A PIM system (Product Information Management) is central software for managing, enriching and distributing product information such as descriptions, attributes, media and translations. It supplies connected channels – such as the online shop, marketplaces, catalogues and data feeds – with consistent product data.
A PIM is the central library for all of a company's product data. Instead of maintaining texts, images and technical data in parallel in spreadsheets, the shop and the ERP, there is one leading source – and every sales channel draws from it.
Why do I need a PIM system?
As soon as product data is needed in several systems and channels, contradictions arise quickly without central maintenance: the shop shows a different description than the marketplace listing, translations are missing, attributes are incomplete. A PIM consolidates data maintenance in one place, defines mandatory fields and quality rules, and distributes the data in a structured way to shop, marketplaces and feeds. The ERP usually remains the leading system for logistics and pricing data, while the PIM leads for descriptive and media content – a clear division of labour instead of duplicate maintenance. Changes such as corrected descriptions or new images are maintained once and are then available consistently across all channels.
Practical relevance for shop owners
Well-maintained product data directly benefits visibility and conversion: complete attributes improve filters and on-site search, consistent data simplifies marketplace listings and shopping feeds, and structured information is increasingly evaluated by AI-driven search systems as well. With upcoming requirements such as the Digital Product Passport, a clean, central data foundation becomes even more important. Widely used PIM solutions include Akeneo and Pimcore, for example; numerous industry-specific systems exist alongside them. Our article on implementing a PIM system describes what a step-by-step introduction can look like.
A practical rule of thumb: the larger the assortment, the variant diversity and the number of channels and languages, the sooner a PIM pays off. A small shop with a few hundred items and a single channel can usually still do without one. At the latest with several marketplaces or international export markets, central data maintenance becomes a competitive factor.
Common mistakes
- Treating PIM as a pure IT project: Without clear responsibilities for data quality and maintenance processes, the system remains an empty shell.
- Unclear data ownership: If it is not defined which system leads which fields (ERP, PIM, shop), synchronisation conflicts arise.
- Migration without cleansing: Taking over old, inconsistent data one-to-one only moves the problem into the new system.
- Overambitious initial scope: Connecting all channels and attributes at once delays the benefit; a step-by-step rollout is usually more successful.
What to look out for
Before selecting a system, the data model, channels and workflows should be sketched out: Which attributes does each channel need? Who maintains, reviews and approves? How does data get from the ERP or supplier feeds into the PIM and from there into the shop? Interfaces are the critical path – from the ERP connection to the delivery to shop systems such as Shopware 6. AI-supported data enrichment can also speed up initial population, attribute maintenance and translations considerably – with quality control remaining a human task.
Define measurable quality criteria before the rollout – for example, completeness of mandatory attributes per channel. This makes progress objectively trackable, and publishing to a channel can be tied to reaching defined thresholds.