What Is Adobe A/B Testing On Its App Home Surface?
Lazyweb Research detected 38 distinct experiments at Adobe (July 2026), split across home (at least 18) and paywall (at least 7), with 3 detected in 2026. [1] Adobe's detected iteration leans toward the home/workspace surface, with a secondary paywall footprint. These are observed before/after variations with inferred rationale, not company-confirmed A/B tests.
Lazyweb Research detected 38 Adobe experiments (July 2026), at least 18 on home and 7 on the paywall.
The finding
Lazyweb Research detected 38 distinct experiments at Adobe, with at least 18 on the home surface and at least 7 on the paywall. [1] Adobe iterates its in-app workspace/home more than its paywall — a pattern for a creative-tools subscription where activation on the core canvas drives retention more than any single upgrade screen.
How to apply it
Adobe's home-heavy split (18 home vs. 7 paywall) is the benchmark for a creative-tools subscription: the workspace where users produce work is the primary test surface, with the paywall secondary. If your creative app over-invests in paywall testing, Adobe is evidence the activation surface may deserve more. Three experiments were detected in 2026. [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 |
|---|---|
| 38 distinct experiments; at least 18 home, at least 7 paywall | company_total:adobe (value 38; home 18, paywall 7, in-2026 3) |
| 1,425 of 4,814 experiments have no screen category | screen_category_null_on_experiments (1425/4814) |
Sources & citations
- [1] Lazyweb Research analysis of 38 detected experiments (Adobe, ~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.