You have been predicted.
Companies, government, universities, law enforcement. All are using computers to predict what you will do.
Will you click on the link in the email?
When will you die?
Will you pay your credit card bill on time?
Are you pregnant?
Dr. Eric Siegel recently released Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die. It’s a fascinating book that has surprisingly broad ramifications for all of us. Eric is a former Columbia University professor, the founder of Predictive Analytics World and Executive Editor of the Predictive Analytics Times.
Let’s start with the definition. What is predictive analytics?
It’s technology that gives organizations the power not only to predict the future, but to influence it. The shortest definition of predictive analytics is my book’s subtitle, the power to predict who will click, buy, lie, or die. Predictive analytics is the technology that learns from data to make predictions about what each individual will do–from thriving and donating to stealing and crashing your car. By doing so, organizations boost the success of marketing, auditing, law-enforcing, medically treating, educating, and even running a political campaign for president.
Why should the average person care about predictive analytics?
Prediction is the key to driving improved decisions, guiding millions of per-person actions. For healthcare, this saves lives. For law enforcement, it fights crime. For business, it decreases risk, lowers cost, improves customer service, and decreases unwanted postal mail and spam. It was a contributing factor to the reelection of the U.S. president.
Let’s jump to politics then. How did President Obama’s campaign gain an edge by using persuasion modeling?
The Obama campaign’s analytics team applied persuasion modeling (aka uplift modeling) in the same way it can be applied to marketing: drive per-person (voter/customer) campaign decisions by way of per-person predictions. If an individual is predicted to be persuadable, then make campaign contact (e.g., a knock on the door). By utilizing resources (campaign volunteers) more effectively in this way, the campaign enacted the new science of mass persuasion. They proved this won them more votes, within swing states and elsewhere.
Everyone is talking about “big data” but data on its own isn’t interesting or useful. You explain how data can show incredibly interesting insights including the fact that if you retire early, your life expectancy drops. Tell me more about that and what else we’ve learned from it.
Beyond the great hype around so much data, the real question is what to do with it. Answer: use data to predict human behavior.
The whole point of data is to learn from it to predict. Talking about how much data there is misses this point. What is the value, the function, the purpose? The one thing that makes the biggest difference to improve how organizations operate is to predict.