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Customers scan your grid in seconds. When one product fills the frame and the next floats in white space, the page looks unmanaged — and they leave. This tool finds every inconsistency before your customers do.
Product photography is expensive. You already paid for the shoot, the retouching, and the upload. The problem is usually not any single image — it is the variation across the set. A catalog of eight near-identical frames looks more trustworthy than a catalog of eight excellent but visually unrelated images [citation:6].
This checker runs four independent measurements against every image you upload. You set the target rules, and it tells you which images pass and which break the rhythm.
Are all images the same pixel size? A 1000×1000 image next to a 1200×800 image forces your grid to stretch, crop, or letterbox. Marketplaces like Amazon require at least 1000px on the longest side, and Google recommends 1500×1500 for rich product displays [citation:19][citation:25].
Is the background actually white, or just close? Amazon requires pure white at RGB 255,255,255 on main images. A background that reads 250,250,250 looks gray next to a true-white listing and can trigger automated suppression [citation:31]. This checker samples border pixels and reports the purity percentage.
How much breathing room sits between the product and the canvas edge? One product with 5% padding and another with 20% makes the grid feel unstable even if both backgrounds are white. Marketplace guidance suggests products occupy roughly 70 to 85 percent of the frame for square thumbnails [citation:1].
Does every product fill a similar share of the frame? Amazon’s 85% fill rule catches more sellers than any other requirement — a product that looks centered in an editor often fills only 60–70% when measured precisely [citation:28]. This check flags outliers before a marketplace does.
Shoppers do not read your catalog one product at a time. They compare. They open a category page, scan ten thumbnails, and decide in under three seconds whether the store looks credible. Baymard Institute research shows 56% of shoppers look at the image first, before price or reviews [citation:20]. When those images disagree with each other about scale and framing, the visual noise reads as carelessness.
The commercial damage compounds. An image that fails Amazon’s 85% fill rule can suppress the listing from search entirely — no impressions, no clicks, no sales — and Amazon’s automated system often does not tell you why [citation:28]. An image with a near-white background rather than pure white can trigger the same result. Checking consistency before you upload is cheaper than discovering it after your traffic disappears.
Pro tip: Review your catalog on a mid-grey background, not white. Light halos around cutout edges are invisible against a white page but obvious on grey — and grey is closer to how many marketplace grids actually render your images [citation:6].
Different platforms enforce different standards. Use the settings panel to match your destination, then run the same check across your whole batch.
| Rule | Amazon Main Image | Google Merchant Center | General Web Catalog |
|---|---|---|---|
| Canvas size | 1000px+ longest side (1600 recommended) [citation:25] | 500×500 minimum; 1500×1500 recommended [citation:19] | 1000×1000 or larger |
| Background | Pure white RGB 255,255,255 [citation:31] | White or light recommended | White or consistent brand color |
| Subject fill | At least 85% of frame [citation:28] | No hard minimum | 70–85% for square thumbnails [citation:1] |
| Padding | Minimal — product nearly touches edge | Minimal | Consistent across the catalog |
This checker diagnoses and reports. It does not edit your images. Once you see which products fail, you fix them with the right tool for the job:
The checker samples pixels along all four edges of each image and calculates the percentage that fall within your tolerance of pure white. If you set tolerance to 5, a pixel at RGB 250,250,250 counts as white; a pixel at 240,240,240 does not. This catches the most common failure: a background that looks white on your monitor but reads as gray to a marketplace’s automated audit [citation:31].
The tool scans for pixels that differ from the dominant background color, builds a bounding box around them, and reports the box area as a percentage of the full canvas. This is an approximation — it does not separate a shadow from the product — but it reliably flags images where one product fills 90% of the frame and the next fills 60%.
Run the checker once per target. Set your rules to Amazon’s spec, run the batch, note the failures. Then change the rules to Google’s spec and run again. The same image set can pass one channel and fail another — that is normal and expected.
No. Every measurement runs in your browser using the Canvas API. The images never leave your device. You can disconnect from the internet after the page loads and still audit your files.
That usually means your master export workflow has a systematic problem — for example, every image was resized to a different width, or every background was shot on an unlit sweep that photographed as light gray [citation:31]. Fix the workflow once, re-export the batch, and re-run the checker. Do not fix images one at a time if the root cause affects the whole set.
Upload your product images, set your marketplace rules, and get a visual consistency report in seconds. No uploads, no signup, no server.
Start CheckingFor platform-specific image requirements, consult the official sources: Google Merchant Center image_link guidelines, Amazon Seller Central product image requirements, and Baymard Institute ecommerce usability research. For catalog workflow guidance, the marketplace photo consistency audit guide covers crop rules and shadow handling in depth.