Predictive Analytics Guide
What is Predictive Analytics?
Predictive analytics is information technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model which has, in turn, been trained over your data, learning from the experience of your organization.
Predictive analytics optimizes marketing campaigns and website behavior to increase customer responses, conversions and clicks, and to decrease churn. Each customer’s predictive score informs actions to be taken with that customer — data science just doesn’t get more actionable than that.
What’s the best way to learn about predictive analytics? There’s no better way to learn than from concrete case studies such as those presented by Fortune 500 analytics competitors and other top practitioners at the next Predictive Analytics World. In the meanwhile, start by taking a look through the resources listed below on this page.
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Read this rich, fascinating — surprisingly accessible — introduction by former Columbia University professor and Predictive Analytics World founder Eric Siegel, which reveals the power and perils of predictive analytics, showing how predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime-fighting and boosts sales. More info, excerpts, reviews, and press.
Machine Learning on Coursera – Free Access
Take “Machine Learning for Everyone with Eric Siegel” on Coursera, from the founder of Predictive Analytics World. This end-to-end, three-course series on Coursera will empower you to launch machine learning. Accessible to business-level learners and yet vital to techies as well, it covers both the state-of-the-art techniques and the business-side best practices. Click here to enroll for free.
The following short, published articles, written by the conference chair, are a great place to get started.
- Hands-On Guide to Predictive Analytics
Free access to the “hands-on” Addendum that appears at the end Eric Siegel’s book, “Predictive Analytics”.
- Predictive Analytics with Data Mining: How It Works
Get a handle on the functional value of predictive analytics for marketing, sales and product direction.
- Seven Reasons You Need Predictive Analytics Today
Predictive analytics has come of age as a core enterprise practice necessary to sustain competitive advantage. This definitive white paper, sponsored by IBM, reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics, namely Compete, Grow, Enforce, Improve, Satisfy, Learn, and Act.
- Hotlist of Training Resources for Predictive Analytics
This article summarizes a good collection of predictive analytics education options.
- Driven with Business Expertise, Analytics Produces Actionable Predictions
Run data mining as a business activity to generate customer predictions that will have a business impact. CRM Magazine’s DestinationCRM.
- Six Ways to Lower Costs with Predictive Analytics
This article delivers six ways predictive analytics lowers costs without decreasing business, thus transforming your enterprise into a Lean, Mean Analytical Machine. Example brand-name case study results are provided along the way. From BeyeNETWORK.
- Numerous interviews with and writings by Eric Siegel, founder of Predictive Analytics World and author of Predictive Analytics
- Uplift Modeling: Predictive Analytics Can’t Optimize Marketing Decisions Without It
To drive business decisions for maximal impact, analytical models must predict the marketing influence of each decision on customer buying behavior. Uplift modeling provides the means to do this, improving upon conventional response and churn models that introduce significant risk by optimizing for the wrong thing. This shift is fundamental to empirically driven decision making. This convention-altering white paper, reveals the why and how, and delivers case study results that multiply the ROI of predictive analytics by factors up to 11.
- Free book chapter: The Seven Practice Areas of Text Analytics
Presently, text mining is in a loosely organized set of competing technologies with no clear dominance among them. This book chapter organizes text analytics methods as seven complementary practice areas, showing how to select amongst them for your objectives.
Predictive Analytics World Conference
Predictive Analytics World is the leading event for machine learning consumers, managers and commercial practitioners. This conference delivers case studies, expertise and resources over a range of business applications of machine learning. For more on this conference’s scope, see About Predictive Analytics World.
Data Driven Government advances the deployment of analytics and data science within Federal, State, and Local government to reduce fraud, waste, and abuse, automate manual processes, and drive smarter decisions by extracting actionable insights from the vast quantities of data within government agencies. For more info see Data Driven Government.
Deep Learning World Conference
Deep Learning World is the premier conference covering the commercial deployment of deep learning. The event’s mission is to foster breakthroughs in the value-driven operationalization of established deep learning methods.
Machine Learning News
Machine Learning Times. The machine learning professionals’ premier resource, delivering timely, relevant industry-leading content: articles, videos, events, white papers, and community. The only full-scale content portal devoted exclusively to machine learning and its commercial deployment, the Machine Learning Times has become a standard must-read. Subscribe here.
www.KDnuggets.com: A comprehensive online portal and newsletter for data mining, including predictive analytics.
Subscribe to Predictive Analytics World event notifications and announcements.
Predictive Analytics Informative Interview
View succinct responses from Predictive Analytics World founder Eric Siegel that provide an overview of predictive analytics. Answers to the following questions are provided:
- Why is predictive analytics important?
- Isn’t prediction impossible?
- Is predictive analytics a big data thing?
- Did Nate Silver use predictive analytics to forecast Obama’s elections?
- Does predictive analytics invade privacy?
- What are the hottest trends in predictive analytics?
- What is the coolest thing predictive analytics has done?