Posted on March 3, 2014
Online search generally follows power law and shows a long tail distribution. With powerful search engine consumers are very specific when searching for their products. Thus the long tail cannot be ignored and in fact largely determines the success of online marketing campaigns. I will look at the long tail problem at Orbitz and how we developed the Bayesian approach and ensemble model to tackle the problem. These methods have advantage over the typical clustering of tail method and can be easily applied to search engine marketing (SEM) and other long tail problems.
Dr. Wenqing Lu is leading an Advanced Analytics team at Orbitz Worldwide – building statistical models for online marketing. Prior to Orbitz, he was at eBay working on website testing and optimization in eBay’s global Experimentation group. He started his career as a statistician in the financial industry and has over 13 years of experience in the area of predictive modeling & data science. Dr. Lu has a Ph.D. in statistics from University of Wisconsin-Madison and B.S. in Operations Research from Fudan University.
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This article and slide show were made by industry experts and can also be found on ieondemand.com