モバイル広告主が「プログラマティック·メディアバイイング」を愛すべき 5 つの理由

モバイル広告主が「プログラマティック·メディアバイイング」を愛すべき 5 つの理由「プログラマティック·メディアバイイング」という単語がアドテク業界に登場して久しくなりますが、本当の意味をまだ多くの人が知りません。しかしこれから「プログラマティック·メディアバイイング」はアドテク業界の主流になりつつあり、モバイル広告主は取り残されないために今、その意味を把握しておく必要があります。

Three Ways Machine Learning Is Helping Mobile Advertisers

Machine learning is probably one of the most hyped words of the last few years, and rather justifiably so. The field is currently the subject of widespread theoretical research, practical industrial implementations as well as a few distant fears (most of them being about robots killing all humans).

Machine learning is typically defined as “a type of artificial intelligence (AI) that provides computers with the ability to do certain tasks, such as recognition, diagnosis, planning, robot control, prediction, etc., without being explicitly programed. It focuses on the development of algorithms that can teach themselves to grow and change when exposed to new data.”How is machine learning used in our industry? We sat down with two data scientists from AppLift, Dr. Florian Hoppe and Bruno Wozniak, to understand how machine learning algorithms are currently helping mobile advertisers drive campaigns more efficiently and cost-effectively. We selected three use cases: Real-Time Bidding (RTB), lookalike targeting and user data enhancement.