Product Matching Software
Automating product data standardization, attribute extraction, and classification can be easy.
With ProductMatch, intuitively make sense of complex, unstructured product and item data with advanced contextual recognition and machine learning.
Join 100+ Clients
- Get your free demo today.
"*" indicates required fields
Customer Stories
See what our customers say...
It’s not just the software which works very well for us, but the focus and knowledge that Data Ladder brings to the table
Thanks to Data Ladder we successfully cleaned up and matched our internal sales file with new leads, greatly improving efficiency and sales.
We could not do these reports before. Now, DataMatch has become a main staple in my suite of tools that I work with
Want to know more?
Check out DME resources
Merging Data from Multiple Sources – Challenges and Solutions
Oops! We could not locate your form.
Data Ethics in the Age of AI: Why Responsible Matching Matters More Than Ever
When AI systems deliver inaccurate or inequitable results, many people immediately assume that something went wrong in the algorithms. Rarely do we look upstream –
Why Data Interoperability Challenges Are Holding Back Your Insights – And What to Do About It
Every modern organization thinks it’s interoperable—until the data says otherwise. Your systems are technically connected. APIs are firing. Data is flowing. But when you zoom
Data Ethics in the Age of AI: Why Responsible Matching Matters More Than Ever
When AI systems deliver inaccurate or inequitable results, many people immediately assume that something went wrong in the algorithms. Rarely do we look upstream –
Why Data Interoperability Challenges Are Holding Back Your Insights – And What to Do About It
Every modern organization thinks it’s interoperable—until the data says otherwise. Your systems are technically connected. APIs are firing. Data is flowing. But when you zoom
Why Data Governance and Stewardship Are the New Cornerstones of Business Strategy
64% of organizations manage at least 1 petabyte of data and 41% manage at least 500 petabytes. But fewer than half (49%) of data practitioners
