Radius launches customer data platform for B2B

The company is evolving beyond its origins in predictive lead scoring, as those data intelligence categories begin to merge.

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Radius' depiction of multiple data sources for its new customer data platform, Unify.

Radius’ depiction of multiple data sources for its new customer data platform, Unify.

Radius, which has been a provider of predictive lead scoring, said on Thursday it is entering the growing space of customer data platforms (CDPs) with the launch of its Unify platform.

The San Francisco-based firm said this is the first CDP intended for enterprises that is entirely focused on B2B.

One question is how the new Unify profiles and data management differ from the ones Radius has previously maintained to provide recommended leads.

Historically, CTO Joel Carusone told me, Radius offered data integration with only four sources — Marketo, Eloqua, Pardot and Salesforce — plus the ability to import data through CSV files.

Now, Unify accepts data from any source via an API, such as customer interaction data from customer service centers. Additionally, he said, incoming data is now matched with the existing datasets in real time, whereas previously it might have required up to half an hour.

Carusone also noted that, in the past, new data was linked up through persistent identifiers like email addresses only to Radius’ existing data, but now it can be matched with any dataset, such as Dun & Bradstreet’s. Radius’ Network of Record contains profiles on about 18 million businesses and related individuals, which are constantly validated against new data provided by clients.

The result, he said, provides “more reliable models” for predicting leads or other purposes.

Related: Enterprise Customer Data Platforms: A Marketer’s Guide

While the golden master profile might live in the Radius CDP, any blended version can be pushed out to other platforms for implementation, such as Salesforce or data management platforms.

Senior Director of Product Marketing John Hurley said via email that predictive lead scoring was “an early categorization of a space (circa 2014) that’s changed and grown dramatically over the last four years.”

“We never loved the categorization,” he wrote, “as we’ve always been strongest in data integration, data management, channel integration and data sourcing with intelligence layered on top (segmentation, addressable market analysis, predictive scoring, etc.).”

He noted that some research firms are renaming the category in various ways, employing such terms as Data Providers, Data Intelligence — or Customer Data Platforms.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About the author

Barry Levine
Contributor
Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.

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