Predictive marketing : easy ways every marketer can use customer analytics and big data /

"Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The mark...

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Bibliographic Details
Main Authors: Artun, Omer, 1969- (Author), Levin, Dominique, 1971- (Author)
Format: Book
Language:English
Published: Hoboken, New Jersey : Wiley, [2015]
Edition:1st edition
Series:Gale eBooks
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Table of Contents:
  • Cover; Title Page; Copyright; Contents; Introduction: Who Should Read This Book; Part 1 A Complete Predictive Marketing Primer; Chapter 1 Big Data and Predictive Analytics Are Now Easily Accessible to All Marketers; The Predictive Marketing Revolution; The Power of Customer Equity; Predictive Marketing Use Cases; Predictive Marketing Adoption Is Accelerating; What Do You Need for Predictive Marketing?; Chapter 2 An Easy Primer to Predictive Analytics for Marketers; What Is Predictive Analytics?; Unsupervised Learning: Clustering Models; Supervised Learning: Propensity Models
  • Chapter 11 Play Seven: Launch Predictive Programs to Convert More CustomersPredictive Remarketing Campaigns; Using Look-Alike Targeting; Chapter 12 Play Eight: Launch Predictive Programs to Grow Customer Value; The Secret to Growing Customer Value; Predictive Post-Purchase Programs; Customer Appreciation Campaigns; Chapter 13 Play Nine: Launch Predictive Programs to Retain More Customers; Understanding Your Retention Rate; The Concept of Negative Churn; Understanding Your Business Model; Not All Churn Is Created Equal; Churn Management Programs; Proactive Retention Management
  • Chapter 7 Play Three: Predict the Customer Journey for Life Cycle MarketingThe Customer Value Journey; Life Cycle Marketing Strategies; Chapter 8 Play Four: Predict Customer Value and Value-Based Marketing; Value-Based Marketing; Chapter 9 Play Five: Predict Likelihood to Buy or Engage to Rank Customers; Likelihood to Buy Predictions; Likelihood to Engage Models; Chapter 10 Play Six: Predict Individual Recommendations for Each Customer; Choosing the Right Customer or Segment; Understanding Customer Context; Content-What to Recommend; Beyond Recommendations
  • Customer Reactivation Campaigns
  • Part 2 Nine Easy Plays to Get Started with Predictive MarketingChapter 5 Play One: Optimize Your Marketing Spending Using Customer Data; Invest in Acquisition, Retention, and Reactivation; Differentiate Spending Based on Customer Value; Find Products That Bring High-Value Customers; Find Channels That Bring High-Value Customers; The Case for Last-Touch Attribution; Chapter 6 Play Two: Predict Customer Personas and Make Marketing Relevant Again; Types of Clusters; Using Clusters to Improve Customer Acquisition; Things to Watch Out for When Using Clusters; Clusters in Action
  • Reinforcement Learning and Collaborative FilteringThe Predictive Analytics Process; Chapter 3 Get to Know Your Customers First: Build Complete Customer Profiles; How Much Data to Collect; What Type of Data to Collect; Preparing Your Data for Analysis; Working with IT on Data Integration; One Hundred Questions to Ask Your Data; Chapter 4 Managing Your Customers as a Portfolio to Improve Your Valuation; What Is Customer Lifetime Value?; Increase Customer Lifetime Value for One Customer; Increase Customer Lifetime Value for All Customers