A PIM data migration moves product records, assets and relationships from spreadsheets, ERP, legacy PIM and e-commerce systems into a new data model. It runs in eight steps, from source inventory and profiling to mapping, cleansing, test loads, reconciliation and cut-over. Vendor benchmarks show migration is often the longest phase of a PIM project.
Migrating product data into a new PIM (product information management) system means extracting records, assets and relationships from every current source. That data is then profiled, mapped to the new data model, cleansed, loaded in rehearsals and reconciled before a controlled cut-over. Published vendor benchmarks show migration is often the longest single phase of a PIM project, so it needs its own plan, owner and acceptance criteria.
Why is PIM data migration the riskiest phase?
Migration exposes every inconsistency that legacy processes have hidden. Spreadsheets hold free-text values, ERP fields have been repurposed, and the same attribute exists in three systems with three different meanings. Inriver's published benchmark places migration at four to eight weeks for smaller businesses and eight to sixteen weeks for enterprises, longer than configuration.
The new PIM also has a stricter data model than most sources. Typed attributes, select lists and variant structures reject data that a spreadsheet accepted without complaint.
What are the steps of a PIM data migration?
The eight steps below form a common sequence. Durations vary widely by project and are shown as illustrative ranges for a mid-sized catalogue.
| Step | What happens | Output | Illustrative effort |
|---|---|---|---|
| 1. Source inventory | List every source: ERP, spreadsheets, legacy PIM, web shop, DAM, supplier files | Source register with owners | 1 week |
| 2. Scope decision | Agree which products, locales and history to migrate | Signed scope | Days |
| 3. Profiling | Measure fill rates, formats, duplicates and outliers per field | Profiling report | 1 to 2 weeks |
| 4. Mapping | Map each source field to a target attribute, with conversion rules | Mapping specification | 2 to 4 weeks |
| 5. Cleansing and conversion | Standardise units, split combined fields, resolve duplicates, map classifications | Cleansed staging data | 2 to 6 weeks |
| 6. Test loads | Load into a test environment, iterate on errors | Load logs, error rate trend | 2 to 4 rehearsals |
| 7. Reconciliation | Compare counts, values and relationships with sources, then steward sign-off | Reconciliation report | 1 to 2 weeks |
| 8. Cut-over | Content freeze, final delta load, switch integrations, hypercare | Live PIM | Days plus hypercare |
How should source data be mapped?
Mapping is where business knowledge enters the migration. Each target attribute needs a defined source, a conversion rule and a fallback. Common conversion rules include:
- Unit normalisation: "18V", "18 V" and "18 volt" become 18 with unit V.
- Field splitting: a combined "Colour/Size" column becomes two variant axes.
- Value mapping: legacy material codes map to new select-list options.
- Classification mapping: legacy categories map to the new master classification and to external codes. For GS1 GPC, the placeholder brick 99999999 is available where no brick fits yet.
- Asset linking: file names or URLs resolve to DAM asset IDs. See DAM and PIM integration.
- Source priority: when ERP and a spreadsheet disagree, a documented rule decides which value wins.
Keep the mapping specification under version control. It becomes the reference for later integrations.
How do you validate a migration?
Validation needs numbers as well as spot checks. Typical acceptance criteria:
- Record counts per family match the agreed scope, with every exclusion explained.
- Mandatory attributes reach an agreed completeness level, measured with the metrics in product data quality.
- Zero duplicate identifiers (SKU and GTIN).
- Every variant has a valid parent, and every asset link resolves.
- Category owners sign off a sample of products per family.
Run the same checks after every test load and plot the error rate. A falling trend over two or three rehearsals is a good signal that the team is ready for cut-over.
How should the cut-over be planned?
Cut-over planning prevents data loss between the last rehearsal and go-live. Agree a content freeze window in legacy systems, run a final delta load of changes since the last full load, and switch inbound and outbound integrations in a fixed order. The integration architecture guide covers connector sequencing.
Keep the legacy sources read-only for a defined period, typically several weeks, so teams can check historical values. The full context of phases and team roles appears in the PIM implementation roadmap.
Key takeaways
- Migration is often the longest phase of a PIM project. Inriver benchmarks it at 4 to 16 weeks depending on company size.
- Follow eight steps: inventory, scope, profiling, mapping, cleansing, test loads, reconciliation and cut-over.
- Cleanse during migration with documented conversion rules, and keep the mapping specification under version control.
- Validate with numeric acceptance criteria and track the error rate across rehearsals.
- Reduce scope by archiving inactive products instead of migrating everything.
Frequently asked questions
How long does a PIM data migration take?
Inriver's published benchmark puts data migration at four to eight weeks for smaller businesses and eight to sixteen weeks for enterprises, which makes it the longest single phase in its implementation table. The main drivers are the number of source systems, the amount of cleansing required and how quickly category owners can review mapped data.
Should product data be cleansed before or after migration?
Most cleansing is best done during migration, between extraction and loading, where scripts and rules can be applied consistently. Fixing data in legacy systems first is often slow, and loading dirty data into the new PIM spreads errors to channels. Leave only low-priority enrichment for after go-live, and track it as a backlog.
Should all historical products be migrated into the PIM?
Usually not. Migrate active and recently discontinued products, plus anything still needed for spare parts, warranty or regulatory retention. Archive the rest in a read-only store. Reducing scope early shortens mapping, cleansing and testing, and keeps the new PIM focused on products that channels actually need.
For guidance on structuring a PIM selection, see the independent resource PIMselection.com.