Features
Hands-on guide to marketing analytics methods and tools
- Integrates all three fundamental areas of marketing analytics: statistical analysis, experiments, and managerial intuition
- Thoroughly details a best-practice methodology, augmenting it with case studies that illustrate the quantitative and data analysis tools you'll need
- Covers resource allocation, dashboards and systems of metrics, marketing mix analytics, customer analytics, and digital marketing analytics
- Pairs real company case studies with data and technical notes, giving you the statistical knowledge to perform each analysis yourself
- Supplemented with how to videos on each analytics technique at dmanalytics.org, a site hosted by the authors
- Copyright 2014
- Dimensions: 7" x 9-1/8"
- Pages: 320
- Edition: 1st
-
Book
- ISBN-10: 0-13-355252-7
- ISBN-13: 978-0-13-355252-2
Master practical strategic marketing analysis through real-life case studies and hands-on examples. In Cutting Edge Marketing Analytics, three pioneering experts integrate all three core areas of marketing analytics: statistical analysis, experiments, and managerial intuition. They fully detail a best-practice marketing analytics methodology, augmenting it with case studies that illustrate the quantitative and data analysis tools you'll need to allocate resources, define optimal marketing mixes; perform effective analysis of customers and digital marketing campaigns, and create high-value dashboards and metrics.
For each marketing problem, the authors help you:
- Identify the right data and analytics techniques
- Conduct the analysis and obtain insights from it
- Outline what-if scenarios and define optimal solutions
- Connect your insights to strategic decision-making
Each chapter contains technical notes, statistical knowledge, case studies, and real data you can use to perform the analysis yourself. As you proceed, you'll gain an in-depth understanding of:
- The real value of marketing analytics
- How to integrate quantitative analysis with managerial sensibility
- How to apply linear regression, logistic regression, cluster analysis, and Anova models
- The crucial role of careful experimental design
For all marketing professionals specializing in marketing analytics and/or business intelligence; and for students and faculty in all graduate-level business courses covering Marketing Analytics, Marketing Effectiveness, or Marketing Metrics
Author's Site
Download supplemental files from the authors' website: here
Online Sample Chapters
A Resource-Allocation Perspective for Marketing Analytics
Cutting Edge Marketing Analytics: A Case Study with Dunia Finance LLC
Introduction to Cutting Edge Marketing Analytics: Real World Cases and Data Sets for Hands On Learning
Sample Pages
Download the sample pages (includes Section 1 and Index)
Table of Contents
Foreword xiv
Introduction 1
Section I: Resource Allocation 5
Chapter 1: A Resource-Allocation Perspective for Marketing Analytics 6
Chapter 2: Dunia Finance LLC 18
Section II: Product Analytics 33
Chapter 3: Cluster Analysis for Segmentation 34
Chapter 4: Segmentation at Sticks Kebob Shop 43
Chapter 5: A Practical Guide to Conjoint Analysis 55
Chapter 6: Portland Trail Blazers 65
Section III: Marketing-Mix Analytics 77
Chapter 7: Multiple Regression in Marketing-Mix Models 78
Chapter 8: Design of Price and Advertising Elasticity Models 90
Chapter 9: SVEDKA Vodka 103
Section IV: Customer Analytics 133
Chapter 10: Customer Lifetime Value 134
Chapter 11: Netflix: The Customer Strikes Back 144
Chapter 12: Retail Relay 153
Chapter 13: Logistic Regression 169
Chapter 14: Retail Relay Revisited 181
Section V: Digital Analytics 183
Chapter 15: Designing Marketing Experiments 184
Chapter 16: Transformation of Marketing at the Ohio Art Company 193
Chapter 17: Paid Search Advertising 211
Chapter 18: Motorcowboy: Getting a Foot in the Door 227
Chapter 19: VinConnect, Inc.: Digital Marketing Strategy 239
Chapter 20: Cardagin: Local Mobile Rewards 261
Section VI: Resource Allocation Revisited 278
Chapter 21: Dunia Finance LLC Revisited 279
Chapter 22: Implementing Marketing Analytics 282
Index 290