Bad product data is a barrier between your customers and the products they’re trying to find. FactFinder’s new data enrichment solution uses LLMs to generate descriptive product tags and attributes that improve how products are discovered through eCommerce search.
Product data has always been the backbone of the eCommerce experience, yet most teams are stuck dealing with inconsistent formats, missing attributes and unreliable information. The result is poor discoverability, irrelevant search results, frustrated customers and missed sales. Each year, companies lose an average of $9.7 million due to inaccurate or incomplete product information. That’s revenue disappearing simply because customers can’t find the products they want.
Until now, solving these issues meant manual cleanup, long-running data projects or accepting underperforming product discovery. With AI-powered data enrichment, there’s finally a faster and more intelligent way to fix your product data.
Better data leads to better product discovery, and that means higher revenue and happier customers.
Why bad product data still holds eCommerce back
Most product discovery issues can be traced back to one root cause: bad data. Across industries, eCommerce teams face the same core challenges:
- Missing or incomplete attributes such as material, dimensions, color or use case
- Non-standard units that make comparisons difficult
- Inconsistent naming conventions across suppliers and systems
In many cases, manually fixing this at scale is simply not feasible. There aren’t enough hours in the day or people on the team to get through it all.
The impact is immediate and far-reaching. Poor product data leads to poor search and navigation. Shoppers can’t find what they’re looking for, results feel irrelevant and the overall experience breaks down. That directly affects conversion, customer satisfaction and revenue.
Introducing data enrichment by FactFinder
FactFinder’s new data enrichment solution gives eCommerce teams a faster, smarter way to take control of their product data. As a standalone tool, it works with any eCommerce tech stack (even if you already use another product discovery solution), so you can improve your data without reworking your entire setup.
For FactFinder Next Generation customers, it’s available right inside the familiar interface, with direct integration to your existing systems for an even smoother workflow.
Powered by large language models (LLMs), it analyzes existing product information and generates high-quality, structured data tags and attributes. Whether your catalog is missing key fields or just inconsistent, data enrichment helps fill the gaps with enriched tags automatically and at scale.
For every suggested tag, the system calculates a confidence score. Tags that exceed your defined confidence threshold are automatically approved, reducing manual effort. Everything else can be reviewed in an intuitive interface where business users can accept, edit or reject suggestions individually or in bulk. No technical skills are required, and manual data entry is also possible whenever needed. The system does the thinking, but you stay in control.
It’s the fastest, easiest way to go from incomplete or inconsistent data to a foundation that supports powerful, high-converting product discovery.
Benefits for eCommerce teams
With high-quality product data in place, eCommerce teams can shift their focus from cleaning up the basics to driving meaningful business outcomes:
What makes us different?
Most data enrichment tools rely on long onboarding cycles, manual input or expensive service layers. FactFinder takes a different approach.
This solution is AI-powered with confidence-based auto-approval, making it faster and more scalable than traditional methods. It enhances your existing data, creating entirely new context from minimal inputs like an image and a short product title.
There’s no need for lengthy collaboration with data teams or ongoing manual reviews. It’s quick to implement and delivers value from day one.
Data enrichment also works hand in hand with other innovations in your stack. For example, when combined with vector search, the enriched data provides essential context that helps increase result accuracy and relevance even further.
What’s next
This first release of data enrichment is just the beginning. While today’s version already automates key steps, future updates will reduce the need for manual input and make the experience even more hands-off for busy teams.
Planned enhancements will make data enrichment even more powerful:
- Unit standardization, so your technical specifications are always consistent and comparable across suppliers.
- Improved tag-based filtering, so shoppers can narrow results more accurately and find the right product faster.
- Use-case attributes, so customers can search and browse by the specific scenarios or needs your products address.
- Fully automatic enrichment at import, so new products are ready for discovery the moment they’re added to your catalog.
The goal is simple: to support a richer, more intuitive product discovery experience at every stage of the customer journey.
Ready to improve your product data?
Bad data shouldn’t hold your eCommerce experience back.
FactFinder’s data enrichment makes high-quality product information accessible, fast and automatic regardless of the platform or systems you use. It’s a smarter way to fix your data and unlock better product discovery across all your sales channels.
Book a demo today and see how quickly your product data can start driving more conversions.
