Discover tips, tutorials, and insights about AI-powered fashion photography, e-commerce optimization, and virtual try-on technology.
The image rules nine platforms publish for product photos, in one place: minimum and recommended sizes, file formats and limits, what the main photo may show and what each asks of AI-made images. Every row links the official page, read on 18 October 2026.
13 min read
The numbers behind virtual try-on in 2026, each read on its publisher's own page: three market estimates that disagree, a Google and Ipsos shopper survey, US return rates from NRF and what Zalando's pilots did to returns.
12 min read
Eight AI tools that make product photos for clothing brands: on-model photos, ghost mannequin shots, team seats, the price of one photo and who owns the images, read from each vendor's own pages.
14 min read
Ten tools turn a flat lay, hanger or mannequin photo into a photo of the garment on a model. What each accepts, what one photo costs, what the free start allows and who owns the result, read from each vendor's own pages.
14 min read
Every marketplace shows your image smaller than you made it, until a shopper zooms. That zoom is the only place the difference between 2K and 4K exists, and it is a real place. When 4K earns its cost, when 2K is the right call, and how to tell real detail from an upscaler's guesswork.
8 min read
A listing image has one job; a campaign image has a placement, a format, a date and a message, and a dozen siblings. How to make the campaign set with AI from the masters you already have — product kept, scene generated, per-placement crops — and where the line runs between a creative scene and a claim the product cannot keep.
9 min read
For a modest fashion customer the image answers questions other categories never ask: how long is the sleeve on a body, where does the hem fall, is the fabric opaque in daylight, does the set layer the way it should. A method for producing those images with AI from the garment's own pixels, and for checking coverage rather than admiring the picture.
8 min read
Automation on Shopify is not a button that photographs your catalogue; it is a pipeline with one photograph per product going in and a named, sized, reviewed image set coming out. The stages, what can run unattended, what must not, and how the set lands in Shopify without hand-uploading each file.
8 min read
A customer buying jewelry online is buying the image, and compares it to the piece in the box under a lamp. A checklist for reviewing generated jewelry images before they go live: stones, metal, settings, chains, clasps, hallmarks and scale, each checked against the photograph rather than judged by eye.
9 min read
A reviewer who can name a failure can fix it; one who can only say "it looks off" regenerates at random. Five classes of failure in AI product photography, what each one looks like at full size, what causes it, and which step of the workflow fixes it.
12 min read
A label is the part of a product a customer can read, and the part a model reads worst. Small type becomes type-shaped marks, numbers drift, a logo rounds off. A method for products with fine text: photograph the label as a document, keep its pixels, and read it character by character before publishing.
8 min read
