E-Commerce: Product Data in Minutes Instead of Days

An industrial supplies online retailer with 50,000 active SKUs faces a structural product data problem: suppliers deliver datasheets in different formats — PDFs, spreadsheets, Word documents. Product copy is technically correct but unsuitable for search engines or purchasing managers. Translations are missing. Attributes are incomplete or inconsistently filled.

An editor previously spent an average of 25 minutes per article on copy, attributes, and SEO optimisation. With 500 new articles per month, that was a full-time role — and still not fast enough.

Why External AI Services Are Problematic

Product data contains purchase prices, supplier terms, and proprietary technical specifications. For a B2B retailer, protecting this data from competitors and suppliers is essential.

Automated Product Data Management with SoverIQ

SoverIQ Stack runs on the retailer’s own server. New supplier data is processed automatically:

• Extract technical specifications from PDFs and datasheets
• Classify and populate attributes according to the internal attribute schema
• Generate SEO-optimised product copy (title, description, bullet points)
• Automatic translation into DE/EN/FR/NL by target market
• Completeness check: which mandatory fields are still missing?
• Direct upload to the PIM system via API

Results

Processing time per article: from 25 minutes to 3 minutes (quality assurance by the editor). The editor can now review 420 articles in the time previously spent on 50. New assortment additions go live 6× faster. SEO visibility of new articles improved measurably through more consistent copy.