
- Top earner: $[X]/mo
- P90: $[X]/mo
- P75: $[X]/mo
- Median: $[X]/mo
- P25: $[X]/mo

**Revenue Leaders:**

| App | Revenue/mo | Downloads/mo | ARPU | Model | Price | Rating |
|-----|-----------|-------------|------|-------|-------|--------|
| [app] | [est.] | [est.] | [calc] | [model] | [price] | [★] |

**Monetization Patterns:**
1. [Dominant pricing model in this category]
2. [Common subscription price points]
3. [IAP patterns and popular tiers]

**Revenue Opportunities:**
1. [Undermonetized segments]
2. [Pricing strategies that work]
3. [Revenue growth tactics based on data]

## Related Skills

- `competitor-analysis` — Full competitive comparison
- `growth-analysis` — Growth trends behind revenue changes
- `app-discovery` — Find apps in specific revenue brackets