# Is one revenue stream the norm, or do apps stack multiple business models?

Source: Lazyweb Research
Published: 2026-07-07
Sample size: n=686
Tags: monetization, pricing, saas, upsell
HTML: https://www.lazyweb.com/research/is-one-revenue-stream-the-norm-mono-vs-multi-model
Markdown: https://www.lazyweb.com/research/is-one-revenue-stream-the-norm-mono-vs-multi-model.md

**Answer.** One stream is the plurality but not the majority: 394 of 686 tagged apps (57%) are mono-model, while 292 (43%) carry two or more revenue models [1]. The mean is 1.64 models per app, driven by 239 two-model apps, 44 three-model, and 9 four-model [1]. If you are deciding whether to add a second revenue stream, note that nearly half of tracked apps already run more than one.

> 394 of 686 tagged apps (57%) run a single revenue model; 43% stack two or more — July 2026.

## The model-count distribution

How many business models a company carries [1]:

| Models carried | Apps | Share |
|---|---|---|
| 1 | 394 | 57% |
| 2 | 239 | 35% |
| 3 | 44 | 6% |
| 4 | 9 | 1% |

Mean 1.64 models per app. The most common multi-model pattern is a primary subscription paired with a secondary stream — advertising, a cross-subsidized funnel, or a marketplace fee.

## How to apply it

Shipping a single, clear revenue model is the modal choice and a defensible default — most tracked apps do it [1]. Stacking a second model is common (43% of apps) but not required to look 'normal.' Market leaders and challengers carry a near-identical average number of models (1.64 vs 1.62), so adding streams is not what separates leaders — they monetize about as simply as everyone else [2].

## Caveats

Denominator is the 686 business-model-tagged apps [1]. 'Mono-model' means one tagged model in the corpus, not necessarily one price point. The leader-vs-challenger model-count comparison excludes the 222 'Unknown' and 14 null market_leader rows [2].

## The numbers

| Stat | Computed from |
| --- | --- |
| 394 of 686 (57%) | bm_model_count_distribution: 1_model 394 / 686 |
| 292 of 686 (43%) | bm_model_count_distribution: 239+44+9 = 292 / 686 |
| 239 apps | bm_model_count_distribution: 2_models 239 |
| 44 apps | bm_model_count_distribution: 3_models 44 |
| 9 apps | bm_model_count_distribution: 4_models 9 |
| 1.64 models per app | bm_model_count_distribution note: mean 1.64 |
| 1.64 (leaders) vs 1.62 (challengers) | market_leader_vs_rest_bm: avg_bm_count Yes 1.64, No 1.62 |

## Methodology

Universe: the 686 business-model-tagged apps in Lazyweb's ~800-app tracked corpus, July 2026 pull. Method: distribution of array_length(business_model). Caveat: leader comparison excludes 222 Unknown and 14 null market_leader rows.

## Sources & citations

- [1] Lazyweb Research analysis of 686 attribute-tagged apps (~800-app tracked corpus), July 2026. business-model count distribution; mean 1.64 models per app.
- [2] Lazyweb Research analysis of 450 leader/challenger apps (~800-app tracked corpus), July 2026. avg model count for market_leader Yes (284) vs No (166); Unknown/null excluded.

## Related questions

- [How do tracked apps actually make money — subscription, ads, or transactions?](https://www.lazyweb.com/research/how-do-tracked-apps-make-money-subscription-ads-transactions)
- [Do market leaders monetize differently than challengers?](https://www.lazyweb.com/research/do-market-leaders-monetize-differently-than-challengers)