Book Review #2: Cutting-Edge Marketing Analytics

Book Title: Cutting-Edge Marketing Analytics
ISBN: 0-13-355252-7
Publisher: Pearson Education, Inc.

Written by three University of Virginia Professors, Cutting-Edge Marketing Analytics is a how-to guide on practical and sensible marketing analytics. It emphasis on connecting marketing inputs to customer behavior, and utilizes different predictive models (based on historical information, experiments, or heuristics) to develop the forward-looking scenarios of “What if”.

Cutting-Edge Marketing Analytics
Cutting Edge Marketing Analytics is heavily dependent on explanation of marketing analytics theories, with real world data sets.

Although I’ve read this book as part of the Purdue MBA program, this book is both intriguing with heavy on marketing analytics theories and applications – including the explanation on linear regression and logistic regression, along with marketing ROIs, customer segmentations, and conjoint-analysis. For your convenience, I’ve also added bonus documents (at the middle of the article), which are Google Power Point slides you can read and see specific content of this book.

This book breaks down each theory step-by-step, explaining why such formula was used, and how it applies to specific business goal. For example, in Chapter 1, a resource allocation perspective for marketing analytics deal with a small business “Dunia Finance LLC”.

Dunia Finance LLC needs to make more profits, but isn’t sure which marketing has the highest ROI, and up to what point? The book introduces customer lifetime value (known as CLV) is introduced in relationship with how advertising and unit price affects overall unit sales, and how different channels, including trade shows or sales force, have different CLV.


Please Like this article, if you found it helpful. I’ve spent nearly +10 hours developing the power points for important chapters to provide in-depth review. You can read them below links.

Check out these following links for Detailed Power Points on:

What is Marketing Analytics? (Chapter 1)

Cluster Analysis for Customer Segmentation (Chapter 3)

Design of Price and Advertising Elasticity Models (Chapter 8)

Customer Life Time Value (Chapter 10)

Logistic Regression (Chapter 13)


One of the most interesting facts I learned was the 10Ps of successful analytics used by a very successful financial firm in UAE, and it made double digit profit during in 2008, economic depression. This organization used the following customer-centric ideas:

  1. People: Hire Top-Tier people with specialized talent
  2. Passion: The team needs to display passion through creativity and innovation
  3. Predictability: Predictability of results lead to profitability
  4. Profitability: Profitability is require for investing in good times and sustainability in stressful times
  5. Proactive: Be Proactive in identifying potential issues.
  6. Precision: The solution needs to be executed with precision.
  7. Power: Computing power has to be at the highest degree. Allowing maximum necessary investment into systems and hardware to keep up with competition and changing trends.
  8. Partnership: Partnership across all functional teams is a critical success factor
  9. Progression: Customer progression has to be in line with their needs and life stage
  10. Pragmatism: The solution has to be pragmatic for simplicity of implementations.

Another very important knowledge I learned from reading this book was from Chapter 3,Cluster Analysis of Segmentation” – which drills down to how to understand the cluster analysis on very simple mathematics term. We use the “Euclidean Distance”, which is essentially the distance between two points and related variables are compared.  (If you want to know more you can click here to read the detailed power point of K-Mean Clustering Algorithm, which I have summarized.)

In the book, Geico insurance company had segmented four customer segment based on four customer criteria: (1) Identifiabliity, (2) Sustainability, (3) Accessibility, and (4) Actionability.

  • Identifiability – Can Manager Identify the Market Segment easily? (Using PRIZM and ACRON population database, are the customer segment easy to segment?)
  • Sustainability – Is there large enough profitable customers to maintain that segment of customers and ensure profitable customization of the marketing program?
  • Accessibility – Can the managers utilize their marketing campaigns to reach these customers?
  • Actionability – Whether customers in the segment and the marketing mix are satisfying their needs are consistent with the core competencies of the Geico.

Although reading this book can be really dry and quite tedious, there are some important insights that helped me better my future in marketing field, including CLV, Customer Segmentation, Conjoint-Analysis.
These are important concepts utilized on regular basis by many marketing analyst, marketing directors and managers in mid-to-senior level positions.

My Suggestions:
I would suggest you invest at least some amount of time in reading this valuable book if you can download or get a copy from a local library, or borrow from a university. Word advice: Focus on chapter 3, 5, 7, and 10. If you are not trained in statistics or aren’t too comfortable with algorithmic math, multiple regression model explanation would be mind-boggling, and even more for logistic regression without the use of R-programming or SAS Enterprise Miner tool.

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