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Which Apps Run The Most Experiments On Their Home Screen?

  • By Ali Abouelatta
  • n = 4,814
  • Published
  • Updated
  • 2 min read
  • landing-page · experiments · mobile · ux-patterns · design

Short answer

Across 4,814 detected experiments (July 2026), the home surface is the single most-experimented labeled screen category, with 562 distinct experiments — more than cancel-subscription (371) or any paywall category. source[1] DoorDash (at least 45 home), Crumbl (at least 39), and Apple Fitness (at least 32) lead the per-company home ranking. source[2]source[3]source[4] These are observed before/after variations with inferred rationale, not company-confirmed A/B tests.

The quotable stat
Home is the most-experimented screen category in the corpus at 562 distinct experiments (July 2026), led by DoorDash's 45+.

Bar chart · Home experiments (lower bound)

Home experiments (lower bound) — The finding

One block is about 1.6 Home experiments (lower bound)

DoorDash
45 [2]
Crumbl
39 [3]
Apple Fitness
32 [4]
Babbel
23 [5]
Etsy
20 [6]

The finding

The home surface leads all labeled screen categories with 562 distinct experiments, ahead of cancel-subscription (371), account-login (167), and sign-up (127). source[1] Per company, the most home-concentrated experimenters are DoorDash (at least 45), Crumbl (at least 39), and Apple Fitness (at least 32). source[2]source[3]source[4]

AppHome experiments (lower bound)
DoorDash45 source[2]
Crumbl39 source[3]
Apple Fitness32 source[4]
Babbel23 source[5]
Etsy20 source[6]

Why home dominates

The home screen is where merchandising, discovery, and personalization compete for attention, and it is served to every user on every session — so it is both the highest-traffic and highest-surface-area screen. Food and content apps (DoorDash, Crumbl, Apple Fitness) concentrate there because the rotating catalog is their product. Paywall-only apps like Tinder show zero home experiments by contrast.

How to apply it

If your app has a content-rich or catalog-driven home screen and you are not testing it, this data says you are ignoring the corpus's most-tested surface. Start with the merchandising order and personalization row logic — the levers DoorDash and Crumbl iterate. Reserve the paywall for a separate track. All figures are detected variations, not proven winners. source[1]

Caveats

The 562 count and per-company home splits are lower bounds because screen category is NULL on 1,425 of 4,814 experiments. source[7] All are observed variations with LLM-inferred rationale, not company-confirmed A/B tests — no lift is measured. source[1]

The numbers

#StatComputed from
[1]Home 562; cancel-subscription 371; account-login 167; sign-up 127top_experiment_screen_categories (home=562; cancel_subscription=371; account_login=167; sign_up=127)
[2]DoorDash at least 45 homecompany_total:doordash (home 45)
[3]Crumbl at least 39 homecompany_total:crumbl (home 39)
[4]Apple Fitness at least 32 homecompany_total:apple-fitness (home 32)
[5]Babbel at least 23 homecompany_total:babbel (home 23)
[6]Etsy at least 20 homecompany_total:etsy (home 20)
[7]1,425 of 4,814 experiments have no screen categoryscreen_category_null_on_experiments (1425/4814)

Methodology

Universe: 4,814 detected experiments across 276 companies, July 2026; screen categories from screen_category join. Method: COUNT(DISTINCT experiment_id) by category and by company. Caveat: home splits are lower bounds (1,425 experiments unlabeled); detected variations only, never confirmed A/B tests.

Sources

  1. [1]

    Lazyweb Research analysis of 4,814 detected experiments (276 companies, ~800-app mobile corpus), July 2026

    Top labeled screen categories by COUNT(DISTINCT experiment_id); home=562.

    Back to text

  2. [2]

    Lazyweb Research analysis of 221 detected experiments (DoorDash, ~800-app mobile corpus), July 2026

    home split from screen_category='home'.

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  3. [3]

    Lazyweb Research analysis of 43 detected experiments (Crumbl, ~800-app mobile corpus), July 2026

    home split from screen_category='home'.

    Back to text

  4. [4]

    Lazyweb Research analysis of 38 detected experiments (Apple Fitness, ~800-app mobile corpus), July 2026

    home split from screen_category='home'.

    Back to text

  5. [5]

    Lazyweb Research analysis of 66 detected experiments (Babbel, ~800-app mobile corpus), July 2026

    home split from screen_category='home'.

    Back to text

  6. [6]

    Lazyweb Research analysis of 32 detected experiments (Etsy, ~800-app mobile corpus), July 2026

    home split from screen_category='home'.

    Back to text

  7. [7]

    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.

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Source: Lazyweb Research — proprietary analysis of real, in-market app screens. Cite as Lazyweb Research, 2026-07-07.