sizeSML

sizeSML is a compact size taxonomy used in product catalogs to denote the core clothing sizes Small, Medium, and Large under a single attribute. It is intended as a standardized label to improve consistency across brands and platforms.

Purpose and scope: sizeSML aims to simplify search and filtering, inventory synchronization, and analytics by providing a canonical three-size set. It is commonly adopted by e-commerce systems, data pipelines, and inventory management to harmonize diverse size labeling (S, M, L, XS, XL, Small, Medium, Large, or numeric measurements).

Implementation: sizeSML is typically modeled as an enumerated field with values S, M, L. Mapping rules translate alternative labels to these canonical values. Examples: XS or Small → S; Medium or M → M; XL or Large → L. Some systems also retain a separate extended size attribute for measurements when needed.

Usage and benefits: Under sizeSML, retailers can offer consistent filters and comparisons, reduce shopper confusion, and simplify analytics. It also helps align data across brands that use different naming schemes. Limitations: the three-size model may omit variation in garment measurements and fit; some products require more granular sizing; improper mapping can cause misclassification.

See also: clothing size, size chart, product data standards.