Predictive Marketing 1st Edition by Omer Artun, Dominique Levin 1119037330 9781119037330

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ISBN-10 :  1119037330 

ISBN-13 : 9781119037330

Author:  Omer Artun, Dominique Levin 

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 marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You’ll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.

Predictive Marketing 1st Table of contents:

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
Reinforcement Learning and Collaborative Filtering
The 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
Part 2: Nine Easy Plays to Get Started with Predictive Marketing
Chapter 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
Chapter 7: Play Three: Predict the Customer Journey for Life Cycle Marketing
The 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
Chapter 11: Play Seven: Launch Predictive Programs to Convert More Customers
Predictive 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
Customer Reactivation Campaigns
Part 3: How to Become a True Predictive Marketing Ninja
Chapter 14: An Easy-to-Use Checklist of Predictive Marketing Capabilities
Organizational Capabilities for Predictive Marketing
Technical Capabilities for Predictive Marketing
Questions to Ask Predictive Marketing Vendors
Chapter 15: An Overview of Predictive (and Related) Marketing Technology
Do-It-Yourself Predictive Marketing
Outsourcing to Marketing Service Providers
Campaign Management and Marketing Cloud Options
Other Tools You May Have Heard About
Which Solution Is Right for Me?
Whatever You Do—Get Started
Chapter 16: Career Advice for Aspiring Predictive Marketers
Business Understanding Trumps Math
Ask the Right Questions
Blend the Art and Science of Marketing
Learn from Others
Chapter 17: Privacy and the Difference Between Delightful and Invasive
Types of Personal Information
Avoid Invasive Situations
Give Customers Control
Hard Boundaries and Government Legislation
Chapter 18: The Future of Predictive Marketing
Advanced Predictive Analytics Models
Think Like a Predictive Marketer
Appendix: Overview of Customer Data Types
Purchases and Transactions
Web and Online Behavior
Email Behavior
Household and Account Grouping
Location
Call Center Interactions, Meetings, and Social Interactions
Returns, Complaints, and Reviews
Gender
U.S. Census Data
Vertical and Size
Other Customer Data Points
Index

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