Enrich products from just a part number and a name

Many products start life as a part number and a 30-character name. SKULaunch enriches them from that alone, using the identifier to find manufacturer pages, datasheets and images, then filling every attribute the product's category needs.

The problem

Distributors and parts businesses often hold thousands of SKUs with nothing more than a code and a short name from the ERP. No supplier file, no datasheet on hand. Researching each one is the only way to get complete data, and at a few minutes per product it never happens for the long tail, which is often where the margin is.

Before and after

An illustrative example from a bearing distributor.

Before: what you hold

"6205-2RS", "BRG DEEP GRV 2RS".

After: in SKULaunch

• Type: Deep groove ball bearing. Seals: 2RS, rubber seals both sides
• Bore: 25 mm. Outside diameter: 52 mm. Width: 15 mm
• Dynamic and static load ratings from the manufacturer datasheet
• Title and description written from the verified attributes

How it works in SKULaunch

1. Classify. Place the product in your taxonomy from its code and name.
2. Source by identifier. Use the part number, with brand where known, to find manufacturer pages and datasheets.
3. Extract. Fill the category's attributes from those sources, in your units.
4. Write and review. Generate copy from the verified attributes and approve.

Part numbers often carry data already

Many part numbers are structured. "6205-2RS" tells an engineer the series, bore code and seal type before any lookup. Decoding what the code itself says first gives enrichment a head start, and helps catch mismatches when a sourced page describes a different variant.

What changes

The long tail gets complete records, not just the top sellers, without anyone researching products one by one.

Common questions

What if the brand is unknown?

Brand helps but is not always needed. Products that cannot be matched confidently are left for review.

Will it guess values it cannot find?

No. Attributes without a reliable source stay empty and visible.

Does this work for automotive parts?

Yes, and it pairs with fitment and cross-reference data for parts catalogues.

See AI web search, ERP product data, and product data enrichment.