FitMatch widget

Translate your size from one brand to another.

This is the product surface we want to test: a lightweight sizing widget that turns a known size at one brand into a recommendation for another brand. The surrounding intelligence layer sits behind it.

Try the widget See the sizing layer Open product mockup

Embed-ready widget

This is the compact frontend we want to ship into a product page or retailer widget slot.

Primary surface

FitMatch size translator

Known size in one brand, recommendation in another brand. Minimal input, immediate value.

Brand to brand Fast flow Low friction

Translate size

Choose the brand and size you already know, then translate it to a target brand.

Recommendation

Translation result

Select two brands to see how the same size translates.

Why this is useful

It reduces guesswork, multi-size orders, and sizing frustration for shoppers.

What we validate

Whether a simple brand-to-brand recommendation is useful enough to keep using.

What the widget sits on top of

The widget is the frontend. Behind it is a lightweight sizing intelligence layer that stores charts, normalizes them, and translates between brands.

Dataset: public brand size charts and product attributes
Logic: normalization and translation between brands
Future: user feedback to refine fit profiles

Why the business cares

For shoppers

Less guessing, fewer size-related surprises, and a faster path to checkout.

For retailers

Lower return pressure, fewer abandoned carts, and better conversion on sizing-sensitive products.

For FitMatch

A narrow, testable wedge: one clear output that can validate product demand.

Sizing intelligence layer

The widget uses a small dataset, but the underlying structure is designed to scale.

Normalized format

Future feedback layer

We are not depending on feedback yet, but the structure is there so the product can learn from fit outcomes later.

No feedback saved yet.

POC scope

Use case

Brand-to-brand size translation for known sizes.

Input

Minimal: source brand, source size, target brand, and product type.

Output

One simple recommendation that is easy to understand and test with users.

Validation

Whether people find brand-to-brand sizing genuinely useful in a shopping flow.