Arm Treasure Data Announces Audience Suite

Arm Treasure Data today announced Audience Suite, a set of applications designed to visualize, segment and analyze customer data, to be used alongside the Big Data profile set marketers already have in Treasure Data.

“Marketers now have an increasing number of tools that help them collect, unify, and analyze customer data, but none that also make it easy for them act on the insight that data shows,” says Erik Archer Smith, marketing director, ABM at Arm Treasure Data. “With Audience Suite, we’ve made it easier for marketers to take immediate action on real-time customer segments, and our breadth of integrations means that insights can be activated in the tools that marketers already use, and likely have mission-critical processes built around.”

Audience Suite has four key features. First, it enables users to bring up a complete customer profile on a single screen, including visualizations highlighting total numbers in an audience, new customers, and growth trends, as well as an interface that allows users to review full profiles of every customer with an eye on quickly assessing attributes and behaviors.

The second key feature is Segment Builder, a guided segmentation experience that includes a full set of data with actions taken and not taken, the ability to create segments and automatically update them based on real-time actions taken by website visitors, and the ability to immediately personalize content, offers, and messages via interactive screens that automatically update with profile counts and statistics.

Audience Suite also features artificial intelligence capabilities for predictive analytics and scoring. These include embedded machine learning logic and visual wizards to assist users in building a predictive scoring model; guided predictive scoring that can be incorporated into new or existing segments; built-in machine learning libraries that support algorithms for recommendations, categorization, and language processing; and built-in statistics for enhancing and checking the accuracy of predictive scoring models.

Finally, the suite has a real-time personalization feature that allows users to update customer profile and segment data in real time, with the ability to integrate with tools including Adobe Target, Optimizely, and Google Optimize.

“Our ability to create segments using real-time, granular data for both online and offline data-sets is pretty unique,” Smith says. “I think most customer data platforms today are getting pretty good at segmenting online data with some granularity. But our ability to blend in granular, ‘event level’ data for online, offline data, ‘batch’ data, partner data, or even IoT data sets, and then enable marketers to build segments from all of these combinations is one of the things that really helps us stand out.

“This is important because when you think about what it takes to truly personalize the customer experience at scale, you can’t do this with the same old data sets; you need to be able to take action on the precise things that make each customer unique,” he adds. “Often those insights only come when you incorporate data outside of your typical channels.”

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