Novel AI Approaches For Marketing & Advertising

Marketing and advertising are some of the functional areas where AI is expected to drive the most ROI for enterprises. Unfortunately, the industry is moving so fast that it's challenging for both marketers and technologists to keep up with all the research advances, much less apply them to pressing business problems. If these accessible AI research analyses & summaries are useful for you, you can subscribe to receive our regular industry updates below. If you'd like to skip around, here are the papers we featured: This paper describes a practical system for Multi-Touch Attribution (MTA) for use by a publisher of digital ads. We developed this system for JD.com, an eCommerce company, which is also a publisher of digital ads in China. The approach has two steps. The first step ('response modeling') fits a user-level model for purchase of a product as a function of the user's exposure to ads. The second ('credit allocation') uses the fitted model to allocate the incremental part of the observed purchase due to advertising, to the ads the user is exposed to over the previous T days. To implement step one, we train a Recurrent Neural Network (RNN) on user-level conversion and exposure data. The RNN has the advantage of flexibly handling the sequential dependence in the data in a semi-parametric way.