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Predictive analytics encompasses a variety of statistical techniques from modelling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events.
In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many variables and assess risk or potential to guide decision making.
Predictive Analytics is a hot topic but, unfortunately, there is a great deal of confusion about what it is and how it fits into marketing research. This webinar will clear up these misunderstandings and offer practical tips and guidelines for marketing researchers.
On completion of this webinar, you will learn:
Webinar Time: 1-hour webinar
Speaker: Kevin Gray
Kevin Gray is a marketing scientist who has been in marketing research for more than 25 years. Kevin has worked for The Nielsen Company's customized (CR) division, Kantar Research International and McCann Erickson as well as on the client side.
In 2008, Kevin established Cannon Gray, a Tokyo-based marketing science and analytics company that partners with clients, marketing research agencies, consultants and ad agencies located in many regions of the world.
As a member of the American Marketing Association and the American Statistical Association, Kevin is always keen to learn about innovations in marketing research and to borrow ideas from other disciplines.