INSTALL CONVERSION

Icon

Scores your app icon across functional clarity, accessibility at thumbnail size, category-aligned color psychology, consistency with your screenshot set, and competitive distinctiveness.

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Moves conversionConversion

What's distinctive.

1

Measured, not eyeballed.

Deterministic computer vision supplies the measurable inputs: medallion ratio, edge density, contrast against accessibility standards, RGB distance from competitor icons, so the legibility and distinctiveness scores rest on numbers, not taste.

2

Scored against your real grid.

Competitive distinctiveness is measured against the same ten competitors the audit benchmarks everywhere else, so the icon score reflects the store grid your icon actually shows up in, not a generic style guide.

3

The first tap, earned.

A clear, distinctive, legible icon is the first thing that earns a tap in the store grid, moving the conversion half of organic install growth where installs equal visibility times conversion.

The methodology.

"The icon is the first thing that earns a tap in the store grid."
  1. 1

    Functional alignment

    Vision models classify whether the icon's visual metaphor matches the app's actual purpose.

  2. 2

    Visual-text consistency

    The engine checks whether the icon's tone matches the listing text and the screenshot set, so the asset reads as one coherent presentation.

  3. 3

    Accessibility and legibility at small sizes

    Deterministic image processing measures legibility at thumbnail resolution:

    • Contrast against accessibility standards.
    • Medallion ratio: how the mark sits within the icon frame.
    • Edge density at thumbnail resolution.
  4. 4

    Competitive distinctiveness

    RGB distance and visual-uniqueness scoring run against the ten competitors from Competitor Discovery, with a category-color reference for what is expected versus what stands out.

Data sources

Live icon image; listing text and screenshot set (for cross-asset consistency); competitor icons from Competitor Discovery; category-color expectation tables.

AI's role

Vision models classify metaphor, tone, rendering style, and visual distinctiveness. Deterministic image processing supplies the measurable inputs: contrast, ratios, distance metrics. The four-layer rubric is the framework and is human-authored.

A real recommendation, end to end.

This is the shape of a recommendation row in the Weekly Revision Plan. The reasoning, the sources, and the projected impact are part of the row — not buried in a tooltip.

Icon
+7 on the Icon score.

Shift the icon's dominant color away from light blue: three of your top competitors share the same hue.

Why
Your dominant color sits within 12% RGB distance of three peer icons in your category, sinking the color-uniqueness component of the distinctiveness score; the category-color expectation table suggests deep teal or violet would still align with finance norms while standing apart.
Sources
Icon image, competitor icons from Competitor Discovery, category-color reference tables.
Expected impact
+7 on the Icon score.
Example

What you get.

  • Icon score with metaphor, consistency, accessibility, and distinctiveness components.
  • Specific recommendations with expected score delta.
  • Before and after view: current icon vs. recommended variant.
  • A/B variant suggestions: alternate icons to test against the current one.

How you act on it.

  • Approve, edit, or decline each recommendation in the Weekly Revision Plan.
  • On Pro and above, generate text-only or stylistic icon variants via Content Generation.
  • On Elite, generate full visual variants in your brand style.
  • A/B testing pairs with App Store Connect and Play Console store-experiment integration when connected.

Free and Basic include analysis only; Pro adds text-variant generation; Elite adds full visual generation.

See plans

See whether your icon earns the tap.

Paste any App Store or Google Play URL. Free to start, no credit card required.

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