How to Revitalize Your PIM System and Drive Innovation with AI Agents

Many companies currently use Product Information Management (PIM) systems merely as operational tools for storing data, rather than leveraging their full strategic potential.

Aleks Amundsen
Senior Manager

+45 2222 2529

ala@immeo.dk

A common pattern repeats itself, when new technologies transition into operational roles, they gradually lose their original purpose as drivers of innovation. They shift into a support role, where operations and maintenance overshadow the original vision. This trend has also affected PIM systems, transforming them into passive storage points.

What if the PIM system could reclaim a prominent role within your business application ecosystem? What if PIM could once again become a strategic enabler for new business models with capabilities such as autonomously enhancing customer experiences through real-time insights? This is the future of PIM when coupled with AI agents.

Why are AI Agents crucial to modern PIM-systems?

Intelligent agents operationalize a Data-to-Experience strategy, bridging real-time insights with automated, scalable actions. They:


Integrating AI-driven agents into your existing PIM solution doesn't require building new systems—it demands a shift in perspective.

Consider adopting the "Innovation Lab" model prototype and test AI-enhanced product experiences based on your current data. Quickly learn where you can activate unused data insights to improve your processes and the overall digital customer experience.


Specific initiatives you can apply if it suits your business.

Agent-Driven Innovation in PIM: 4 Practical Use Cases

Agent Role:

  • AI agents assess regional market requirements, product completeness, and sales data to pinpoint exactly what product attributes or documentation need enhancement.

Impact:

  • Product information is precisely tailored to cultural, legal, and industry standards, accelerating market acceptance and compliance.


Concrete Example:

  • An agent identifies missing Environmental Product Declarations (EPDs) required in Nordic markets and auto-populates these fields based on historical data models.
  • It also recognizes low sales conversion in the DACH region and suggests enriched technical specifications to align with market expectations.

Agent Role:

  • Agents continuously analyze user behavior, search patterns, and interaction data to refine product classification structures.

Impact:

  • Product navigation becomes highly intuitive, ensuring users quickly find relevant items.


Concrete Example:

  • The agent detects high bounce rates on certain category pages and automatically proposes reclassification or introduces new relevant search synonyms to enhance discoverability.

Agent Role:

  • AI agents monitor ERP, CRM, and customer behavior data to dynamically publish tailored product catalogues.

Impact:

  • Catalogues remain consistently up-to-date and precisely targeted to specific buyer segments.


Concrete Example:

  • When a product category trends upward, the agent proactively generates a specialized catalogue for relevant sales partners.

Agent Role:

  • Agents use compatibility data, co-purchase history, and industry metadata to structure products around specific application scenarios rather than generic categories.

Impact:

  • Buyers receive bundled, contextually relevant product recommendations, enhancing solution-driven purchasing experiences.


Concrete Example:

  • An agent detects that certain compressors and fittings are commonly purchased together for cold storage applications and automatically creates pre-configured bundles.
  • Products suitable for clean room environments are automatically tagged based on their certification metadata, facilitating targeted marketing and sales efforts.

Governance is key

Remember: Governance is key when working with AI agents—you’re always in control. It’s your decision which tasks require approval and which can be automatically executed. Leveraging AI effectively can drive significant value, but remember to approach it thoughtfully and systematically, ensuring actions remain deliberate and aligned with your strategic goals.

Moving Forward with Agent-Powered PIM

To successfully move forward with Agent-Powered PIM, it's crucial to establish strategic ownership of your PIM system as a core component of your broader product strategy.


Are you ready to reboot and transform your PIM with AI agents?

Join our PIM Network Group

Join our PIM network group - a space to explore key topics, exchange insights, and solve real challenges together.

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Do you want to know more?

Contact
Simon Aisen Partner, Immeo

+45 2222 0260

sai@immeo.dk

sai
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