We completely reimagined how contact data matching should work, and created a new engine – built from the ground up specifically for the challenges of working with customer data. We eliminated the complexity, difficulty, and uncertainty of traditional matching processes, and enable users of all skill levels – to quickly build and deploy highly accurate contact data matching models with greater accuracy and in a fraction of the time of conventional fuzzy matching methods.

We did this by building an engine that performs an interconnected three stage process – where the AI automatically analyzes, normalizes and tokenizes data- builds matching models, and intelligently Grades, Scores and Groups Matches. Each stage feeds the next –  intelligently applying multiple forms of data matching and analysis to the entire contact record.

360Science is amazingly tolerant to the wide variations specific to customer data – even on large datasets from disparate sources! Unlike ‘traditional’ applications  – 360Science doesn’t require data extraction, transformation, standardization, correction or manipulation prior to matching – and it doesn’t even require two different data sources to be normalized into a standard format or a target database! It doesn’t even need the same number of address lines in each record to compare the addresses.