How to Build a PIM Requirements Checklist

Key Takeaways

• A PIM (product information management) requirements checklist only works once you know what product data you manage, where it lives, and who touches it. Features come second.
• Your business type changes the checklist. A manufacturer, a distributor, and a retailer each need something different from the same PIM software.
• Product relationships like variants, kits, and accessories decide how flexible your data model has to be.
• Team pain points turn vague wishes into requirements you can test in a demo.
• Auditing your ERP (enterprise resource planning) system, spreadsheets, and shared drives shows you what counts as product data in your business and where the gaps are.
• Add the newer must-haves after your own needs: AI enrichment, agentic commerce readiness, and Digital Product Passport compliance.

1. Catalog Every Type of Product Data You Have

Start by listing every type of product data your business creates, collects, or sends out. Most teams manage more than they expect. Common buckets include:

• Core attributes such as names, descriptions, and dimensions
• Technical specifications that vary by category
• Pricing and availability that change often
• Images, video, and documents like spec sheets and manuals
• Compliance and supplier data such as certifications and country of origin

Each bucket asks something different of a PIM. Heavy technical specs call for flexible attributes. Large image libraries call for strong digital asset management (DAM). Regulated products call for compliance fields and audit trails. Write down your buckets, then note roughly how many SKUs and attributes sit in each.

2. Identify Your Business Type

Your business type shapes almost every requirement that follows. Here’s how the priorities usually shift:

• Manufacturers manage complex specs, compliance data, and information from engineering or product lifecycle management (PLM) systems. Attribute flexibility and compliance fields come first.
• Distributors and wholesalers handle huge catalogs and inconsistent data from many suppliers. Supplier onboarding and data cleanup matter most.
• Retailers and marketplace sellers publish to many channels with different format rules. Publishing to each channel (often called syndication) and channel-specific content lead the list.
• Brands selling direct need speed, consistency, and rich content. Enrichment tools and asset management carry more weight.

Many businesses are a mix. A manufacturer that also sells direct needs the first and last priorities together.

3. Map Your Product Relationships

Next, map how your products connect to each other. Teams often skip this step, and it’s where many PIM projects hit trouble later.

List the relationship types you manage: size and color variants, bundles and kits, accessories and replacement parts, cross-sells, compatibility (this part fits these models), and multi-level hierarchies. Simple variants work in almost any PIM. A kit with 40 components that each carry their own data needs a model built to handle relationships.

Try this test. Sketch your three most complex products on a whiteboard. Whatever is hard to draw will be hard to model, and that’s a requirement.

4. Name Your Team’s Biggest Pains

Then ask the people who handle product data every day what slows them down. Common answers include chasing suppliers for missing information, copying content into channel templates, fixing retailer rejections, waiting on IT for changes, and launching late.

Turn each pain into a requirement you can test. Messy supplier spreadsheets point to a supplier portal that validates data at the point of entry. Retailer rejections point to completeness rules and approval workflows that block incomplete products from publishing. Ask marketing, ecommerce, merchandising, and operations separately, because each team feels a different pain.

5. Audit Where Your Product Data Lives Today

Now find out where your product data sits. Check your ERP, spreadsheets, PLM, shared drives, supplier emails, and marketplace dashboards. For each one, note who owns it, how often it changes, and how it reaches other systems.

The ERP usually holds the core: SKUs, prices, and inventory. Spreadsheets usually hold the rest, like descriptions, extra attributes, and channel versions. That split tells you a lot. If the ERP stays the system you trust for core data, you need strong two-way ERP integration so the PIM doesn’t create a second version. If spreadsheets hold most of your enrichment, you need easy bulk import and a clear plan to retire them.

6. Turn Your Answers Into a PIM Requirements Checklist

You now have what you need to write the checklist. Match each finding to a requirement, and each requirement to a question for vendors. Here’s how that mapping looks in practice.

7. Add the Modern PIM Requirements

Once your own requirements are on the page, add the modern PIM requirements every growing catalog now needs.

AI-powered enrichment. Teams use it to write descriptions, pull attributes from supplier files, and flag gaps at scale. The strongest versions, like Pimberly’s Pimbles AI layer, work inside the product record instead of in a separate tool.

Agentic commerce readiness. AI shopping tools lean on structured product data, not just marketing copy. Adobe reports that AI-referred traffic to US retail sites grew 62% year over year in July 2026, and that traffic converted 60% better than other visits. A well-written description on an incomplete record is easy for those tools to miss.

Digital Product Passport compliance. The first legally mandatory deadline lands February 18, 2027, starting with batteries. More categories phase in through 2030. If you sell into the EU, keep compliance data in the same controlled record as everything else, with approvals and an audit trail.

8. Prioritize and Test Requirements With Vendors

Finally, sort your list into must-haves, should-haves, and nice-to-haves. Must-haves tie to your biggest pains or hardest data realities, like relationships or compliance. Score each vendor from 0 to 3 on every line, and count the must-haves double.

Then run the demo on your data. Send two or three of your hardest products ahead of time and ask each vendor to load and model them live. A demo on sample data shows what the software can do. A demo on your data shows whether it will work for you.

Ask about pricing too. Per-channel or per-connector charges can punish the growth you’re buying a PIM to support. And ask who handles implementation, the vendor or a partner.

FAQs

Q: How do I build a PIM requirements checklist?
A: Start with your data, not features. Inventory your data types, identify your business type, map product relationships, name team pain points, and audit where your data lives. Then turn each finding into a requirement and add must-haves like AI enrichment and compliance.

Q: What should I look for in a PIM?
A: Look for a flexible data model, product relationships, workflows and completeness rules, supplier data submission, ERP integration, publishing to each channel, built-in DAM, AI enrichment, compliance handling, and implementation support. Your own findings decide which items rank highest.

Q: How do I choose a PIM?
A: Turn your answers into PIM selection criteria, then score each vendor against them. Count the must-haves double, and ask every vendor to load your hardest products live. A demo on your own data is the best test of fit.

Q: Who should help build a PIM requirements checklist?
A: Bring in the people who handle product data daily, such as marketing, ecommerce, merchandising, and operations. Add IT or whoever owns the ERP, since integration shapes the whole project.

Q: Do I need a PIM if my data lives in an ERP and spreadsheets?
A: Often, yes. ERPs are built for transactional data like inventory and pricing, not for enrichment and channel publishing. If your teams spend more time fixing and reformatting data than using it, a PIM is worth a look.

Q: How many requirements should a PIM checklist have?
A: Most teams do well with 15 to 25 prioritized requirements. Longer lists tend to bury the ones that matter.

Start With Your Data, Then Choose the Platform

The best PIM evaluations begin with a team that knows its own data. Once you know what you house, how it connects, where it lives, and what slows people down, the checklist nearly writes itself. Vendors also have a harder time hiding behind generic feature claims.

Pimberly was built for these realities. Its flexible data model, supplier portal, workflows, and built-in DAM tackle the data challenges this checklist surfaces.