Implementing a PIM System: How to Manage Your Product Data

Christoph Könninger7/28/2026

A PIM system collects and manages product information and data in one place. Find out here how you can implement it in your company.

Table of contents

PIM system: definition
Where can a PIM system help?
The benefits of PIM systems
Implementing a PIM system: a step-by-step guide
These are the best PIM systems

Key Takeaways

A PIM system acts as a central hub to consolidate and distribute error-free product information across all channels.
Structured data management breaks down internal silos and minimizes inaccurate descriptions, directly reducing costly customer returns.
Modern cloud-based PIM solutions utilize no-code interfaces and open APIs for rapid implementation without heavy IT involvement.
High-quality, well-maintained product data is the essential foundation required to successfully leverage modern AI applications.

A PIM system collects, manages and distributes all of a company's product information in one central place. That includes basic data, technical specifications, images and videos. It becomes your single source of truth for product data, replacing the job of maintaining the same information in several systems at once.

Without that central structure, product data tends to sit scattered across Excel sheets, folders and various systems. Change a product in one place and every other place is instantly out of date, so your shop shows the wrong description. Then come the returns, the unhappy customers and the lost revenue.

This is exactly where PIM systems such as viingx, Akeneo and Pimcore come in. In this article you'll find out what a PIM system can do, how to implement one step by step, and why implementation no longer has to mean a months-long IT project.

PIM system: definition

Product Information Management, or PIM for short, means collecting, managing and distributing all product information in one central place. That covers basic data and technical specifications as much as the images, videos and documents attached to each product.

PIM software is the central platform for all of it: the single source of truth for your product data. Create or change a product and the system syncs that change automatically across every connected channel. Your team maintains data in one place rather than five systems at once. Errors surface sooner, duplicates disappear, and everybody works from the same version.

So your PIM is more than a data hub. It's also the foundation for the automation and AI projects ahead. The cleaner and better structured your product data, the sooner you can put it to work.

Where can a PIM system help?

A PIM system brings structure to your internal processes, so that consistent, accurate product information is what reaches your customers. In practice, it supports your team with three jobs:

Data capture: The system draws data from internal and external sources such as ERP, PLM and supplier feeds. CSV and XLSX files import too. For images, videos and documents, you connect your PIM to a DAM system. Some platforms go a step further and combine PIM, DAM and headless CMS in a single system, so product data, media assets and marketing content all share one data model.
Data management: Inside the PIM platform you clean and update every piece of data and every asset attached to your products, from dimensions and materials through to descriptions and prices. Where you need to, you translate and localise the content for each market and region.
Data distribution: Everything you've maintained goes out across channels: to marketplaces, resellers, social media, your online shop, or print products such as catalogues. Wherever customers look, they see the same current information.

The benefits of PIM systems

Gartner puts the cost of poor-quality data at an average of $12.9 million per company per year. Revenue is only part of it. Poor data quality makes your entire data ecosystem more complex, and that complexity eventually shows up as worse decisions.

There's a newer factor too: AI projects rarely fail on the technology. They fail on missing or inconsistent data. A PIM system builds exactly the structured foundation that AI needs.

Here are the most important benefits of PIM software:

It structures product information management end to end, from capture through maintenance to distribution across internal and external channels.
Data validation and deduplication protect the quality and consistency of your product data.
Real-time updates mean everyone on the team is working with the latest product information.
Access levels let you control who sees and edits what. Data silos dissolve, and teams work from one source across departmental lines.
Structured, consistent product data is the basis for AI applications, from automated copy generation to AI agents that reach your data directly through open standards such as MCP.

Recommended reading: We show you the best routes to smooth PIM processes in your company.

Implementing a PIM system quickly, without a long IT project: is it possible?

Yes, it is. Plenty of companies put a PIM system off because they picture a major IT project with a customisation bill to match. That worry comes from an era when PIM projects genuinely did run for months or years. Cloud-native SaaS solutions have made implementation far simpler, for four reasons:

Use cases, not big bang: Instead of switching the whole company over at once, you break the project into individual use cases, each with a clear payoff. Product data management for the online shop first, say, then catalogue production. Early use cases often go live within a few weeks.
Configuration, not customisation: Modern systems run on no-code and low-code interfaces. Your business teams adapt data models, fields and workflows themselves. No programming, no external agency, no ticket to IT.
API-first architecture: You connect the systems you already run — ERP, shop, DAM — through open interfaces, rather than commissioning expensive bespoke integrations.
A platform that lasts: A PIM will be with you for years, so weigh open standards and flexible extensibility while you're still choosing. The system then grows with new requirements, and you won't be replacing it in five years' time.

