Creative performance scoring

Two banners that differ by ten percent in detail can differ by three hundred percent in conversion, and nobody can tell which is which by looking. The system reads your own ad library against its performance data, finds the visual patterns that actually correlate with results, and scores a new creative before any budget moves.

How it works

You giveYour historical ad library with the numbers attached: impressions, click-through, and ROMI per creative.

The system doesThe analysis. It decomposes each creative into measurable visual features — colour zones, text placement, focal point, contrast ratios, compositional structure — and works out which combinations consistently sit behind your high-converting ads.

You stay in controlOver what the model is allowed to conclude. You decide which campaigns and date ranges count as training data, how a score translates into a go or no-go, and whether a pattern it found is a real effect or an artefact of one unusual quarter.

You getA predicted score per creative before launch, a ranked batch instead of a pile, and a pattern library your designers and generation tools can brief from.

Inside the system

06 components

Creative corpus ingestion

Your historical ad library loads in with its performance data attached: impressions, click-through, ROMI per creative. The corpus is yours, which is what makes the result specific to your audience.

Visual feature extraction

Each creative is decomposed into granular, measurable elements: colour zones, text placement, focal point, contrast ratios, compositional structure. These are the differences a person registers as roughly the same banner.

Performance correlation

A statistical model works out which visual features consistently correlate with high-conversion outcomes, and which ones the team believed in without evidence.

Pattern library

The feature combinations that perform get written out in structured form, usable directly as a creative brief or as a generation prompt.

Pre-launch scoring

A new creative is scored against the model before any spend, and a batch comes back ranked by predicted performance instead of arriving as an undifferentiated pile.

Brief-to-output loop

Designers and generation tools receive scored briefs, so production starts from a direction instead of arriving at one after three rounds of revision.

Who it's for

Good fit

Performance marketing teams running paid social at volume

Advertisers with a year or more of creative performance history

Agencies managing creative budgets across several clients

E-commerce and apps testing many creative angles each month

Not a fit

Teams with no historical performance data to train on

Brands running a handful of creatives a year

Channels where results are driven by targeting rather than by the creative

What you can configure

What counts as a winThe outcome the model optimises for: click-through, ROMI, install, or your own blended metric.

Which history it learns fromCampaigns, channels, and date ranges are included or excluded, so a seasonal anomaly does not quietly become a rule.

Where the score gates productionA score can be a note in a brief, a ranking across a batch, or a threshold a creative has to clear before it gets budget.

Who acts on itDesigners, media buyers, or a generation pipeline. The pattern library reads as a brief either way.

What we need from you

Your ad libraryThe creatives themselves, as many as you have. This is the dataset.

Performance dataImpressions, click-through, and ROMI joined to the right creative.

Your success metricWhat a winning creative means for your business, stated precisely enough for a model to optimise against it.

One marketerSomeone who can say whether a predicted winner looks plausible, a few hours a week during the build.

Example use cases

Knowing which banner will win before paying for the test

A performance team saw near-identical banners convert up to 300% apart and learned which one won only after the test budget was spent. An AI model trained on its past ads now scores every creative before launch, which cuts testing spend by 15%.

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Find out which creative wins while it is still free to be wrong.

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