Self-service customer data analytics just got easier, faster and a lot more accurate!
360Science today introduced an all-new integration for Alteryx, featuring the world’s most advanced customer data matching engine, and delivers groundbreaking performance with 360Science’s new In-memory architecture.
If you use Alteryx to analyze customer data – you need to see 360Science, because It makes unifying contact data in Alteryx EASIER, FASTER and A LOT MORE ACCURATE! It’s like nothing you’ve ever seen before!
When it comes to self-service analytics – Alteryx is awesome! But.. trying to match and unify contact data in alteryx hasn’t exactly been easy. As a matter of fact it’s been hard.
Alteryx, relies on conventional matching algorithms like Soundex and Levenshtein, and creating substring match keys to find fuzzy and phonetic matches.
It’s a slow, tedious, iterative process of trial and error, playing with various algorithms and matchcodes just to figure out how to get ‘adequate’ results.
360Science’s integration with Alteryx
360Science’s integration with Alteryx fundamentally changes how you do customer data analytics – with none of the data wrangling, or the toolbox of regular expressions to extraction, transformation and standardize data before matching it.
With 360Science, you can pull contact data—from any source of data you care about—into a single, intuitive platform for matching. This enables you to see customer data matches in context, and leverage data in ways never before possible.
“We built our Alteryx integration with the Data Analyst in mind”, quoted Rob Heidenreich – 360Science CEO. “We’ve reduced the level of expertise, steps, complexity, and the sheer number of transformations required to match customer data – while significantly increasing the accuracy of matching”.
360Science Matching Engine can easily match data in different formats, process data that has not been corrected, normalized or standardized. It will simultaneously process data from multiple different sources, in different formats, and it’s amazingly tolerant to the wide variations specific to customer data – even on large datasets from disparate sources!
It will match, dedupe, suppress, merge and group, and even identify Individual level, household level, and business level matches all in one routine – without the need to rerun analysis, create a new matchcode or generate new match keys on the data! #gamechanging!
It easily scales to processing on “hundreds of millions” of records – to put that in context it can match on a million record database in less than 10-seconds! Yeah…. it’s FAST!