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SOASTA Extends Digital Performance Management Platform with Enhanced Predictive Analytics and Cloud Testing

soasta_logoSOASTA, a leader in performance analytics, announced its Fall 2016 Release, extending its Digital Performance Management (DPM) platform with the introduction of deep data science integration across the product portfolio; correlation with performance metrics and key marketing analytics tools; expansion of predictive analytics into new verticals; and enhanced Single-Page Applications (SPA) support for performance monitoring and load testing.

Only SOASTA is bridging the three worlds of business, customer experience and IT performance metrics,” said SOASTA CEO Tom Lounibos. “With the Fall 2016 Release, SOASTA DPM gives executives deeper insights into products, regions and customers, allowing decisions to be made on real data and not on assumptions. Beyond being better informed, DPM is actually changing the process of strategic decision-making.”

The Fall release also illustrates SOASTA’s commitment to “BizOps,” breaking down silos that exist between technical and business teams and allowing them to frictionlessly pursue a common goal – delivering an excellent customer experience and incremental revenue.

BizOps offers a holistic view of a company’s performance, aligning strategy, business and operations across an enterprise to ensure that they work in concert to achieve goals,” Lounibos explained. “We understand the business impact of improved collaboration and the most important priorities: unlocking new growth, driving strategy alignment, and building a strong and stable infrastructure.”

Fall Product Release Highlights

  • The Fall release features deeper data science integration and expanded capabilities designed for analyzing desktop and mobile traffic. Also with this release, SOASTA mPulse becomes formally powered by SOASTA’s data science engine, which allows for RUM-based testing and integration merged with mPulse dashboards, real-time campaign performance, and real-time visibility and correlation with key marketing analytics tools – Adobe Analytics, IBM Coremetrics and Google Analytics.
  • Already a key part of mPulse predictive analytics, the “what-if” dashboard now offers expanded functionality that enables users to select any conversion or revenue metric, such as session length or duration, bounce rate, and non-revenue-related conversions. This takes predictive analytics to a new level for verticals outside of e-commerce/retail. Most importantly, IT operations can now accurately forecast the value of their web and mobile performance improvements.
  • With SOASTA’s new SPA support for performance testing, customers can easily create performance load test for SPA sites using the Chrome browser recorder extension. It records SPA apps, catching the “page” changes that are no longer full HTML downloads but instead are smaller region changes that deliver a faster end user experience.
  • Measuring SPA is also improved with JavaScript error tracking, alerting and analytics in mPulse and provides, at a glance, critical error information, such as error rate, session experiencing errors, errors broken down by build, and recent error stack.
  • SOASTA can isolate first-party resources to determine the impact from third-party resources to remediate problems and establish SLAs for third- party vendors. “We have 14 third-party services on our site,” explained Jason Trester, senior director of site engineering for CNET, ZDNet and TechRepublic at CBSi. “We went through and analyzed every third-party tracking service on our site, extracting the data in a meaningful manner and establishing performance costs decisions about the relative performance gains and costs of adding new scripts. The cool thing about SOASTA is that it allows us to compare side-by-side the exact impact of every third-party script that we add to the site.”

With the Fall 2016 product release, SOASTA has further advanced its DPM capabilities, providing digital businesses with an unparalleled ability to deliver the best possible customer experience and business outcome in real time. Having contextual intelligence of business performance; enabling predictive intelligence, prioritizing resources, budget and time; and taking smarter actions based on data-driven recommendations are all critical components in this competitive digital business era.

 

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