Implementing a PIM system: a step-by-step guide

Exactly how implementation runs depends on your industry, your business model and the system landscape you've grown into. Almost every team works through these seven steps, though:

Identify your goals. Why do you want a PIM system? To raise the quality of your product information? To take manual data maintenance off your team? To consolidate several separate tools into one platform? Or to build a structured data foundation for AI applications? Think past today and ask what the system should be handling in three or five years. New sales channels, additional product ranges and AI processes are all far easier to set up if you've allowed for them from the start. The clearer the goal, the easier every decision that follows.
Work out who will use the system. Who is actually going to work in the PIM? Identify your future users and what they need. In practice it's rarely just the product managers — marketing, e-commerce and external partners all reach for product data. Settle this early and access management gets much simpler later.
Decide where the data will live. You can hold data centrally or decentrally. Large companies with wide ranges and complex data structures usually choose the central model. Smaller companies often let their teams manage data decentrally, on their own terms.
Identify the PIM features you need. No PIM software fits everyone, so settle a few questions first. Which languages must it support? Do you also need a DAM system for your digital assets, or an integrated platform that covers both? Which systems have to connect by API? Is the solution genuinely AI-ready — does it actually make structured data available to AI applications? And how flexibly can it be extended later, as new markets, channels and processes arrive? Integrated systems such as Pimcore make the start easier, because there are no separate tools to wire together.
Clean your data. Before you migrate, find and fix the errors and inconsistencies sitting in your data. The step is unglamorous, and it's decisive. Migrate chaotic data into a new system and all you have is chaotic data in a new system.
Choose a vendor. A PIM system is a long-term commitment. Choose on more than today's requirements, and keep AI, new channels and changing processes in view. The right vendor also keeps implementation inside the time and budget agreed. Weigh these points as you choose: How does the offer compare with other PIM vendors? Does the vendor know your industry, or comparable use cases? Can they support the use cases you actually have? How quickly does a first use case reach production? Is the platform built on open standards, and will it extend flexibly over the long term? Can your business teams adapt data models and workflows themselves, or will you need developers permanently? Once you have a shortlist, ask for quotes and a personal demo. The most revealing demo is the one built on your own use cases and sample data. Work out the total cost as well, including licences, implementation and ongoing maintenance. Verified user reviews help you narrow the field, for instance in the Product Information Management (PIM) category on OMR Reviews.
Test, implement and monitor. With the decision made, implementation begins. Migrate a portion of your products first, so you can test every function. That confirms the system runs properly and shows you early what still needs adjusting. Start training your first colleagues during this phase and watch how they get on with the new system.

If testing goes smoothly, you roll the software out to everyone. And then? Implementation isn't finished. A PIM system grows with your company. Extend it step by step with new use cases, channels and automations. Every new data source, every extra sales channel and every further automation raises the value for the business as a whole.

These are the best PIM systems

Demand for high-quality product data keeps growing, and the choice of PIM systems with it. Here are some of the best PIM software options:

The best PIM systems at a glance

PIM systems: a must for every company

B2B or B2C, high-quality data is the backbone of any business. That's precisely why PIM systems {{VENDOR_SLOT}} matter so much now. PIM software holds your data in a central hub and keeps every piece of product information accurate, current and consistent. Your team is spared manual data entry and upkeep. Data silos dissolve, and you keep control of all your product information and digital assets. Along the way you also build the data foundation your AI plans depend on. And thanks to use-case-based implementation, no-code configuration and API-first architecture, none of it needs a months-long IT project in the diary.

Would you like to get to know more PIM systems? OMR Reviews holds an extensive list of PIM vendors, where you can research every solution and use verified user reviews to choose the right tool for your requirements.

Frequently asked questions about implementing a PIM system

Which PIM system is easy to use and quick to implement?

Look for two things: a no-code interface and a use-case-based approach to implementation. Systems where business teams configure data models and workflows themselves are noticeably easier to live with day to day. Solutions that need IT resources for every adjustment slow you down instead. Cloud-native platforms such as viingx often have a first use case live within a few weeks.

A proper practical test matters here. Ask the vendor to show you, in the demo, how you would create a new data field yourself. If that takes a developer, you know what you're signing up for.

Which PIM systems can be connected by API?

Most modern PIM systems offer interfaces, but the depth is what counts. API-first means every function of the platform is available through the API, not just some of them. Look for REST APIs, ideally alongside GraphQL and webhooks for event-driven processes. That's how you connect ERP, shop system and other tools without developing expensive bespoke integrations. It's worth asking vendors about ready-made connectors for the systems you already run, too.

Which PIM systems are genuinely AI-ready, rather than just marketing?

"AI-ready" now appears in almost every product brochure. Three questions will tell you whether there's substance behind it:

Do product data, assets and content sit in one shared, structured data model? AI needs context, not just raw data.
Can AI reach that data directly, for example through open standards such as MCP, which lets AI agents communicate with the system?
Are AI features built into the workflows, for copy generation or translation say, rather than bolted on as an isolated add-on?

A vendor who can answer yes to all three means it.

Tool Implementation

Author

Christoph Könninger

Product Information Management (PIM)

Christoph Könninger ist Director Business Development bei viingx, einem Marketing Content Hub, der PIM, DAM und Headless CMS in einer Plattform vereint. Er verantwortet den Ausbau von Kundenbeziehungen und strategischen Partnerschaften und begleitet Unternehmen bei der Digitalisierung und Transformation von Marketingprozessen. Sein Schwerpunkt liegt auf der Vernetzung und Automatisierung von Produktinformationen, Content und Prozessen – vom Daten-Onboarding bis zur Bereitstellung in Marketing- und Vertriebskanälen. Ein besonderer Fokus seiner Arbeit ist heute der Einsatz von KI und Agentic AI.

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