Predictive Analytics

once worked on an HP project that predicted the potential demand of its corporate clients—how many computers will the company need to buy, and how much of that need is currently covered by HP’s competitors?

The company challenged the world by requiring that the winner improve upon Netflix’s own established recommendation capabilities by 10 percent. Netflix is a prime example of PA in action, as a reported 70 percent of Netflix movie choices arise from its online recommendations.

Emotion is the goose that lays the golden eggs, hatching stock market movement—but not the other way around. There’s no chicken-and-egg cycle to be found.

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

In fact, it is usually what individuals have done that predicts what they will do.

By tapping the public’s mood and opinions, they’re trying to predict it all: Product sales. Top music hits. Movie box-office revenue. Academy Award and Grammy winners. Elections. Unemployment statistics.

Many of your everyday clicks contribute to the web’s constant testing of how to improve overall persuasiveness.

One time, Michael noted failure for certain groups within a direct mail campaign selling a home-equity line of credit to existing customers. For those groups, the campaign not only failed to cover its own printing and mailing costs, it in fact had the detrimental effect of decreasing sales, a slight downlift overall.

This win resulted from decreasing both the amount of direct mail that commanded no impact and the amount that instigated an adverse response.