IBM Predictive Customer Intelligence solutions helps provide a consistent and profitable experience across all channels including marketing outreach, sales and customer service; and across all touch points whether online, through a call center, mobile apps, social media or in a store.
There are complex challenges that a data scientist might face in statistically modeling real-time decision-support scenarios in fast-moving athletic competitions. Each sport needs to be modeled on its own terms. A within-game decision-support predictive model for one sport cannot be applied
Medical professionals are between the proverbial rock and hard place when trying to determine whether, how and why patients are failing to comply with doctor's orders. On the one hand, their ability to help people depends on having intimate, current and accurate knowledge of people's physical
http://ibm.co/5stepsThis big question looms whenever and wherever practitioners all join together to discuss advances, changes and needs in the industry. While, in some ways, the answer is “yes"—because there is a need, a desire and a significant opportunity—in many ways healthcare organizations
Watson Foundations, an IBM Big Data & Analytics Platform, presents Acquiring, Growing and Retaining Customers with C Spire, a wireless provider who uses predictive analytics and decision management to identify when customers might leave and personalize experiences so they don't.
I’m looking forward to the upcoming Healthcare Analytics Symposium in Chicago next week (July 14-16) led by Health Data Management. During this analytics focused conference, we will hear from innovators who are leveraging big data and analytics in a variety of ways to solve real problems that touch
Prioritizing data mining projects is a delicate art, equivalent to the decisions that R&D managers face every single day. How should you prioritize your data mining efforts and allocate your limited resources most effectively? Most important, how do you decide what NOT to work on?
Nucleus Research examined XO Communications’s deployment of IBM Business Analytics and found it enabled XO to identify customers with a high likelihood to churn. XO client service managers used this predictive analysis to proactively contact those customers, improving customer retention and