PIM migration: How to transfer product data cleanly to the new system

Why migration is the most critical part of a PIM project

New software is quickly installed. The real challenge of a PIM project starts when existing product data is to be transferred to the new system. This is where it is decided whether the PIM becomes a clean central system — or just the old chaos ends up in a new tool.

Many companies underestimate this step: It is assumed that you can somehow import the existing Excel lists UNDERP master data. In practice, it then becomes apparent that data is incomplete, contradictory or unsuitable for the new data model.

Typical mistakes with PIM migrations

1:1 transfer of all old data:

For fear of losing something important, all available data is transferred unchecked — including duplicates, outdated products and unclear attributes. The new PIM is therefore burdened by the day.

View migration as a technical task:

‍Migration is often seen as a purely IT issue. In fact, it is a technical issue: Only the specialist areas can assess which data is relevant, correct and sustainable.

Start data preparation too late:

‍Many teams only start cleaning data shortly before the planned go-live. That's when things get hectic and compromises become the rule — often with long-term consequences for data quality and trust in PIM.

5 steps to a successful PIM migration

Step 1: Capture data sources and data types

List all sources that contain product data today: ERP, PLM, CRM, Excel lists, access databases, file servers, legacy systems. Note down which types of data are there (master data, technical data, marketing texts, media files, translations).

Step 2: Understanding the target data model

Before you move data, it should be clear what the data model looks like in PIM: Which product classes are there? Which attributes are envisaged? Which mandatory fields apply to which channels? This target image is the basis for all mapping decisions.

Step 3: Define mapping and transformation rules

It is now defined how old fields and structures are mapped onto the new model. Typical tasks:

• Merging attributes that were previously maintained in different systems
• Splitting combined fields (e.g. length x width x height into three separate fields)
• Normalize units (e.g. convert cm to mm)
• Defining default values where old data gaps have

Step 4: Clean data before migration

Before importing data into PIM, obvious problems should be addressed:

• Remove or merge duplicates
• Identify outdated or discontinued products or remove them from scope
• Identify extreme outliers and implausible values
• Update missing mandatory information as far as possible

Step 5: Test migrations and validation

Instead of migrating everything in one go, an iterative approach with test migrations has proven effective. They import a section of data, check completeness and quality in PIM, and adjust mapping and rules. Only when the quality is right is the migration approved for larger amounts of data.

Roles and Responsibilities in Migration

Successful migration requires clear responsibilities:

• Technical responsibility: Product management/ Product data manager
• Technical responsibility: IT/data architecture
• Coordination and Project Management: Project Management
• Quality assurance: depending on the company, e.g. quality management

IT provides support with tools and scripts, but the decision as to which data is transferred to PIM in which form is technical.

conclusion

PIM migration is not an annoying task, but a unique opportunity to raise the quality of your product data to a new level. Anyone who takes this step consciously and in a structured manner will lay the foundation for the PIM to be accepted and used in the long term — instead of being perceived as a new chaos system.