Cloud CRM solutions have long since become mainstream and expanded beyond their initial foothold in small and mid-sized enterprises. Today B2B and B2C companies in many industries are eyeing cloud CRM solutions for their call center, their sales force and more. These CRM solutions offer the classic benefits of a cloud offering—multi-tenancy, usage pricing, location transparency, network access and high availability. What these solutions often do not offer, however, is advanced analytics. Typically limited to reporting and dashboards, many cloud CRM solutions do not allow companies to maximize the value of their data. The analytics that are available in a typical cloud CRM solution assume that users have the necessary decision-making expertise as well as the time required to make these decisions. In a typical high-volume call center environment, neither of these assumptions is reasonable. What companies using these CRM solutions need is predictive analytics, specifically predictive analytic solutions designed to drive better decisions in real-time. Delivering predictive analytic solutions in a cloud CRM environment, however, has its own challenges. Those adopting cloud CRM solutions don’t want (nor have the budget) to hire analytics teams to build predictive analytic models using traditional techniques or have to move their cloud CRM data to an on-premise analytic environment. They also don’t want predictive analytic models “in the lab,” they want business-friendly decision-making solutions powered by sophisticated predictive analytics. To be successful with cloud CRM, these companies need predictive applications for the cloud, in the cloud. Predictive Analytics in Cloud CRM