SOASTA is now delivering performance insights for digital businesses with the addition of Third-Party Resource Analytics, Conversion Impact and Activity Impact scores, Session Path Analysis, and Predictive Analytics from SOASTA’s Data Science Workbench (DSWB) platform.
Brands can now improve revenue and deliver great customer experiences by improving their digital performance in real time with precise insights based on their real user data. With this release, SOASTA is evolving how companies view their user events, enabling them to make the best decisions for their digital business. SOASTA‘s data-driven approach creates a baseline for Digital Performance Management; out of this data, companies can more effectively manage their digital assets.
Built on data from SOASTA mPulse, which collects all user performance data from web assets, DSWB allows enterprises to:
- Understand exactly how many third-party resources make up their pages
- Identify the most problematic third-party resources needing remediation across a website
- Prioritize which pages and resources to focus on first
- Find out which domain servers are responsible for the greatest performance issues
Third-Party Resource Analytics
Because SOASTA’s DSWB now offers deep analytics and powerful visualization capabilities for third-party resources, digital businesses have the ability to easily manage third-party resources which were previously out of their control and negatively impacted site and application performance.
“Today, most commercial web and mobile user experiences depend heavily on third-party content to deliver everything from syndicated content to video to advertising to interaction with social media,” explained SOASTA Executive Chairman and Founder Ken Gardner. In fact, sites often have 50 percent or more of their resources originating from third parties, creating persistent challenges in performance management.
“It is quite common for us to discover that customers and prospects don’t know how many third-party resources are being used and where, much less the impact of those resources on site performance and, ultimately, user outcomes,” Gardner explained. “In other words, if you’re not managing the performance of third parties, you’re not managing your company’s digital performance.”
SOASTA third-party analytics addresses this challenge by analyzing detailed information about each resource loaded on a page, the domain that served it, the type and size of the resource, and performance information for that resource. Resources served from third-party domains are available for analysis together with or separate from first-party domains.
Conversion Impact Score and Activity Impact Score
The Conversion Impact Score and Activity Impact Score offer the industry’s most effective method to prioritize page group optimization by user sensitivity to performance, relative to conversion and session length. Both visualizations provide clear guidance to teams wanting to identify the highest-priority pages for remediation and fix the pages most important to their company’s business first.
“Marketing and eCommerce teams that look to customer data and analytics to drive better marketing, customer experiences and sale completion rates know that along with content, offers and design, app performance also drives customer success,” wrote Milan Hanson and James McCormick of Forrester Research in the February 2016 report, Brief: Take Application Performance To The Next Level With Digital Performance Management. With the Conversion Impact and Activity Impact scores, any company relying on marketing campaigns and conversion for their revenue streams has a powerful option that connects IT and business segments around their business goals.
Session Path Analysis
Session Path Analysis shows the paths users are taking through an application and the performance of those pathways. It helps customers understand how users enter and navigate through a site while also illustrating the performance impact of each page in the session. This function offers value by allowing teams to understand how performance affects user sessions, for both users converting or users abandoning the site.
Predictive Analytics
DSWB’s predictive analytics capabilities are based on historical trends within a company’s web properties. Tolerance bands are modeled from a company’s entire performance analytics history and drive “smart alerting,” allowing IT Ops and Marketing teams tracking campaigns to make better decisions in real time about performance remediation and changes to campaigns as they run. This is accomplished by comparing real-time data to machine learning models benchmarked from a company’s entire performance history, regardless of industry. According to the Forrester report cited above, “Firms want predictive analytics that bind together performance and business data to produce actionable insights for business decisions.”
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