How do I clean product data before migrating to a PIM?

Clean product data against the target data model, and only for the products and attributes that will move. Cleansing everything in the old systems spends effort on data nobody will use.

Work in 5 steps:

1. Profile every source: ERP, spreadsheets, old PIM and supplier files. Measure completeness, duplicates, units and value formats per attribute.
2. Scope the migration: decide which products, families and attributes move, and archive inactive products. PIMvendors estimate: this often removes 20 to 40 percent of records in a mature catalogue.
3. Standardise units, option lists, naming rules and classification, aligned with standards such as ETIM or GS1 where your partners use them.
4. Deduplicate and resolve conflicts between sources, with a data owner deciding the master value.
5. Validate in the target PIM with its quality rules, in trial migrations before cutover.

AI helps with extraction and classification of supplier data, and remains unreliable for regulatory and compliance attributes. Keep those under human review.

Assign cleansing to the business data owners with clear deadlines, supported by a small technical team for scripts and loads. In PIMvendors engagements, migration goes faster when the data model was designed before selection, because the target structure is known early.