Krusader's Talk

Data Quality #3: How to ensure high-quality, consistent product data across all platforms

1 april 2025

Over the past decade at Kruso, we’ve helped organizations tackle both the technical and human aspects of PIM. Here are four steps we recommend for a smooth, value-adding implementation.

Data Quality #2: Why good product data is also critical in B2B Krusader's Talk

Have you read my latest insight?

In my two previous insights, I showed why data quality matters in both B2C and B2B. Poor product data frustrates consumers and undermines sales, while missing or inconsistent data can derail entire supply chains. Either way, accurate, up-to-date product information is essential.

So, how do you ensure that your product information stays accurate and consistent across every platform? A product information management (PIM) system can be a game-changer, but technology alone won’t solve everything.

Step 1: Assessment & planning

Begin with a thorough evaluation of your current systems and clear objectives.

Analyze existing data processes: Are you juggling spreadsheets or multiple systems?
Gather stakeholder requirements: Involve marketing, sales, logistics, and others who rely on product data.
Outline a concrete project plan: Set milestones, timelines, and deliverables to keep everyone aligned.

Step 2: Selecting & customizing your PIM system

Choosing the right solution is crucial; every business has unique workflows, data models, and scalability needs.

Evaluate different platforms: Look for features that match your organization’s size, complexity, and budget.
Tailor the system: Adjust user roles, data structures, and integrations to fit your processes.

Step 3: Data migration & integration

Next, migrate your existing data in a way that preserves accuracy and operational continuity.

Plan a data migration strategy: Include cleansing, mapping, and transformation to weed out errors.
Execute carefully: Maintain data integrity and minimize downtime.
Integrate with key systems: Connecting your PIM to ERP, CRM, or other tools fosters real-time data coherence.
This is also a great opportunity to clean up other systems – like your ERP – by relocating product data that doesn't belong there. This not only streamlines the ERP but simplifies your entire data ecosystem.

Step 4: Training & ongoing support

A great platform won’t help if your team doesn’t know how to use it.

Provide targeted training: From quick tutorials for content writers to deeper sessions for data managers.
Offer thorough documentation: Accessible resources reduce support needs and keep the system running smoothly.
Support & maintenance: Your business will grow, and your PIM should evolve with it.

PIMExplore how a PIM can enhance efficiency, growth, and scalability by streamlining business processes in a dynamic commercial landscape.

Technology + people = Sustainable data quality

A PIM system can be transformative, but successful implementation requires more than software alone. It demands a structured approach, clear goals, and committed training and support. By following these steps, you’ll build a solid foundation for high-quality, consistent product data – across every channel and platform.

If you have questions or want to explore PIM in your context, feel free to reach out. Data quality isn’t just about technology – it’s about empowering people to make the most of it. Let’s ensure your product data is ready for whatever comes next.