Which Growth Tactics Do Companies Actually A/B Test the Most?

Across 4,814 before/after UI experiments Lazyweb Research detected (362 companies, 1,358 canonical screens), discount badges lead at 1,133 mentions, followed by CTA copy (561), trials (517), and urgency/countdowns (317) [1][2]. Price anchoring (279), social proof (120), pricing-tier removal (117), and free-plan removal (10) round out the tail [3]. These are experiments that *mention* each tactic, not a curated pure-tactic set.

Discount badges are the single most-touched tactic at 1,133 of 4,814 detected experiments (222 companies) — Lazyweb Research, July 2026.

Lazyweb Research · n=4814 · Published 2026-07-07

experimentsmonetizationpricingpaywallux-patterns

The tactic leaderboard

TacticExperimentsCompanies
Discount badges1,133222 [1]
CTA copy changes561201 [4]
Trials517140 [5]
Urgency / countdowns31797 [6]
Price anchoring279136 [3]
Social proof12062 [7]
Pricing-tier removal11783 [8]
Free-plan removal108 [9]

Discounts dominate both by experiment count and company reach [1].

Where the tests land on the page

By annotated change area, the hero is the most-tested surface (405 experiments), followed by offer (281), pricing (229), CTA (225), and value props (178) [10]. So even though discount and CTA copy lead by keyword, the hero is where the largest share of annotated experiments concentrate [10].

How to apply it

Use this as a prior on how mainstream a tactic is before you spend a test slot. Heavily-tested levers (discounts, CTA copy, trials) have deep precedent and named examples; thinly-tested ones (free-plan removal, n=10) mean you're closer to the frontier with less benchmark to lean on [9]. Pair the frequency read with retention: social proof and anchoring are almost never reversed once added, while trials churn most [11].

Caveats

Counts are experiments that *mention* a tactic via keyword tagging, which has precision limits ('%anchor%' overcounts, '%save %' inflates discounts) — read them as theme prevalence, not exact test counts [12]. Free-plan removal (n=10) is publishable as absolute counts only [9]. Learnings are LLM-inferred, not measured A/B lift.

The numbers

StatComputed from
discount badges 1,133 experiments, 222 companies (most-touched)tactic_mentions__discount_badges
4,814 detected experiments, 362 companies, 1,358 canonical screenstotal_detected_experiments; distinct_companies_in_experiment_corpus
price anchoring 279 experiments, 136 companiestactic_mentions__price_anchoring
CTA copy 561 experiments, 201 companiestactic_mentions__cta_copy
trials 517 experiments, 140 companiestactic_mentions__trial_length
urgency/countdown 317 experiments, 97 companiestactic_mentions__urgency_countdown
social proof 120 experiments, 62 companiestactic_mentions__social_proof
pricing-tier removal 117 experiments, 83 companiestactic_mentions__pricing_tier_removal
free-plan removal 10 experiments, 8 companies (absolute counts only)tactic_mentions__free_plan_removal; smallSampleWarnings
hero 405, offer 281, pricing 229, CTA 225, value props 178 (annotated areas)annotation_area_breakdown
social proof 100% and anchoring 98% retained; trial 85% (lowest)retention__social_proof; retention__price_anchoring; retention__trial
keyword tags have precision limits ('%anchor%', '%save %' overcount)smallSampleWarnings
Methodology. Universe: 4,814 detected before/after UI experiments (362 companies, 1,358 canonical screens); tactic counts are keyword mentions on what_changed+learning, area counts from LLM annotations, July 2026 pull. Counts reflect experiments that mention each tactic, not measured A/B results.

Sources & citations

  1. [1] Lazyweb Research analysis of 4,814 detected experiments (362 companies, 1,358 canonical screens), July 2026. Tactic counts are keyword mentions on what_changed+learning; distinct companies via control screenshot join.
  2. [2] Lazyweb Research analysis of experiment annotation areas (2,160+ annotated experiments), July 2026. Area counts are distinct experiments per annotated change area; LLM-derived, not measured outcomes.

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

Related questions

Explore the underlying screens, flows, and A/B tests inside Lazyweb. More research