AI size recommendation helps a shopper choose a clothing size. Virtual try-on helps a shopper preview how clothing may look. Closku currently provides photo-based virtual try-on; automated size recommendation is not currently available.
A generated image does not establish body measurements, a size recommendation, or physical garment fit. Use the product's size chart, fit notes, and fabric information when deciding which size to order.
How size recommendation differs from a visual preview
| Experience | Shopper question | Information to check |
|---|---|---|
| Photo-based virtual try-on | How might this garment look on me? | Product and shopper images, preview fidelity, and appearance limitations. |
| Size recommendation | Which size should I consider? | Required shopper data, garment size information, validation, and uncertainty. |
| Size chart and fit notes | How do the listed dimensions and cut compare with what I need? | Whether values describe body or garment dimensions, units, and fit preferences. |
A size recommender needs an established basis for connecting shopper information to a garment's available sizes. The existence of a generated try-on image does not prove that such a process happened. Check the feature's actual output and supporting documentation rather than inferring a size from the preview.
What Closku provides today
Closku's storefront widget lets a shopper supply a photo and receive a generated clothing preview for a catalog garment. The current try-on result is an image. Closku does not currently offer an automated body-measurement or size recommendation output as part of this workflow.
Read how virtual try-on works for a labeled photo/garment/preview illustration. The simulated walkthrough shows the interface with prepared assets; it is not a sizing validation experiment.
Keep size information alongside try-on
- Keep a readable size chart on each relevant garment page.
- State whether chart values represent body dimensions or the physical garment.
- Provide measurement units, fit notes, fabric composition, and relevant stretch information.
- Explain any garment-specific fit differences rather than reusing one generic statement.
- Make merchant support and return information easy to find when a shopper is uncertain.
The visual preview can support an appearance decision while these details support size selection. Neither a generated image nor a generic label such as medium replaces the actual product information.
Questions to ask before adopting a sizing system
- Which shopper inputs and garment data does the system require?
- Does the output recommend an available size or report an estimated measurement?
- Which garment types, size ranges, and input conditions have been validated?
- What happens when required data is missing or confidence is low?
- How are photos and any derived information processed and retained?
- How does the advice relate to the merchant's size chart and the shopper's fit preference?
A future Closku sizing feature would need a documented workflow, validated inputs, outputs, and limitations before it is advertised as available. This page does not announce a launch date or a measured accuracy figure. For current product questions, contact the Closku team.
Start with current virtual try-on
Closku setup uses a CSV catalog and a storefront script, without live catalog sync or a marketplace app installation. Follow the Shopify guide, WooCommerce guide, or documentation, then compare current plans.
To evaluate purchases and completed returns, use the returns measurement guide. Store outcomes need real order data and a defined comparison method; a preview alone is not evidence of a guaranteed commercial result.
