How do tracked apps actually make money — subscription, ads, or transactions?
Subscription is the default: 418 of 686 attribute-tagged apps (61%) carry a subscription model, more than double advertising at 176/686 (26%) [1]. Cross-subsidized funnel/companion apps (124), marketplace/transaction fees (70), and B2B licensing (44) form the next tier [1]. If you are choosing a primary revenue stream for a consumer app, subscription is the modal bet, but it is far from universal — 39% of apps monetize some other way.
418 of 686 attribute-tagged apps (61%) run on subscription — July 2026.
The revenue-model leaderboard
Across the 686 apps with a business-model tag, the ranked prevalence is [1]:
| Business model | Apps | Share of 686 |
|---|---|---|
| Subscription | 418 | 61% |
| Advertising | 176 | 26% |
| Cross-subsidized Funnel / Companion App | 124 | 18% |
| Marketplace / Transaction Fees | 70 | 10% |
| B2B Licensing | 44 | 6% |
| Financial Rails Revenue | 41 | 6% |
| Commerce Margin | 39 | 6% |
| IAP Consumables / Usage | 36 | 5% |
| One-Time Purchase | 28 | 4% |
| Creator Monetization Take Rate | 26 | 4% |
The tag is multi-valued, so shares sum past 100% — the mean app carries 1.64 models [2].
How to apply it
Subscription is the safe default for a consumer or prosumer app, but treat advertising and cross-subsidized funnels as live alternatives, not fringe cases — together they cover 300 apps [1]. If your model is not subscription, you are in good company; nearly 4 in 10 tracked apps monetize some other way. Use the category and archetype cuts (linked below) before locking a model, because the overall leaderboard hides large per-category swings — Health & Fitness is 98% subscription while Shopping is almost none.
Caveats
The honest denominator is the ~800-app tracked corpus, specifically the 686 apps carrying a business_model tag — never 62,376 companies [1]. business_model is a multi-valued array, so counts are 'apps carrying tag X', not a partition of the population [2]. Revenue figures exist for only 320 apps and are used as named anecdotes, not aggregates.
The numbers
| Stat | Computed from |
|---|---|
| 418 of 686 (61%) | bm_leaderboard: Subscription 418 / denominator 686 |
| 176 of 686 (26%) | bm_leaderboard: Advertising 176 / 686 |
| 124 of 686 (18%) | bm_leaderboard: Cross-subsidized Funnel 124 / 686 |
| 70 of 686 (10%) | bm_leaderboard: Marketplace/Transaction Fees 70 / 686 |
| 44 of 686 (6%) | bm_leaderboard: B2B Licensing 44 / 686 |
| 41 of 686 (6%) | bm_leaderboard: Financial Rails Revenue 41 / 686 |
| 39 of 686 (6%) | bm_leaderboard: Commerce Margin 39 / 686 |
| 36 of 686 (5%) | bm_leaderboard: IAP Consumables 36 / 686 |
| 28 of 686 (4%) | bm_leaderboard: One-Time Purchase 28 / 686 |
| 26 of 686 (4%) | bm_leaderboard: Creator Monetization Take Rate 26 / 686 |
| 1.64 models per app | bm_leaderboard note / bm_model_count_distribution: mean 1.64 |
Sources & citations
- [1] Lazyweb Research analysis of 686 attribute-tagged apps (~800-app tracked corpus), July 2026. business_model multi-valued tag prevalence; denominator = 686 apps with a business_model tag. ↩
- [2] Lazyweb Research analysis of 686 attribute-tagged apps (~800-app tracked corpus), July 2026. model-count distribution; mean 1.64 business models per app. ↩
Source: Lazyweb Research — proprietary analysis of real, in-market app screens. Cite as Lazyweb Research, 2026-07-07.