Häufig gestellte Fragen
What is the difference between PIM and ERP?
An ERP system primarily manages transactional and commercial data such as stock levels, prices, orders and postings, while a PIM manages the descriptive, marketing-relevant product information such as long texts, technical attributes, translations and media references. Both systems overlap where the product is concerned, but pursue different focuses and complement each other. In practice, basic data such as article number, unit of measure or list price flows from the ERP into the PIM, which then editorially enriches this data and distributes it across channels. Which system leads for which data should be clearly defined before integration.
When is a PIM system worthwhile?
A PIM is worthwhile above all when a company sells many products through multiple channels such as an online shop, marketplaces and print, and has so far maintained product data multiple times in separate systems. The drivers are usually high assortment complexity, intensive multilingual requirements or the connection of numerous output channels, because with each additional channel the manual maintenance effort and the risk of errors increase. With very small assortments and only one sales channel, the implementation effort often outweighs the benefit. A sound decision should weigh the expected maintenance effort, the channel diversity and the existing system landscape against each other.
How much does a PIM system cost?
The price range is wide and depends heavily on the vendor, functional scope and assortment size. Mid-market-oriented SaaS PIMs frequently fall within a range of roughly 15,000 to 60,000 EUR in licence costs per year; enterprise systems can be significantly higher, while open-source solutions such as Pimcore have, since the licence change to the Pimcore Open Core License, been free to use in the Community Edition only under certain conditions (for example for companies below a defined revenue threshold) and usually require a paid edition for commercial production use. Importantly, the pure licence fees often account for only the smaller part of the total cost, since implementation, customising, data migration and training frequently amount to 0.5 to 2 times the first annual licence. Cloud models lower the initial investment but permanently shift costs into ongoing operating expenses.
What is the difference between PIM, DAM and MDM?
The three systems handle different data domains and are often used in combination. A PIM manages structured, descriptive product information such as attributes, texts and classifications; a DAM (Digital Asset Management) stores and organises unstructured media files such as images, videos and print data, which the PIM merely links to the product data. MDM (Master Data Management) is the overarching strategy and platform for all business-critical master data and can incorporate PIM and other domains as specialised building blocks. Put simply, PIM centralises product data, DAM centralises media, and MDM centralises all of a company's master data.
Which classification standards does a PIM use?
PIM systems work with standardised classification systems so that product characteristics are described in a structured, machine-readable way that is uniform across manufacturers. Widely used are ETIM, which originally comes from electrical engineering and also covers heating, ventilation, air conditioning and sanitary equipment, among other areas, and eCl@ss as a cross-industry, ISO/IEC-compliant standard that is frequently mentioned in the context of Industry 4.0. Such standards serve as a common language between manufacturers, retailers and end customers and facilitate electronic data exchange across shops, catalogues and marketplaces. Which standard is relevant depends on the industry, target markets and the requirements of the connected trading partners.
How long does implementing a PIM system take?
The project duration depends on the data model, assortment size, number of interfaces and organisational maturity, and therefore cannot be stated as a blanket figure. Mid-market implementations are in practice often completed within a matter of a few months, while extensive enterprise projects with many source and target systems can run significantly longer. The greatest effort often arises not from the software itself but from cleansing, structuring and enriching the existing product data, which regularly accounts for a substantial share of the total effort. A clearly delineated data model, a defined interface strategy and realistically planned data maintenance resources considerably shorten the time to productive benefit.