
What is a SKU? Definition, structure and common mistakes
The identifier everything hangs off — stock, orders, channels. How a SKU differs from a GTIN, how to structure one, and the mistakes that hurt for years.
Insights on Product Data Management, AI & E-Commerce

The identifier everything hangs off — stock, orders, channels. How a SKU differs from a GTIN, how to structure one, and the mistakes that hurt for years.

"We already have an ERP" is the most common objection — and sometimes right. Which data belongs where, when the ERP is enough, and when it starts to strain.

The EU product safety regulation lands as something mundane for retailers: a set of fields that must be filled per product, on every channel, in the right language.

Two hard problems stacked: heightened safety expectations, plus age and size logic no two brands express the same way. Where the longtail breaks and how to structure it.

Most PIM comparisons are written for brands or enterprise IT. If you carry dozens of brands, the evaluation criteria are genuinely different — here they are.

JTL-Wawi already handles product data, so the honest question is whether you need a PIM at all. A decision rule — and the options if the answer is yes.

BMEcat is the XML format B2B suppliers send catalogs in — and it is not a classification system. What it contains and how it relates to ETIM and eCl@ss.

What a Kaufland listing needs, why uploads get rejected (hint: it is rarely the upload), and how to publish from one source alongside your other channels.

advarics keeps the merchandise side in order. What it is not built to produce is sales-ready online content — that is where a PIM sits alongside it.

plentymarkets covers product data as part of the platform — many setups need nothing more. An honest decision rule for when a PIM layer earns its place.

Properties make Shopware filters work — and are the first thing that degrades with many suppliers. Why lists get messy and how to make a cleanup stick.

JTL-Wawi holds whatever you put in. A five-step workflow to keep product data complete and consistent when forty suppliers deliver forty formats.

Every supplier delivers differently. See how AI Autofill fills attributes, writes copy and translates — in bulk across thousands of products, with a review queue.

The 5 signs you have outgrown spreadsheets, what Excel really costs, and a 5-step migration to a PIM — with no big-bang go-live.

Single-text tools write one description at a time. The retail advantage: generate hundreds of consistent, on-brand, multilingual descriptions from structured data.

More product research now starts in an AI assistant. Whether your products show up comes down to clean, structured product data — here is how to prepare.

Shopware handles the storefront — but multi-brand retailers need a PIM behind it. How the main options compare, factually, and which fits which retailer.

Approval rarely fails because of the writing — it fails in the hand-offs. The four stages of an efficient product content workflow, the tools compared, and how an in-PIM review queue removes the email bottleneck.

AI-powered PIM systems promise painless cross-border selling — translation, local attributes, per-market compliance. Where that holds up, where it breaks, and how the systems compare for retailers going international.

Which e-commerce syndication solutions actually automate well on a sub-€500 budget? The tool categories, honest DIY workarounds and where they break, and what to prioritize when the budget is tight.

Every multi-brand retailer fights the same core problem — no two suppliers deliver alike. But the pain looks completely different per industry. The landscape, and where a PIM built for retailers takes over.

Sports & outdoor is the broadest retail sector: variant-heavy soft goods meet attribute-rich hardware. Buying-group pools and FEDAS cover the core — Productbay handles the niche and longtail.

Fashion Cloud is the industry standard – but only covers connected brands. How a PIM consolidates the Excel/CSV everyday, unifies size and color systematics, and matches images via DAM.

Footwear shares fashion's Fashion Cloud reality but adds far more complex size and width logic. Why size mapping is the central pain — and how Productbay solves it.

Furniture data is unusually PDF- and catalog-heavy, with configurable variants and huge asset volumes. How a PIM with a DAM reads PDFs into attributes, keeps variants linked and manages assets.