Business intelligence has always been a vital component in effective decision-making–but it’s now substantially smarter thanks to predictive analytics. Traditionally, to help solve business problems, organizations have targeted specific data and analyzed performance reports. Sure that works, but it focuses on the past and may provide only a limited view with limited value. With predictive analytics, you can leverage all your available data sources and discover patterns that unlock predictive intelligence to help you take the most appropriate action for achieving key business goals.
Predictive analytics help you understand how your organization is performing, and enables you to define rules for making better business decisions based on predicted outcomes. From uncovering customer pain points and operational risk to creating highly nuanced customer segments for targeted marketing, predictive analytics takes your business intelligence to the next level.
Predictive intelligence in action
Here are a few examples of how companies are applying predictive analytics to increase business value:
- Increasing marketing effectiveness by targeting people most likely to respond A major newspaper needed to increase online subscriptions without flooding customers with too many offers to avoid the appearance of spam. Using predictive analytics, we helped them analyze reading patterns of various news sections to determine which topics mattered most to certain customers. By identifying key characteristics for each customer segment, they could tailor offerings for specific subject areas to send the right message to the right people at the right time. Learn more…
- Improving retention with enhanced customer service based on behavioral segmentation A large mobile service provider wanted to reduce attrition by targeting which customers were likely to cancel service soon, so they could take preemptive action to retain their business. By developing predictive models based on specific behaviors for different groups of customers, they were able to craft offers that would likely appeal to certain segments. They then fed this information into the call center, so service reps could provide specific offers to high-risk segments to improve customer satisfaction. Learn more…
- Reducing employee turnover and hiring for success using predictive intelligence A leading financial institution used advanced analytics to increase the long-term effectiveness of hiring choices. By analyzing patterns in their HR data, they were able to identify which skills, experience, and behaviors were predictive of success on the job for frontline employees. They could use a similar approach to reduce employee attrition, finding solutions by analyzing a broad scope of data such as hiring information, Voice of the Employee feedback, intranet browsing patterns, and more.
While traditional business intelligence reports on what’s happened, predictive intelligence gives you the power to create business impact. By mining and analyzing all your available “big data,” you can develop reliable, repeatable models for predicting outcomes and actions that drive more profitable decision making.
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