Product data is no longer just operational. It is a strategic infrastructure.
It powers digital shelves, feeds marketplaces, enables personalization, and increasingly supports AI-driven and agent-based commerce.
The quality and structure of your product data directly influence how competitive your business can be across channels.
But while commerce is evolving rapidly, many companies still treat product data intake as an afterthought.
Struct PIM’s new Data Extraction feature is built to change that.
Data Extraction enables product information to be captured directly within Struct PIM and automatically aligned with your product model.
Incoming information is mapped, organized, and governed inside the PIM - before it flows into the rest of your commerce ecosystem.
Streamline how product data enters your PIM
Product data often comes from PDFs, supplier catalogs, or technical documents.
The format varies, the structure is inconsistent, and the information is rarely aligned with your product model.
Traditionally, this leads to copy-paste workflows, spreadsheet clean-ups, and manual mapping into your PIM.
The process is time-consuming, repetitive, and difficult to scale - especially when onboarding large assortments or multiple suppliers at once.
When onboarding 500 new SKUs from three suppliers, manual mapping is not just inefficient - it is a growth constraint.
With Data Extraction, product information is pulled directly into Struct PIM and automatically structured according to your product model.
This means:
- Faster onboarding of new products and suppliers
- Less time spent on repetitive admin tasks
- Fewer manual errors
- Shorter time-to-market
Data intake becomes structured and standardized from the moment information enters the PIM.
It is aligned with your product model, governed by your rules, and ready to be used across commerce touchpoints.
Future-proof your commerce foundation
AI, automation, and standard protocols like UCP and ACP are raising the bar for product data. But intelligent systems are only as strong as the data behind them.
If product information is inconsistent or poorly structured, it limits automation, weakens AI outputs, and slows expansion into new channels.
Data Extraction helps ensure that incoming data is aligned with your product model from the start.
Information becomes structured and governed before it reaches your webshop, marketplaces, or AI-driven recommendation engines - reducing errors, inconsistencies, and rework downstream.
This positions your PIM not as a passive storage system - but as the operational backbone of scalable, AI-ready commerce.
Data Extraction doesn’t just save you time - it makes your product data ready for the rise of agentic commerce.
You can read our deep dive on what Google’s UCP means for PIM in the age of agentic commerce here.
Conclusion
As assortments grow, suppliers increase, and AI-driven commerce becomes standard, manual data intake simply does not scale.
What once was manageable quickly turns into a bottleneck that slows launches and limits innovation.
Data Extraction transforms your data intake from manual effort to controlled automation.
It removes friction at the source, ensures structural consistency from day one, and strengthens your foundation for automation and AI.
In a landscape moving toward agentic commerce and standardized data protocols, structured product data is no longer optional. It is the price of entry.
With Data Extraction, Struct PIM ensures your product data is ready for what comes next.
See how Struct PIM turns structure into speed in our webinar, A Brief Tour of Struct PIM, below.
