We read the public product data of 88 Australian fashion stores and counted the things that quietly cost money. Here is the whole result, including the parts that are less dramatic than they sound.
Scanned August 2026. No store is named. Method at the bottom.
Median store health score. The full range was 74 to 99, so the spread is wide. Median catalogue size was 1,210 products; the largest was 2,000.
Percentage of the 88 stores with at least one instance.
The percentage tells you how widespread something is. The median count tells you how bad it is at a store that has it, which is usually the more useful number.
| Problem | Stores affected | Median count, affected stores |
|---|---|---|
| Products with fewer than 2 images | 97% | 28 |
| Products live but completely sold out | 94% | 96 |
| Product images with no alt text | 94% | 50 |
| Products with descriptions under 200 characters | 89% | 131 |
| Products sharing a title with another product | 61% | 24 |
| Variants with no SKU | 59% | 8 |
| Products whose 'was' price is BELOW the current price | 26% | 5 |
| Sampled pages with no meta description | 10% | 4 |
| Sampled pages with no Product structured data | 9% | 5 |
This is the comparison that made the whole exercise worth doing. Median catalogue size is 48 products for a roaster and 1,210 for a fashion brand, and almost every difference below follows from that one gap.
| Problem | Coffee (152 stores) | Fashion (88 stores) |
|---|---|---|
| Products live but completely sold out | 73% (median 7) | 94% (median 96) |
| Products sharing a title with another product | 21% (median 5) | 61% (median 24) |
| Products with descriptions under 200 characters | 87% (median 8) | 89% (median 131) |
| Product images with no alt text | 88% (median 20) | 94% (median 50) |
| Products with fewer than 2 images | 93% (median 18) | 97% (median 28) |
| Variants with no SKU | 89% (median 20) | 59% (median 8) |
| Products whose 'was' price is BELOW the current price | 28% (median 2) | 26% (median 5) |
Note that fashion stores score higher overall (89 vs 85) despite far bigger absolute problems, because the score is rate based. 96 dead products out of 1,210 is a smaller share than 7 out of 48. Whether that is the right way to score it is a fair argument to have.
Scan your own store against this data Paste your address, get your numbers in about five seconds. No app install, no login to your store.Every Shopify store serves its full catalogue at /products.json,
publicly, with no key and no login. We read that, plus a small sample of product
pages, at one request per second with an identifying user agent. Nothing behind a
login, no orders, no customer data, no traffic figures.
Two honest caveats. Catalogues were capped at 2,000 products, so a handful of counts are floors rather than totals. And roughly one store in ten disables the public feed, so those are missing from the sample entirely.