Adobe Introduces Greater Context to its Advanced Analytics Products

SAN JOSE, Calif., – November 1, 2017 – Building a relevant and successful business comes with a multitude of challenges, not the least of which is how to thrive in the face of competition. One of the most crucial elements to growing a business is having a deep analytical understanding of your customer base. Leading brands find that analytics powers every decision, from the strategic to the tactical; recognizing that a single valid data point could create the competitive edge that means the difference between success and failure. Whether a firm has a centralized data science team, or a single analyst, organizations need to democratize data to ensure it gets to every worker who is making decisions for the company.

To address these challenges, Adobe (Nasdaq:ADBE) today debuted a series of innovations which arm teams and workers with intelligence that can be curated for roles throughout the organization, leveraging advanced analytics and Adobe’s data management platform (DMP), Adobe Audience Manager. Building on Adobe Analytics’ heritage of enabling enterprises to move from insight to action instantaneously by uniquely integrating insights and action, the new capabilities include Context-Aware Sessions, Audience Analytics, enhancements to Analysis Workspace (Adobe’s easy-to-use data discovery and analysis tool), as well as virtual report suite updates for mobile teams. These new capabilities enable increased collaboration, faster analysis and improved customer intelligence, allowing high-growth brands to derive meaningful insights faster, and with more precision.

“Adobe is the leader in marketing analytics, with thousands of brands leveraging our tools in unique and advanced ways,” said Bill Ingram, vice president, Adobe Analytics Cloud. “We are the only company that provides in-depth behavioral pathing and powerful segmentation that’s truly accessible to users at all skill levels, and today we’re ensuring that the analysis has even greater context to help drive business success.”

Nearly two-thirds of the Fortune 100 turn to Adobe Analytics Cloud to address today’s digital challenges, with the number of customers more than doubling between 2014 and 2017. These leading brands include G6 Hospitality, Major League Baseball, Home Depot, Carnival, ASOS.com and Royal Bank of Scotland.

“Our guest’s experience, from searching cruise destinations on a mobile device, booking an excursion on our Web site, and ultimately embarking on one of our ships is paramount to our success,” said Aaron Fossum, director of digital analytics at Holland America. “Adobe Analytics Cloud has transformed our engagement metrics, and allowed Holland America to treat each traveler as an individual versus just a profile. In just a few weeks of leveraging Audience Analytics, we’ve been able to improve the efficiency of our direct-response buys by 30%, ultimately impacting our bottom line by helping to identify which guests are the most responsive to our marketing activities across channels.”

New features in Adobe Analytics include:

To learn more about these and many other new capabilities in Adobe Analytics, visit this blog and watch this video.

About Adobe Analytics Cloud

Adobe Analytics Cloud, part of Adobe Experience Cloud, is the customer intelligence engine that powers experience businesses by enabling them to move from insights to action in real-time, uniquely integrating audience data across all Adobe clouds. Adobe Analytics Cloud, which leverages privacy by design, combines Adobe Analytics, the industry-leading solution for modern customer intelligence and precision audience segmentation across all marketing channels and Adobe Audience Manager, the industry’s leading data and audience management platform. Built on the Adobe Experience Platform, which provides open APIs, a standard data model, and Adobe Sensei, Adobe’s unified AI and machine learning framework, Adobe Analytics Cloud enables brands to better capture, aggregate, rationalize and understand vast amounts of their own disparate data and then translate that data into singular profiles of their customers.

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