IN THIS CHAPTER
Identifying some common use cases
Implementing recommender systems
Improving targeted marketing
Optimizing customer experience by personalization
Predictive analytics sounds like a fancy name, but we use much the same process naturally in our daily decision-making. Sometimes it happens so fast that most of us don't even recognize when we’re doing it. We call that process “intuition” or “gut instinct”: In essence, it’s quickly analyzing a situation to predict an outcome — and then making a decision.
When a new problem calls for decision-making, natural gut instinct works most like predictive analytics when you’ve already had some experience in solving a similar problem. Everyone relies on individual experience, and so solves the problem or handles the situation with different degrees of success.
You’d expect the person with the most experience to make the best decisions, on average, over the long run. In fact, that is the most likely outcome for simple problems with relatively few influencing factors. For more complex problems, complex external factors influence the final result.
A hypothetical example is getting to work on time on Friday morning: You wake up in the morning 15 minutes later than you normally do. You predict — using data gathered from experience — that traffic is lighter on Friday morning than during the rest of the week. You know some general factors that influence traffic congestion: