UNSPSC 55121602: Clothing labels

UNSPSC 55121602 Clothing labels is a Commodity code covering labels affixed to or printed on apparel, fabric, and related textile items — though recent state and local solicitations tagged with this code show minimal genuine clothing-labeling activity. Instead, the recent opportunities reveal that this code is being used to capture file-folder labels, training-unit supplies including office labels, and organizational labeling products. State and local buyers posting under this code include city procurement departments and county sheriffs' offices. The work solicited involves custom-printed labels for filing systems, year labels in color variations, numeric and color-coded labels for organizational purposes, and expandable folders with label integration. This mismatch between the code's nominal scope and what jurisdictions are actually buying suggests that clothing labels proper see little recent state and local procurement activity under this categorization.

The County of Orange Sheriff-Coroner in Orange County, California posted a competitive invitation for bid (IFB #060-3015801-MB) due March 26, 2026 for file folders and labels across nine product categories, including custom-printed reinforced folders, year labels in ten color variations, and single-digit and two-digit numeric labels, with approximate annual usage of 15,000 custom-printed folders and delivery to two locations. The City of Philadelphia issued a micro purchase (B2727862) with a due date of August 31, 2026 for Training Unit Supplies with a contract ceiling of $45,000, featuring automatic annual CPI-U adjustment through the contract term of 365 days. The Orange County solicitation includes a five percent price preference for County of Orange Local Small Business (OCLSB) and Disabled Veteran Business Enterprise (DVBE) certified vendors, with a three-year term and option to renew for two additional years. Geographic concentration is limited; recent opportunities appear in California and Pennsylvania, though the sample is too sparse to characterize broader state-level activity.