Xactly AI Algorithm Predicting Sales Rep Attrition Available Now
SAN JOSE, Calif.--(BUSINESS WIRE)--Sep 20, 2018--Xactly, a leading provider of cloud-based sales performance management (SPM) software, today announced the immediate availability of its machine learning algorithm to predict sales rep attrition. Integrated with Salesforce, Xactly’s Sales Performance Artificial Intelligence (AI) platform applies machine learning algorithms to over 13 years of pay and performance data to analyze and predict the risk of future employee attrition. Leveraging a model of over 50 unique data elements, organizations can proactively address and prevent undesired sales attrition, reducing a significant business cost and safeguarding performance.
Customers now have the ability to leverage the power of Salesforce Einstein and Xactly Insights™ together, allowing sales leaders to become smarter and more predictive. With the ability to predict leading sales indicators using both customer as well as their own reps’ pay and performance data, sales leaders can: prioritize opportunities, prevent their top reps from leaving the organization and make real-time decisions to optimize overall sales performance.
“Xactly has harnessed the power of big data to provide organizations with a predictive, real-world AI application that they can easily implement and use today to ensure the productivity and health of their sales force,” said Christopher W. Cabrera, founder and CEO of Xactly. “By revealing which reps are at the highest risk of undesired attrition, Xactly allows organizations to take immediate steps – before they lose a top rep and impact their revenue attainment.”
Real-World AI Application Benefits Sales Organizations
Xactly’s platform includes over a decade of historical compensation insights garnered from thousands of customers. Leveraging this comprehensive and unique data set, Xactly Insights can capture and analyze dozens of key criteria associated with employee satisfaction, such as:compensation sales performance industry employee tenure company attrition levels
Integrating this information, Xactly Insights provides a data-based behavioral indicator to empower sales organizations to more effectively plan and manage teams and processes. Xactly’s sales rep attrition algorithm is the first in a number of planned AI applications to help enterprise companies optimize their SPM processes.
See Xactly Sales Performance AI Platform at Dreamforce
Attendees of Dreamforce, the most innovative technology conference of the year, can see a demonstration of Xactly’s sales performance AI platform at the Dreamforce Saleslodge being held at the San Francisco Marriott Marquis September 25-28. Contact Xactly for more information.
Xactly delivers a scalable, cloud-based enterprise platform for planning and incenting sales organizations, including sales quota and territory planning, incentive compensation management, and predictive analytics. Using this powerful sales performance management (SPM) portfolio, customers mitigate risk, accelerate sales performance, and increase business agility. Combined with Xactly Insights, the industry’s only empirical big data platform, Xactly empowers companies with real-time compensation insights and benchmarking data that maximize the bottom line. With an open, standards-based architecture, Xactly seamlessly integrates within an enterprise’s existing infrastructure, with the ability to work with any ERP, CRM, or HCM application, while meeting the highest enterprise standards in security, reliability, and privacy.
Salesforce and others are among the trademarks of Salesforce.com, Inc.
©2018 Xactly Corporation. All rights reserved. Xactly, Xactly Insights, the Xactly logo, and “Inspire Performance” are registered trademarks or trademarks of Xactly Corporation in the United States and/or other countries. All other trademarks are the property of their respective owners.
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CONTACT: Blanc & Otus Public Relations
Neil Torres, 415-856-5140
KEYWORD: UNITED STATES NORTH AMERICA CALIFORNIA
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SOURCE: Xactly Corporation
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PUB: 09/20/2018 08:00 AM/DISC: 09/20/2018 08:01 AM