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Revenue Estimation Toolkit

Revenue estimation is critical for deciding whether an opportunity is worth pursuing. Never rely on a single method — triangulate from multiple sources.

Claude Code Knowledge Pack7/10/2026

Overview

Revenue Estimation Toolkit

Revenue estimation is critical for deciding whether an opportunity is worth pursuing. Never rely on a single method — triangulate from multiple sources.

Method 1: Rating-Count Proxy

iOS doesn't show download counts, but rating counts are a useful proxy.

The Formula

Estimated downloads = rating_count × multiplier
App TypeMultiplierReasoning
Free apps (no prompt)× 80-120Few users bother to rate
Free apps (prompted)× 40-60Rating prompts increase rate
Paid apps× 20-40Paying users rate more often
Subscription apps× 30-50Mix of prompted and organic

Confidence Levels

Rating CountConfidenceNotes
>10,000HighLarge sample, multiplier is reliable
1,000-10,000MediumReasonable estimate, ±30% margin
100-1,000LowWide variance, use as directional only
<100Very LowCould be new, niche, or genuinely unpopular

Example Calculation

App with 5,000 ratings (subscription, uses rating prompts):

  • Estimated downloads: 5,000 × 40 = 200,000
  • At 5% conversion to paid: 10,000 paying users
  • At $14.99/yr: ~$150K/yr = ~$12.5K/mo

Important: This is a rough estimate. Always cross-reference with other methods.

Method 2: App Store Chart Position

Chart position correlates with daily downloads:

Chart Position (US)Estimated Daily DownloadsNotes
Top 10 Overall30,000-100,000+Major apps only
Top 50 Overall10,000-30,000Significant traction
Top 10 Category2,000-10,000Category leader
Top 50 Category500-2,000Solid performer
Top 100 Category200-500Moderate traction
Top 200 Category50-200Baseline visibility

These numbers vary significantly by category. Health & Fitness top 10 is very different from Board Games top 10.

Method 3: Public Revenue Data Sources

Direct Revenue Reports

  • IndieHackers.com: Filter by iOS apps, many share exact MRR
  • Twitter #buildinpublic: Indie devs post monthly revenue screenshots
  • RevenueCat blog: "State of Subscription Apps" annual reports with aggregate data by category
  • Sub Club podcast: Founders share revenue numbers openly
  • AppFigures/Sensor Tower blogs: Occasional free category reports

Search Patterns

"{app name}" revenue OR MRR OR ARR
"{app name}" "monthly revenue"
site:indiehackers.com "{category}" revenue ios
site:twitter.com "{app name}" revenue
"{category} app" "$" "per month" site:reddit.com

Known Indie iOS Revenue Data Points (Reference)

AppCategoryRevenueModelTeam Size
RootdHealth/Anxiety$1M+ totalSubscription1 person
DaylioMood tracker~$50K/moFreemiumSmall
FinchSelf-care~$2M/moSubscriptionSmall
CalmMeditation$100M+/yrSubscriptionCompany
WiprAd blockerUndisclosedOne-time $21 person
1BlockerAd blocker$3-5M/yrSubscriptionSmall
Carrot WeatherWeather~$20K/moSubscription1 person
HalideCameraUndisclosedOne-time2 people
StreaksHabit trackerUndisclosedOne-time $51 person
Dark NoiseSound machine~$3-5K/moOne-time1 person

Method 4: Competitor Pricing Reverse Engineering

If competitors charge subscription prices, you can estimate their revenue floor:

Minimum viable revenue = team_size × $100K/yr (rough salary cost)

If a 5-person company charges $9.99/mo, they need at minimum:

  • $500K/yr revenue to survive
  • = ~4,200 active subscribers
  • = probably 40,000-80,000 total downloads (at 5-10% conversion)

This gives you a floor estimate of market size.

Method 5: Revenue Modeling Template

For your own opportunity, build a simple model:

Monthly Revenue = Downloads/mo × Trial Start Rate × Trial→Paid Rate × Price/mo

Example:
- ASO + marketing drives 3,000 downloads/mo
- 40% start free trial = 1,200 trials
- 20% convert to paid = 240 new subscribers/mo
- At $14.99/yr ($1.25/mo effective) = $300/mo new MRR
- With 5% monthly churn, steady state ≈ 4,800 subscribers
- Steady state revenue ≈ $6,000/mo

Lifetime model alternative:
- 3,000 downloads/mo
- 15% buy lifetime at $39.99 = 450 purchases = $18,000/mo

Adjust assumptions based on category benchmarks in benchmarks.md.

Revenue Red Flags

  • No competitor in the category charges more than $2.99 (low WTP ceiling)
  • Top apps are free with no in-app purchases (users expect free)
  • Category is dominated by ad-supported apps (race to the bottom)
  • All subscription competitors have "too expensive" as the #1 complaint
  • Category has a strong free open-source alternative

Revenue Green Flags

  • Multiple competitors successfully charge $9.99+/mo (proven WTP)
  • Users in Reddit threads say "I'd gladly pay for..."
  • Competitor with poor quality still makes money (market will support better product)
  • Category has high switching costs (data lock-in, learning curve)
  • Problem is painful enough that money is not the primary objection