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What Are Companies A/B Testing on Value Props and Feature Lists?

  • By Ali Abouelatta
  • n = 276
  • Published
  • Updated
  • 2 min read
  • paywall · monetization · ux-patterns · experiments · mobile · upsell
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Short answer

Value props — benefit bullets and feature lists — is the fourth most-tested area: 276 of 2,160 annotations (13.1%) across 254 experiments Lazyweb Research observed by July 2026. It is heavily tested (194 mobile / 82 web) but rarely flagged as high-leverage: average model impact is 3.03/5 and only 15.6% of tests score 4+/5, the second-lowest of major areas. Observed moves focus on quantifying entitlements and dropping tier comparisons. source[1]

The quotable stat
Value props is the 4th most-tested area (276 of 2,160 annotations, 13.1%) but among the lowest-impact — only 15.6% of its tests score 4+/5 — Lazyweb Research, July 2026.

Bar chart · Value

Value — How much, and where

One block is about 9.1%

Annotations
276 (13.1% of 2,160)
Distinct experiments
254
Mobile / web split
194 / 82
Avg impact (1–5)
3.03
Share scored 4+/5
15.6% (43/276)

How much, and where

Value-props testing at a glance (VALUE PROPS merged with VALUE PROPS/FEATURES): source[2]

MetricValue
Annotations276 (13.1% of 2,160)
Distinct experiments254
Mobile / web split194 / 82
Avg impact (1–5)3.03
Share scored 4+/515.6% (43/276)

Teams test value props often, but the model rarely rates the change high-impact — a heavily-iterated, modestly-scored surface. source[3]

Observed patterns

From value-props experiments Lazyweb Research scored impact 4: source[4]

  • Quantify the entitlement. Canva rewrote benefit bullets from capability framing ('what you can do') to concrete numbers ('100 million+ premium photos', '1 TB storage'), turning vague promises into inventory and scale cues.
  • Drop the tier comparison. Geocaching replaced a Basic-vs-Premium checklist with a Premium-only, icon-led benefit list — reframing the decision from 'compare tiers' to 'do I want these outcomes,' and avoiding a reminder of what's already free.

The recurring move: make benefits concrete and stop inviting a comparison. source[4]

How to apply it and caveats

If you test value props, the field's stronger plays are quantifying entitlements (numbers, not adjectives) and removing side-by-side tier comparisons that anchor users on the free plan. But temper expectations: value-props changes are frequently tested yet seldom high-impact (15.6% scored 4+), so treat them as supporting moves behind offer and pricing rather than headline bets. Caveat: impact is a relative model score on observed diffs, not measured lift. source[5] Named examples are single observations scored 4/5.

Real in-market screens

Screens from real, in-market apps, tracked by Lazyweb Research.

  • Fubo plan-paywall screen — real in-market example tracked by Lazyweb Research
    Fubo1206 × 2622opens the full image
  • Apartmentscom Account Setup screen — real in-market example tracked by Lazyweb Research
    Apartmentscom1206 × 2622opens the full image
  • Gauth paywall screen — real in-market example tracked by Lazyweb Research
    Gauth1206 × 2622opens the full image
  • Stupido Onboarding screen — real in-market example tracked by Lazyweb Research
    Stupido1206 × 2622opens the full image

The numbers

#StatComputed from
[1]Value props 276 annotations (13.1%), 254 experiments, 194 mobile / 82 web, avg impact 3.03, 15.6% scored 4+statpack area_VALUE_PROPS + high_impact_share_by_area
[2]Value props (merged): 276 annotations, 254 experiments, avg impact 3.03, 43/276 scored 4+statpack area_VALUE_PROPS + high_impact_share_by_area
[3]Value props: 194 mobile / 82 web; 15.6% scored 4+ (second-lowest of major areas)statpack area_VALUE_PROPS + high_impact_share_by_area
[4]Value-props impact-4 examples: Canva (quantified entitlements), Geocaching (dropped tier comparison)statpack qualitative VALUE PROPS entries
[5]Impact is a relative model score on observed diffs, not measured liftstatpack methodology note

Methodology

Universe: 276 value-props annotations (merged variants) across 254 detected experiments (subset of 2,160), July 2026, LLM-labelled and impact-scored from paired screenshots. Named companies are single observations; impact is relative signal, not measured lift.

Sources

  1. [1]

    Lazyweb Research analysis of 276 value-props annotations (254 experiments) within 2,160 total, July 2026

    VALUE PROPS merged with VALUE PROPS/FEATURES; 194 mobile / 82 web.

    Back to text

  2. [2]

    Lazyweb Research analysis of 276 value-props annotations, July 2026

    43 of 276 scored 4+/5; avg impact 3.03.

    Back to text

  3. [3]

    Lazyweb Research analysis of 2,160 area annotations, July 2026

    Value props has the second-lowest 4+ share of the major areas.

    Back to text

  4. [4]

    Lazyweb Research qualitative review of value-props experiments, July 2026

    Canva and Geocaching — single observations scored impact 4 by the model.

    Back to text

  5. [5]

    Lazyweb Research methodology note, July 2026

    Impact is a relative model score on before/after diffs, not measured lift.

    Back to text

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

Explore the evidence

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