A size recommendation on your product page.
Customers enter their usual size and how they like clothes to fit. Metr compares their answers with the item’s size chart, recommends a size and explains the expected fit.
Request accessEssential oversized tee
Heavyweight cotton, dropped shoulder. Sample size chart.
| Size | XS | S | M | L | XL |
|---|---|---|---|---|---|
| chest | 52 | 55 | 58 | 61 | 64 |
| length | 66 | 68 | 70 | 72 | 74 |
| shoulder | 46 | 48 | 50 | 52 | 54 |
- Shoulders
- Sits easy
- Chest
- Relaxed
- Length
- Regular
Example only: change the size and fit preference to see the guidance update. This demo uses a simplified rule, not a live AI recommendation.
Start with your chart.
Your brand supplies the product’s measurements for each size. Recommendations depend on that product’s approved size chart.
Ask about fit.
The customer shares their usual size and preferred fit. Some products may need additional body measurements.
Recommend a size.
Metr compares the customer’s inputs with the garment’s measurements to suggest a size for that product.
Explain the fit.
The customer sees how the size is expected to fit, such as relaxed at the chest or longer in length, before deciding to buy.
Help customers find
what to buy and in which size.
Request early access to Metr. We’ll review your product catalog, size charts and website to plan how search and size recommendations would work in your store.
Request access