Back

Speaker "Saket Mengle" Details Back

 

Topic

Applying AI algorithms to help advertisers discover the most effective third party audience segments

Abstract

Marketers are looking for ways to economically use third-party data for customer acquisition rather than audience buying based on intuition. To date, this has not been effective because the incremental cost of buying audience segments. This talk discusses dataxu’s Open AI for Advertisers (OAIFA) algorithm, which is the first scalable ROI positive 3rd party data algorithm that can be used for customer acquisition. OAIFA allows advertisers to automatically evaluate the effectiveness of several thousand third party data segment using sophisticated AI algorithms, and add the most influential segments to dataxu’s machine learning models. Our extensive evaluation on hundreds of live campaigns demonstrates that OAIFA reduces the cost of customer acquisition by almost 30% while allowing advertisers to spend on third-party segments that are curated and updated by an AI algorithm. The talk provides an insight in our experiences when designing this algorithm, and how AI helped us solve a classic advertising problem.

Profile

Saket holds a PhD in Machine Learning from Illinois Institute of Technology, Chicago. He has worked in a variety of fields including text classification, information retrieval, large scale machine learning and linear optimization. He currently works as Senior Principal Data Scientist at Dataxu Inc., where he is responsible for developing and maintaining the algorithms that drives Dataxu’s real-time advertising platform.