The face of marketing research is changing. Using yesterday’s tools to gain marketing insights is akin to going to a gun battle with sticks and stones. Predictive analytics is emerging as the bridge between reasoned approach of MR and mindless iteration of big data analysis. To be relevant we need to meet the challenge.
Predictive analytics has come to the fore in the past few years because of big data, web analytics and availability of powerful open-source software like R. What was nearly impossible to do in predictive analytics just ten years ago can be done with ease now. Our results can be validated quickly and we can go much farther than sterile tests of significance.
But there is a lot of confusion about predictive analytics. What exactly is predictive analytics? Where does it fit in the spectrum of big data and web analytics? How to use predictive analytics effectively to gain marketing and consumer insights? How to make sure that your results are valid? How to make them relevant to marketers? This talk is designed to answer these questions and illustrate it with cases that have used predictive analytics successfully.
Dr. Chuck Chakrapani