# What Is Zero A/B Testing On Its Fasting-App Paywall?

Source: Lazyweb Research
Published: 2026-07-07
Sample size: n=68
Tags: paywall, retention, monetization, experiments, mobile, saas
HTML: https://www.lazyweb.com/research/zero-fasting-app-paywall-experiments
Markdown: https://www.lazyweb.com/research/zero-fasting-app-paywall-experiments.md

**Answer.** Lazyweb Research detected 68 distinct experiments at Zero (July 2026), a top-10 company total in the corpus, with a detected paywall footprint of at least 9 and a small signup footprint of at least 2. [1] Zero is one of the highest-volume health/fasting apps tracked, and its detected iteration is spread across surfaces rather than concentrated on the paywall. These are observed before/after variations with inferred rationale, not company-confirmed A/B tests.

> Lazyweb Research detected 68 Zero experiments (July 2026), a top-10 company total across the 276-app corpus.

## The finding

Lazyweb Research detected **68 distinct experiments** at Zero, placing it among the ten most-experimented apps in the corpus. [1] The detected surface mix is diffuse — at least 9 paywall and at least 2 signup experiments — with the remainder spread across unlabeled surfaces. For a fasting/health app, this volume signals a continuous iteration culture rather than a one-off redesign.

## How to apply it

For a fasting app benchmarking its own cadence, Zero's 68-experiment volume is a reference point: it sits alongside Blinkist (70) and Grammarly (67) at the top of the corpus. Use it to argue that sustained, multi-surface iteration — not a single big redesign — is the norm among the most-tracked apps. Because only 2 of Zero's experiments were detected in 2026, treat this as a cumulative-volume signal, not a current-year one. [1]

## Caveats

All figures are observed variations with LLM-inferred rationale, not company-confirmed A/B tests — no lift is measured. [1] Surface splits are lower bounds because screen category is unlabeled on 1,425 of 4,814 corpus experiments. [cat_null]

## The numbers

| Stat | Computed from |
| --- | --- |
| 68 distinct experiments; at least 9 paywall, at least 2 signup | company_total:zero (value 68; paywall 9, signup 2, in-2026 2) |
| 1,425 of 4,814 experiments have no screen category | screen_category_null_on_experiments (1425/4814) |

## Methodology

Universe: 68 distinct Zero experiments (COUNT(DISTINCT experiment_id)) within 4,814 detected before/after UI diffs across 276 companies, July 2026. Extraction: LLM-inferred rationale on observed variations. Caveat: detected variations only, never company-confirmed A/B tests.

## Sources & citations

- [1] Lazyweb Research analysis of 68 detected experiments (Zero, ~800-app mobile corpus), July 2026. COUNT(DISTINCT experiment_id) on before/after diffs; surface splits from is_paywall + screen_category.
- [cat_null] Lazyweb Research analysis of 4,814 detected experiments (276 companies, ~800-app mobile corpus), July 2026. screen_category is NULL on 1,425 experiments, so all surface splits are lower bounds.

## Related questions

- [What Is BetterMe A/B Testing On Signup And Paywall?](https://www.lazyweb.com/research/betterme-signup-paywall-experiments)
- [Which Apps Run The Most Detected UI Experiments Overall?](https://www.lazyweb.com/research/which-apps-run-the-most-experiments-overall)