When people talk about implementing a PIM, it’s easy to picture a mostly technical project: import the catalog, connect the ERP, set up the ecommerce site and get to work.
In reality, implementing a PIM means getting data, tools, people and processes on the same page.
You need to understand where information comes from, who owns it, how products are structured, which checks are needed and where that data has to end up.
That’s why a good implementation doesn’t start with the software. It starts with how the company works today and what it wants to improve.
1. Define goals, priorities and scope
Before talking about connectors or imports, you need to be clear on why you’re introducing a PIM in the first place.
The problem varies from company to company: data scattered across files and systems, too much manual work, long lead times to publish new products, trouble handling languages and markets, or errors that keep resurfacing across channels.
This is also when you decide where to start. You don’t have to bring in the entire catalog, every brand and every market from day one. It’s often more useful to define a clear initial scope that’s representative enough of your real complexity.
What you get: shared goals, clear priorities and criteria for evaluating the first phase.
2. Map the data journey
The next step is figuring out where product information lives today.
ERP, ecommerce, marketplaces, WMS, a DAM if you have one, internal databases, Excel, shared folders: in practice, data rarely comes from just one place.
The key question isn’t just “what do we connect to the PIM?”, but which system should own each piece of information.
For example, codes and operational data can keep coming from the ERP, while descriptions, translations and marketing content are managed in the PIM.
What you get: a map of data flows and ownership before any integrations are built.
3. Build a data model that fits your company
A PIM has to reflect how your products actually work: families, attributes, variants, bundles, compatibilities, relationships, languages, units of measure, documents and market-specific content.
The usual starting point is the existing catalog and a set of representative products, including the trickier cases.
The goal isn’t to copy the old system’s structure into the PIM. It’s to work out which structure genuinely makes the catalog easier to manage, and to validate it with the people who work with those products every day.
What you get: a shared data model that can handle the exceptions too.
4. Decide who does what
Software doesn’t manage a catalog. People do.
The product team might handle technical data, marketing the descriptions and images, a translator the languages, and a manager the final review.
So the implementation needs to spell out who can create, edit, review and approve each type of information, along with permissions, required fields and workflows.
Above all, it has to be clear when a product counts as ready.
What you get: clear ownership and less chasing between departments.
5. Import, clean up and validate existing data
Now it’s time to bring what already exists into the new model.
That means pulling information from the agreed sources, mapping it to the new structure and, where needed, importing images, documents and relationships as well.
This is often where hidden problems surface: duplicates, the same value written in different ways, missing fields, inconsistent categories or information with no clear owning system.
Some issues can be normalized automatically; others need someone to make a call.
What you get: usable data in the shared model and a clear view of what’s still left to fix.
6. Switch on and test the integrations
Now the flows to other systems can be put to a real test.
Mappings and connectors are configured, and you check what happens when a product is created, edited or completed.
Testing the happy path isn’t enough. You also need to see what happens when data is missing, a variant changes, a translation isn’t ready or information is corrected after publication.
The most useful test is to follow a handful of products all the way from data entry to their final destination.
What you get: flows that are tested and validated before day-to-day use.
7. Train people and build independence
Training shouldn’t be a generic software demo tacked on at the end of the project.
What matters most is that each person understands how to do their own job in the new workflow.
Everyday users need to know how to find, edit and complete products. Specialist users may need specific features. Whoever will run the PIM in-house needs to know the data model, configurations and checks they’re responsible for.
Working directly on real data makes this phase far more valuable than abstract training.
What you get: self-sufficient users and in-house leads who can run the system.
8. Go live and support the rollout
Go-live isn’t just the day someone flips a switch.
You need to catch up on changes made during the project, switch on the production flows and make clear from what point the PIM becomes part of day-to-day operations.
In the first few days, cases that never came up in testing will inevitably appear. That’s why it’s important to keep an eye on the first publications, work alongside users and quickly tie up any loose ends.
What you get: a controlled handover from project to everyday use.
What if I want to start smaller?
A pilot project can be a good way to get started.
The key is not to pick only the simplest products. A pilot should include just a few cases, but ones representative enough to put the model, flows and main requirements to the test.
A proof of concept and an operational pilot aren’t the same thing: a pilot needs to be close enough to real work to produce useful insights for the full project.
External partners are part of the project too
Ecommerce agencies, ERP consultants, system integrators and other vendors often look after key parts of the ecosystem.
Bringing them into the steps that concern them helps clarify responsibilities, dependencies and testing, without turning the client into the technical go-between for multiple parties.
So how “technical” is a PIM implementation, really?
There’s a technical side, of course.
But connecting systems and importing data is only part of the job.
A good implementation makes sure the PIM represents your products accurately, receives reliable information, puts it in the hands of the right people and delivers it wherever it’s needed.
In other words, it’s not simply about launching new software. It’s about building a more orderly way to manage product data, every single day.