Apparel HS Code Classification Guide: Knit vs Woven, Fiber Type, and Gender

A practical apparel HS classification guide for catalog and trade teams: how construction, fiber content, gender, garment type, and use drive tariff codes and duty rates.

Apparel classification is deceptively hard because small attribute differences can change the tariff line. A buyer may see two similar tops. Customs classification sees construction, fabric, fiber content, gender, age category, and intended use. If those attributes are missing from the product record, teams guess from the title — and guesses become duty errors, broker questions, and margin surprises.

The fix is not to memorize every apparel code. The fix is to build an apparel data model that captures the attributes classification depends on. Claro helps by extracting and validating those attributes from supplier feeds, spec sheets, labels, and product copy, then preserving the evidence behind each HS or national tariff code assignment.

The apparel classification decision tree

1

Identify the garment type

Start with what the item is: shirt, blouse, sweater, jacket, trousers, dress, underwear, swimwear, accessory, footwear, or textile article. A vague merchandise category such as “women’s tops” is not specific enough.
2

Determine knit/crochet vs woven

Construction is one of the biggest splits in apparel schedules. A supplier title may omit it, so use fabric attributes, spec sheets, or material descriptions rather than merchandising labels alone.
3

Capture fiber composition

Cotton, synthetic fiber, wool, silk, and blended materials can classify differently. For blends, teams often need the chief weight fiber or exact percentages, not just “poly/cotton” text.
4

Confirm gender, age, and intended user

Men’s, boys’, women’s, girls’, babies’, and unisex products may follow different lines. Do not infer this only from color or collection name.
5

Check special use and construction details

Water resistance, protective use, sports function, lining, coating, and whether an item is part of a set can matter. These details need structured fields or reviewer prompts.

The attributes that drive duty-rate differences

Attribute	Why it matters	Common data problem	Better catalog field
Construction	Knit/crochet and woven goods are often separated early	Title says 'top' but not construction	fabric_construction: knit / woven / nonwoven
Fiber content	Cotton, wool, synthetic, and blends can follow different subheadings	Material field says 'mixed fibers'	fiber_percentages with chief_weight_fiber
Gender or age	Schedules can split men's/boys' from women's/girls' and babies' garments	Supplier uses collection name only	intended_user plus age_group
Garment type	A blouse, shirt, sweater, jacket, and dress are not interchangeable	Merchandising category is too broad	customs_garment_type
Use or finish	Protective, coated, waterproof, or sport-specific construction can matter	Feature buried in copy	regulated_use / coating / water_resistance

Examples of classification drift in apparel catalogs

Apparel catalogs drift when merchandising data and customs data evolve separately. A style may start as a cotton woven blouse, then launch in a synthetic knit version under the same parent style. A supplier may update fabric composition but leave the old tariff code in the spreadsheet. A retailer may create a unisex category for ecommerce while trade data still requires men’s, women’s, boys’, girls’, or babies’ handling.

Those changes are manageable when product identity, variant attributes, and classification evidence are linked. They are dangerous when the code is a static text field copied across colors and sizes without validation.

Build the classification record per style and variant

For apparel, some classification attributes live at style level and others at variant level. A style may share garment type and construction, while fiber content, gender, or use can vary across capsules or regional assortments. Size and color usually do not change classification by themselves, but they can reveal that records were copied incorrectly.

A durable model includes:

style identifier and variant identifier
garment type
knit/crochet/woven construction
fiber composition and chief weight fiber
gender or age group
intended use or special construction
source document or supplier file
HS root and market-specific tariff code
reviewer status and effective date

Claro uses that kind of canonical record so tariff codes are not maintained as isolated spreadsheet values. When a supplier revises fiber content, the affected SKUs can be rechecked before the next import file or marketplace feed is sent.

Guide

HS Code vs HTS Code

Understand the global six-digit root and the U.S. national extension.

Tool

HS Code Lookup

Validate code structure and catch malformed tariff-code values.

Guide

Classify an Inherited Catalog

A practical workflow for rebuilding classification from messy source data.

Claro

Apparel classification governance

Extract, validate, and govern classification-driving attributes across supplier catalogs.

FAQ

What apparel attributes matter most for HS classification?

The highest-impact attributes are garment type, knit versus woven construction, fiber composition, gender or age category, and intended use. Missing any one of those can move an item to the wrong heading or subheading.

Are knit and woven garments classified differently?

Yes. Apparel classification often separates knitted or crocheted garments from woven garments before it considers fiber type or gender. A cotton knit shirt and a cotton woven shirt can land in different areas of the tariff schedule.

Can a product title alone classify apparel correctly?

Usually not. Titles rarely carry every required attribute, and terms like top, blouse, shirt, shell, pant, and legging are used inconsistently by suppliers. Reliable classification needs structured attributes plus source evidence.

How does Claro improve apparel classification data?

Claro extracts construction, fiber, gender, size, and use attributes from supplier files and product content, validates them against classification rules, and writes source-linked codes back into the catalog so duty and compliance teams are not working from ambiguous titles.