Business metrics do a great job summarizing the past. But if you want to predict how customers will respond in the future, there is one place to turn -- predictive analytics. By learning from your abundant historical data, predictive analytics delivers something beyond standard business reports and sales forecasts: actionable predictions for each customer. These predictions encompass all channels, both online and off, foreseeing which customers will buy, click, respond, convert or cancel. If you predict it, you own it. The customer predictions generated by predictive analytics deliver more relevant content to each customer, improving response rates, click rates, buying behavior, retention and overall profit. For online applications such as e-marketing and customer care recommendations, predictive analytics acts in real-time, dynamically selecting the ad, web content or cross-sell product each visitor is most likely to click on or respond to, according to that visitor's profile.

This online training course goes from fundamentals and best practices to hands-on discussion of predictive analytics models and their applications.

• Applications: Business, marketing and web problems solved with predictive analytics
• The techniques, tips and pointers you need in order to run a successful predictive analytics and data mining initiative
• How to strategically position and tactically deploy predictive analytics and data mining at your company
• How to bridge the prevalent gap between technical understanding and practical use
• How a predictive model works, how it's created and what it looks like
• Evaluation: How well a predictive model works and how much revenue it generates
• Detailed case studies that demonstrate predictive analytics in action and make the concepts concrete
• Two tool demonstrations showing how predictive analytics really works

• Managers. Project leaders, directors, CXOs, vice presidents, investors and decision makers of any kind involved with analytics, direct marketing or online marketing activities.
• Marketers. Personnel running or supporting direct marketing, response modeling, or online marketing who wish to improve response rates and increase campaign ROI for retention, up-sell and cross-sell.
• Technology experts. Analysts, data scientists, BI directors, developers, DBAs, data warehousing professionals, web analysts, and consultants who wish to extend their expertise to predictive analytics.