Since 1994, online advertising has grown to a $113 billion industry worldwide and has been pivotal to the success of the mobile and World Wide Web. This success has arisen largely from the transformation of the advertising industry from a low-tech, human intensive, “Mad Men” way of doing work (which was commonplace for much of the 20th century and the early days of online advertising) to highly programmatic, optimized, mathematical, computer-centric, and performance-driven processes that form the backbone of many current online advertising systems.

To date, digital advertising can be divided into four generations: Generation One borrowed from offline techniques (human sales force) and pricing models (cost per thousand impressions, CPM); Generation Two leveraged automatic pricing models (via online auctions and cost per click, CPC, pricing models) and automatic targeting; Generation Three has focused on personalization (behavioral targeting, ad exchanges and real-time bidding for each impression) and on new personal media channels such as mobile and social media; and Generation Four is focusing on native and more engaging advertising experiences.

This talk, while reviewing the four generations of online advertising, will provide a clear and detailed overview of the business models and technologies that are transforming the field of online advertising primarily from statistical machine learning and information science perspectives in both the guaranteed and spot markets (e.g., real-time bidding). Open research questions will also be described.

Dr. James G. Shanahan is VP of Data Science and Chief Scientist at NativeX, a mobile ad network.