Catalina Taps IBM Analytics to Aid in Digital Transformation

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Dec 17, 2018, 08:00 ET

ARMONK, N.Y., Dec. 17, 2018 /PRNewswire/ -- IBM (NYSE: IBM) announced today that Catalina, the market leader in shopper intelligence and personalized digital media, has adopted the IBM Integrated Analytics System (IIAS) as a key pillar of its expanding analytics program to help provide its clients increasingly more relevant shopper insights.

Catalina, the pioneer of personalized digital marketing, has been helping consumer packaged goods (CPG) brands and retailers turn shoppers into buyers with targeted marketing solutions driven by data analytics since 1983. The company is embarking on comprehensive digital transformation to enable retailers and brands to seamlessly connect with consumers regardless of their location, whether in-store, online or via their mobile devices, anytime and anywhere.

A key piece of the transformation is the IBM IIAS, a unified data system designed to give users fast, easy access to advanced data science capabilities, as well as the ability to work with data across hybrid multiclouds, which are a mix of public and private cloud environments, as well as traditional on-premises IT. The high-performance system comes with a variety of data science tools built-in, and because it is based on the IBM common SQL engine, clients can use the system to easily move workloads from on-premises to cloud environments to begin automating their businesses with machine learning.

"Catalina sits squarely at the intersection of marketing, technology and analytics," said Wes Chaar, Chief Data and Analytics Officer at Catalina. "As part of our broader data science strategic initiative, Catalina is leveraging IBM's technology to power more meaningful outcomes from Catalina's analytics solutions, from personalization and consumer choice modeling, to revenue management and multi touch attribution – all to perform at optimum levels. The solutions we are building are critical for our customers because they optimize media and promotional offerings for every single consumer, and enable seamless, integrated user experiences that drive results."

Catalina partners with more than 10,000 of the world's leading CPG brands across every major category to deliver meaningful value for shoppers anytime, anywhere. The company's personalized digital media networks and shopper intelligence insights lead to more effective consumer engagements.

As retailers and brands continue to invest in insights-driven marketing programs – to help them do everything from engage the right shoppers and increase sales lift and loyalty, to drive both visits and "basket" sizes – data science is at the core of Catalina.

"Catalina is immersed in data, managing and extracting insights via data science from ever increasing volumes," said Seth Dobrin, Vice President and Chief Data Officer, IBM Analytics. "And its work with the IIAS is a great example of how the system can help streamline their analytics work today, and easily scale to support future growth."

In addition to the aforementioned features, IIAS comes with Data Virtualization, a new built-in capability that enables people to write analytics queries that can access data anywhere across the enterprise. The system also features IBM fast data movement, which enables organizations to easily move data between Hadoop clusters and the IIAS, extending and scaling their processing environments.

About Catalina
Catalina's personalized digital media drives lift and loyalty for the world's leading CPG retailers and brands. Catalina personalizes the consumer's path to purchase through mobile, online and in-store networks powered by the greatest shopper database in the world. Catalina is based in St. Petersburg, FL, with operations in the United States, Europe and Japan. To learn more, please visit www.catalina.com or follow us on Twitter @Catalina.

About IBM
For more information visit IBM Analytics.
For more on this story, read the IBM THINK Blog.

Contact
Michael Zimmerman
IBM Media Relations
[email protected]
(585) 698-9974

SOURCE IBM