3 steps needed to bridge the gap between advanced machine learning and real-world marketing

Whether we realize it or not, machine learning is already a part of our everyday lives. Think about a simple Google search, a quick query to Apple's Siri, an afternoon visit to Facebook, or, of course, a great product recommendation on Amazon. As the prevalence of high-performance computing continues to grow, the thought of computers doing things we could only dream of is exhilarating and, for many, almost magical. This is especially true when it comes to marketing. Yet, as we apply machine learning to marketing and unique business goals, oftentimes all of that mystery and intrigue turn to disillusion and struggle with the practical applications.