Product Data & PIM

Product Data & PIM The two-day seminar for everyone whose product data consists of one spreadsheet, three Excel files and the memory of a colleague: you learn to design a data model, secure data quality and introduce a PIM so that the shop and all channels are supplied from it. By the end you know whether you need a PIM — and what it saves you.

Product Data & PIM at a glance

• Format: 2 days on site + self-learning track
• Level: basic to advanced
• Participants: max. 16 people
• Language: German (English on request)
• Certificate: AEI certificate of attendance
• Investment: €490.00 plus VAT

Product data is the largest unpaid item in e-commerce. It decides findability, comparability and the questions that reach the service desk — and is still mostly maintained on the side, by changing people, without an agreement.

The consequences are familiar: the same property has different names in two channels, an attribute is missing on a third of the articles, and every new requirement starts a discussion about where the truth lives. A PIM does not solve that automatically — it only makes visible what is missing.

This seminar works from the data model to the system. You design which attributes really describe your range, define ownership and validation rules and plan the connection and migration. Only then does the question of the tool arise.

What you take away

• A data model for your range that still holds when you grow.
• Validation rules for completeness and consistency that you can automate.
• An ownership assignment for every attribute.
• A plan for import, enrichment and translation.
• A basis for deciding whether and when a PIM makes sense.

Your learning objectives

• You distinguish product data that sells from data that merely exists.
• You design a data model with sensible attributes and hierarchies.
• You recognise gaps and contradictions before they reach the channel.
• You plan import, enrichment and translation as a repeatable process.
• You assess which requirements a PIM must meet and which it must not.

The levers at a glance

Data quality is an agreement, not a state. As long as nobody has defined what a complete article is, there is no complete article. A list of mandatory fields and one validation run replace any discussion.

Attributes without ownership decay. Every field needs a name behind it. Without that assignment everybody maintains a little and nobody maintains the whole.

A PIM solves order, not data. Whoever moves unclear attributes into a PIM gets unclear attributes with a better interface. First the model, then the tool.

Channels demand different depth. A marketplace needs other fields than your own shop, and a price comparison site others again. Whoever separates that in the model exports once instead of three times.

Who is this seminar for?

For people responsible for range, data or channel supply.

• E-commerce and shop managers with a growing range.
• PIM and data owners before an introduction or a migration.
• Marketing and content teams who maintain product texts and images.
• IT owners who build interfaces between systems.

Experience with spreadsheets and exports helps. The modelling is explained during the seminar; no database knowledge is required.

The seminar is not suitable for teams wanting training in a specific PIM. We work on the model and the process, not on one provider's interface.

Investment and dates

Participation costs €490.00 plus VAT, including the self-learning track, materials and certificate of attendance. There are six dates per year in Berlin, Hamburg, Cologne, Munich and live online, plus an in-house variant for teams. You will find all dates in the list on this page.

For the exercises bring an extract of your range — ten articles are enough. Anyone without access works with a sample dataset from retail.

After the seminar

You keep the materials, an attribute list as a template and a validation scheme with which you can measure completeness and consistency regularly. With that you can establish a reliable as-is state within a month.

The scheme runs on a spreadsheet: one column per attribute, one row per article, one percentage for completeness. Whoever runs it once a quarter sees deterioration before it shows up in the channel.

Two weeks after the seminar you receive a short follow-up: your data model and the attributes that are still unclear. We check which of them are really needed.

For teams the seminar is available as an in-house event with your own range. The procedure stays the same, the examples come from your assortment.

Programme: 2 days

Day 1 – Product data fundamentals

• Why product data counts
• Understanding the data model
• Completeness and consistency
• Maintenance and ownership
• What a PIM can do
• Connecting shop and channels

Day 2 – PIM systems

• Import and export
• Enrichment and translation
• Data for many channels
• Measuring and improving

Both days run from 09:00 to 16:15 with breaks in the morning, at midday and in the afternoon. Short self-checks sit between the blocks so you can test where you stand before moving on.

Each day has three parts: an introduction to the pattern, an exercise on your own range and a review in the group. At the end of day one your data model stands; on day two you test it against two channels.

The seminar includes a self-learning track. It contains the patterns from both days as short units with examples and one self-check each. You can work through it before the date to clarify terms, or afterwards to repeat what stuck and what did not.

Our approach

We work on your range, not on a sample structure. At the start of each exercise you decide which property you want to map and who will maintain it in future; at the end stands an attribute with an owner.

The exercises are short and repeat in variations. That is deliberate: a data model does not emerge from watching but from repeatedly deleting attributes that nobody maintains.

Every block ends with a sentence you could show a colleague: which attribute, who owns it, and which channel currently breaks without it.

We work in pairs, in small groups and in plenary, with changing partners. Every participant gets feedback on their model, not just on their idea. Group level and participant count are deliberately limited: with 16 people no anonymous lecture is possible.