# Which app categories run on word of mouth?

Source: Lazyweb Research
Author: Ali Abouelatta, Lazyweb Research
Published: 2026-07-09
Updated: July 2026
Sample size: n=599
Tags: gtm, strategy, word-of-mouth, category, referral
HTML: https://www.lazyweb.com/research/which-app-categories-run-on-word-of-mouth
Markdown: https://www.lazyweb.com/research/which-app-categories-run-on-word-of-mouth.md

**Answer.** Word of mouth is universal in three categories: 100% of tagged Education (28) and Utilities (23) companies cite it, and Health & Fitness is right behind at 97.7% of 44 [1]. Social Networking (90.0%) and Productivity (78.6%) also lean heavily on it [1]. The categories where WoM barely registers are transactional: Shopping (9.1%) and Travel (21.2%) [1]. Habit and identity products spread by referral; commerce products don't.

> Education and Utilities apps are 100% word-of-mouth-driven, and Health & Fitness 97.7% — July 2026.

## The finding: habit and identity products spread by mouth

Word of mouth concentrates in categories tied to routine, self-improvement, or social identity [1]. Education and Utilities hit 100%, Health & Fitness 97.7%, and Social Networking 90.0% — products people either recommend because they work daily, or because using them is inherently social [1]. Transactional categories where each purchase is private (Shopping 9.1%, Travel 21.2%) get almost no organic referral lift.

## The breakdown

Word-of-mouth share within each category (per-row N = category companies with a growth_engine) [1]:

| Category | N | Word-of-mouth % |
|---|---|---|
| Education | 28 | 100.0% |
| Utilities | 23 | 100.0% |
| Health & Fitness | 44 | 97.7% |
| Social Networking | 30 | 90.0% |
| Productivity | 42 | 78.6% |
| Sports | 20 | 55.0% |
| News | 45 | 48.9% |
| Lifestyle | 26 | 38.5% |
| Finance | 31 | 29.0% |
| Music | 22 | 27.3% |
| Travel | 33 | 21.2% |
| Shopping | 33 | 9.1% |

## How to apply it

In Education, Utilities, Health & Fitness, or Social, treat referral and shareability as a first-class growth engine — nearly every peer relies on it, so build invite loops, shareable results, and referral incentives into the core loop [1]. In Shopping and Travel, don't over-invest in referral programs; the category shows WoM is weak there and paid does the work instead [1]. WoM pairs naturally with PLG — the same categories top both lists.

## Caveats

Denominator is the 599 growth_engine-tagged companies grouped by category; per-row N is category companies with a growth_engine [1]. 'Word of mouth' here is a tagged growth engine, not a measured k-factor — it means the company relies on organic referral, not a specific viral coefficient. Multi-select field; smaller cells directional.

## The numbers

| Stat | Computed from |
| --- | --- |
| 100.0% of 28 | categoryMotionShares: Education wom_pct 100.0, n 28 |
| 100.0% of 23 | categoryMotionShares: Utilities wom_pct 100.0, n 23 |
| 97.7% of 44 | categoryMotionShares: Health & Fitness wom_pct 97.7, n 44 |
| 90.0% of 30 | categoryMotionShares: Social Networking wom_pct 90.0, n 30 |
| 9.1% of 33 | categoryMotionShares: Shopping wom_pct 9.1, n 33 |

## Methodology

Universe: the 599 growth_engine-tagged companies grouped by primary app category. Method: within-category word-of-mouth prevalence, July 2026. Caveat: WoM is a tagged growth engine (reliance on organic referral), not a measured viral coefficient; multi-select; small cells directional.

## Sources & citations

- [1] Lazyweb Research analysis of 599 companies, July 2026. categoryMotionShares: word-of-mouth share within each app category; per-row N = category companies with a growth_engine; denominator = 599.

## Related questions

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