Introduction to Predictive Analytics

Predictive analytics, artificial intelligence, and machine learning are trending buzzwords among application teams today. MIT Sloan Management Review reports that 91 percent of business leaders expect to see new business value from Artificial Intelligence (AI) implementations in the next five years. And predictive analytics is now the #1 feature on product roadmaps, according to Logi’s 2018 State of Embedded Analytics Report.

Predictive Analytics

But why is predictive analytics the “next big thing?” And what value could it offer your company?

In the Definitive Guide to Predictive Analytics, we offer a comprehensive overview of the topic. We dive into real-world examples, share guidelines on how to get started, and answer common questions like:

  • How are companies currently using predictive analytics in business applications?
  • How can I solve common data challenges?
  • How will this impact my go-to-market strategy?
  • What is the right and wrong way to price predictive analytics?
  • How do I maintain our predictive models?

Ready to get started? Let’s dive in.

Chapter 1:

Introduction to Predictive Analytics

At its core, predictive analytics answers the question, “What is most likely to happen based on my current data, and what can I do to change that outcome?” It uses historical data, machine learning, and AI to predict what will happen in the future.

Read Chapter One
Chapter 2:

5 Industry Examples of Predictive Analytics

The opportunities of predictive analytics are endless—and it all starts with a little inspiration. Read about five end-to-end examples of how predictive analytics works for industries including healthcare, manufacturing, and SaaS.

Read Chapter Two
Chapter 3:

7 Steps to Start Your Predictive Analytics Project

Whether you’re kicking off a small passion project or launching a large-scale initiative, the steps are essentially the same. Follow these seven steps to start your predictive analytics project.

Read Chapter Three
Chapter 4:

Bringing Predictive Analytics Capabilities to Market

How do you price and package predictive analytics with your application to maximize your ROI? Discover go-to-market strategies and best practices, including the right (and wrong) way to price predictive capabilities.

Read Chapter Four
Chapter 5:

Solving Common Data Challenges

Don't let data problems slow your time to market. Follow these guidelines for getting the most predictive analytics power from your data and the best performance from your models.

Read Chapter Five
Chapter 6:

Maintaining and Improving Predictive Models Over Time

How do you make sure your predictive analytics features continue to perform over time? Find out how to maintain and enhance your models over time, including when to refresh and best practices for refining your algorithms.

Read Chapter Six