INSTALL CONVERSION

Screenshots

Scores every screenshot and the full set across clarity, coverage, consistency, message diversity, and metadata alignment, with each frame classified by value-prop message type.

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Moves conversionConversion

What's distinctive.

1

A conversion asset, not art.

Screenshots are scored as a conversion asset, not a design deliverable. Per-frame scoring catches feature-led and aesthetic-only frames that should be outcome-led, because outcome-led frames are what turn product-page views into installs.

2

The set works as a story.

Set-level scoring catches inconsistent visual style, redundant messages, and image-text mismatches where the overlay claims one thing and the UI shows another. The full set is graded on whether it reads as a connected story.

3

First three frames weigh more.

The first three frames carry extra weight because they are what users actually see in the store card. A weak opening sequence is scored as a conversion problem, not a cosmetic one.

The methodology.

"The first screens have to show the why, not just the what."
  1. 1

    Score each frame across six buckets

    Every frame is classified by value-prop message type, then scored against the bucket it claims to occupy:

    • Tangible benefit: a concrete outcome the user gets.
    • Use-case fit: the situation the app is built for.
    • Trust or proof: credibility signals that reduce hesitation.
    • Social proof or identity: who else uses it and who it is for.
    • Emotional payoff: how using the app feels.
    • Experience promise: what the product experience will be like.
  2. 2

    Score the set as a whole

    Set-level scoring covers visual-style consistency, message-type diversity, image-text alignment (does the overlay claim match what the UI actually shows), and the weighting on the first three positions.

  3. 3

    Check image-text alignment

    Vision models read each frame and its overlay text, then compare the claim the caption makes against what the interface in the frame actually demonstrates. A high overlay claim on a screen that does not show it scores low.

  4. 4

    Ranked, explainable edits

    Findings convert to specific edit recommendations with the signal that triggered each one, the data sources it pulled from, and the expected score delta.

Data sources

Live screenshot assets from the App Store and Google Play; OCR text extraction; vision-model analysis of each frame; app metadata (title, subtitle, description) for cross-asset alignment; competitor screenshot benchmark.

AI's role

Vision models classify message type, evaluate image-text alignment, and extract the dominant message from each frame. The six value-prop buckets, the priority weighting on the first three positions, and the scoring rubric are the human-authored framework.

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.

Screenshots
+9 on the Screenshot score.

Replace your second screenshot (currently a feature-list overlay on the settings screen) with an outcome-led frame showing the workout timer in use with a '+15 min PR this week' overlay.

Why
Frame 2 is feature-led with a low image-text alignment score, you have zero outcome-led frames in positions 1 through 3, and competitors in the top three of the category all lead with outcomes.
Sources
Live screenshot OCR and visual classification, competitor screenshot benchmark, listing metadata themes.
Expected impact
+9 on the Screenshot score.
Example

What you get.

  • Per-frame score with bucket classification and an image-text alignment metric.
  • Set-level score across coverage, diversity, consistency, and first-three-position quality.
  • Specific edit recommendations, such as replacing a frame with an outcome-led story, each with an expected score delta.

How you act on it.

  • Approve, edit, or decline each recommendation in the Weekly Revision Plan.
  • On Pro and above, generate alternative screenshot drafts via Content Generation.
  • On Elite, produce full visual generation in your brand style and Publish the approved set.

Free and Basic include analysis only. Pro, Elite, and Enterprise add draft generation and Publishing.

See plans →

Related.

The cross-engine methodologySister engine: IconPairs with: Store TextPairs with: User Sentiment

See whether your screenshots convert.

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

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