“I was doing “data science” long before that name was used — data mining, knowledge discovery in databases, business intelligence, and OLAP are all somewhat deprecated terms,” say Gutierrez. “I’ve always been data-centric in my professional life, which began after my degree program in mathematics/computer science at UCLA. So now with the fancy new monikers like “data science,” “machine learning,” and “big data,” I’m pleased that what I’ve been doing for so long has developed such wide exposure and interest.”
The first four installments of the Big Data & Customer Intelligence series focused on predicting and influencing customer behavior, looking at determining customer value, and understanding your customer’s social influence. In this final article of the series, we’ll take a hard look at exploring customer sentiment which is another important element of Computational Marketing.
Over at The Register, Dan Olds writes that Big Data is powering amazing fortune-telling capabilities for sports at the Prediction Machine. “My pal Rich Brueckner and I had a chance to interview PredictionMachine.com founder Paul Bessire as part of our Radio Free HPC podcast a few weeks ago. In the programme, Paul discusses the genesis of the Predictalator and how he turned his master’s degree in quantitative analysis into a full-time business. Along the way, we talk about what’s involved in analysing sports and how they arrived at their winning formula. It’s interesting listening for anyone who has ever been curious about applying scientific methodology to sports.
The first three installments of the Big Data & Customer Intelligence series focused on predicting and influencing customer behavior and also looking at determining customer value. In this article, we’ll take a look at understanding your customer’s social influence and taking action on that knowledge which is another important element of Computational Marketing.