What Is Zero A/B Testing On Its Fasting-App Paywall?
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) |
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. ↩
Source: Lazyweb Research — proprietary analysis of real, in-market app screens. Cite as Lazyweb Research, 2026-07-07.