Predictive Analytics

Astronomers are building a new array of radio telescopes that will generate an exabyte of data per day (an exabyte is a quintillion bytes; a byte is a single value, an integer between 0 and 255, often representing a single letter, digit, or punctuation mark).

Therefore, influence cannot be observed. We can never witness an individual case of persuasion with complete certainty. How then could we ever predict it?

employing analytical methods to predict treatment impact (i.e., medical influence) similar to the uplift modeling techniques used for marketing treatment decisions.

Must souping up model precision involve overwhelming complexity, or is there an elegant way to build and scale?

Beyond predicting departure, must a company secondarily predict how customers will respond when contacted? Must

Their PA projects include customer loss prediction, sales lead scoring, and supplier fraud detection.

Knowing who your “good” customers are—the ones who will buy more—may be nice to know, but it takes second place.

influence takes place across a group, but ascertain nothing about any one individual, so the choice of message still cannot be individually chosen

Among the competing approaches to machine learning, decision trees are often considered the most user friendly, since they consist of rules you can read like a long (if cumbersome) English sentence, while other methods are more mathy, taking the variables and plugging them into equations.