High-accuracy product matching across thousands of datasets.

The challenge

Profitero, a commerce analytics company, ingests product data from a very large number of retailers and sources and needs to match records to a common product identity with high accuracy. Inconsistent identifiers, titles, and attributes across thousands of datasets made reliable matching at scale hard to sustain with rules alone.

The approach

Paladio applied product-matching and normalization agents to resolve records across sources — reconciling identifiers, normalizing attributes, and deduplicating — to produce a consistent, high-confidence match across the dataset landscape.

The results

Match accuracy reached 80%+ across 1,000+ datasets, improving the reliability of the analytics built on top of that matched data.