Product data governance is the set of owners, rules and routines that keep product data complete, correct and current. In practice every attribute has a named owner, every product passes agreed checks before it goes live, and someone reviews quality on a fixed rhythm. Without it, a new PIM decays within a year of go-live.
MRO distributor catalogues break because they combine hundreds of suppliers, very large numbers of technical SKUs and buyers who search by exact specification. When supplier data arrives in different structures, units and levels of completeness, filters fail, search misses and buyers pick up the phone or go elsewhere. The fix is rarely a new search tool. It is MRO product data built on a model.
ETIM is an open international classification standard for technical products. Each product is assigned to an ETIM class, and each class sets the features, units and value lists that describe it. Distributors use ETIM to receive supplier data in one structure, run consistent filters and exchange data with wholesalers and buying groups.
Agentic commerce is buying where an AI assistant researches, compares and in some cases completes a purchase for the shopper. An agent can only choose products it can understand. What decides the outcome is complete, structured, current product data: the same data behind your filters, site search and marketplace listings.
Bunnings supplier product data covers far more than a barcode and a price. Bunnings asks suppliers to provide and maintain master data, website content, images and compliance documents for every product they supply. New lines stall when that data is incomplete, does not match the physical product or arrives in the wrong structure. The fix sits upstream, in the supplier’s own product data.
Marketplace listings in Australia are rejected or suppressed for a short list of reasons. The usual causes are missing or invalid identifiers, the wrong category, missing required attributes, images that break the rules and missing Australian compliance information. Each marketplace has its own template, so fixes made by hand in one channel rarely carry over to the next.
An ERP runs the transactions: item codes, cost, price, stock, orders and finance. A PIM runs the product content: attributes, descriptions, images, documents and the version each channel needs. Most distributors and retailers need both, with the ERP owning operational data and the PIM owning everything a buyer reads.
Maropost Commerce Cloud, formerly Neto, can hold product data well for a simple range. Once you sell thousands of SKUs from many suppliers, with variants, detailed attributes and several channels, that changes. A PIM becomes the governed source, and Maropost becomes one of the channels it feeds.
GS1 Australia issues the barcode numbers (GTINs) Australian suppliers use. It also runs the National Product Catalogue (NPC), the data pool suppliers use to share product, packaging and logistics data with retailers and healthcare buyers. Retailers such as Woolworths receive new item and pricing data through it, so getting it right decides how quickly a new line goes live.
A Digital Product Passport (DPP) is a digital record of a product’s composition, sustainability, repair and compliance information. People open it through a carrier such as a QR code. The EU is making it mandatory product group by product group, starting with batteries in February 2027. Most of the work is product data you already hold, collected from suppliers and governed in one place.
The licence is rarely the biggest number in a PIM budget, and it is the only one most vendors will quote you early. Everything else arrives later. Implementation, integration, getting the data fit to load, training, and the internal time nobody costed. PIM pricing conversations start with a monthly subscription and end somewhere considerably more expensive. This is the version we build with clients before they sign anything.
Three acronyms turn up in the same meeting and usually only one of them is relevant. PDM manages engineering definition: CAD files, drawings, revisions and bills of materials. PIM manages the commercial information you sell with: attributes, descriptions, images and channel-ready content. MDM governs the shared master records every system depends on, of which product is one domain. The phrase product data management causes most of the confusion, because it means the first one in engineering and the second one in ecommerce.
Most distributors do not have one product catalogue. They have five, and nobody owns the relationship between them. The ERP holds the list finance and the trade counter trust. The website holds a subset of it with better photography. A spreadsheet on somebody’s desktop holds whatever was last uploaded to a marketplace. Product catalogue management is the work of making those versions agree without maintaining each one by hand.
Search for Amazon listing optimisation and you will be sold copywriting. Better bullets, punchier titles, keyword-rich descriptions. We have rewritten plenty of Amazon copy over fifteen years and it does move numbers. It is also the second-order fix. In Amazon’s own published guidance, what decides whether a shopper ever sees your listing is the structured attribute data behind it. Amazon states the consequence of leaving those attributes empty in one unambiguous sentence.
A Google Shopping feed is not a marketing asset. It is a schema with a validator attached. Every disapproval traces back to an attribute that was empty, malformed, or contradicted by your own website. Google publishes the whole specification. Below is what it requires, which omission triggers which disapproval, and which of those a feed tool can fix. The rest have to be fixed in the PIM.
A marketplace listing rejected on submission is almost never a copywriting problem. It is an empty field, a value the channel does not recognise, or a category mapped to the wrong node. The causes are finite, they are published, and they are all fixable in your PIM before the feed leaves the building.
Search for supplier onboarding and almost everything you find is about procurement. Vendor risk, bank details, compliance questionnaires, master data in the ERP. All necessary, none of it the reason your new range is not on the website. The part that takes the time is product data. Getting a specification, a description, images and a hundred structured attributes out of a supplier, in a state you can sell from. That is a different process with different owners, and most distributors run it as a series of one-offs. Below is the supplier onboarding stage model we use to make it repeatable.
Your new line form is a spreadsheet. It has somewhere between forty and two hundred columns. There is a hidden tab nobody has opened since the person who built it left. The filename ends in v4_FINAL, and the version number stopped incrementing three years ago. A buyer emails it to a supplier. The supplier fills in what they can and guesses the rest. Someone in merchandising fixes it by hand. That loop is where speed to market goes, and it is the same loop in almost every distributor we work with.
A distributor sends us a category export. It has eight or nine hundred rows. We sort by product count and the bottom third of the tree holds fewer than five items per node. Somewhere near the middle there is a level that exists because the website menu needed a third click. Product taxonomy design is rarely a question of how deep the tree should go. It is a question of which decisions belong to categories and which belong to attributes. Depth is what you notice when that split has gone wrong.
Checked on 20 August 2026, the first line of Google’s published English taxonomy file still reads # Google_Product_Taxonomy_Version: 2021-09-21. That Google taxonomy lists 5,595 categories across 21 top-level branches, seven levels deep at its deepest point. The en-GB file carries the same version number. Google describes its own categorisation as “continuously evolving”. The gap between that and a static published file causes most of the mapping confusion we are asked to fix.