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Joanne Rodrigues

Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights (Pearson Business Analytics Series) 1st Edition

by Joanne Rodrigues (Author)

21 ratings

Part of: Addison-Wesley Data & Analytics (11 books)

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This guide shows how to combine data science with social science to gain unprecedented insight into customer behavior, so you can change it. Joanne Rodrigues-Craig bridges the gap between predictive data science and statistical techniques that reveal why important things happen -- why customers buy more, or why they immediately leave your site -- so you can get more behaviors you want and less you don't.

Drawing on extensive enterprise experience and deep knowledge of demographics and sociology, Rodrigues-Craig shows how to create better theories and metrics, so you can accelerate the process of gaining insight, altering behavior, and earning business value. You'll learn how to:

Develop complex, testable theories for understanding individual and social behavior in web products
Think like a social scientist and contextualize individual behavior in today's social environments
Build more effective metrics and KPIs for any web product or system
Conduct more informative and actionable A/B tests
Explore causal effects, reflecting a deeper understanding of the differences between correlation and causation
Alter user behavior in a complex web product
Understand how relevant human behaviors develop, and the prerequisites for changing them
Choose the right statistical techniques for common tasks such as multistate and uplift modeling
Use advanced statistical techniques to model multidimensional systems
Do all of this in R (with sample code available in a separate code manual)

Book Website: actiondatascience.com.

ISBN-10

0135258529
ISBN-13

978-0135258521
Edition

1st
Publisher

Addison-Wesley Professional
Publication date

October 1, 2020
Language

English
Dimensions

7 x 1.01 x 9.13 inches
Print length

360 pages
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Editorial Reviews

From the Back Cover

This guide shows how to combine data science with social science to gain unprecedented insight into customer behavior, so you can change it. Joanne Rodrigues-Craig bridges the gap between predictive data science and statistical techniques that reveal why important things happen -- why customers buy more, or why they immediately leave your site -- so you can get more behaviors you want and less you don’t.
Drawing on extensive enterprise experience and deep knowledge of demographics and sociology, Rodrigues-Craig shows how to create better theories and metrics, so you can accelerate the process of gaining insight, altering behavior, and earning business value. You’ll learn how to:

Develop complex, testable theories for understanding individual and social behavior in web products
Think like a social scientist and contextualize individual behavior in today’s social environments
Build more effective metrics and KPIs for any web product or system
Conduct more informative and actionable A/B tests
Explore causal effects, reflecting a deeper understanding of the differences between correlation and causation
Alter user behavior in a complex web product
Understand how relevant human behaviors develop, and the prerequisites for changing them
Choose the right statistical techniques for common tasks such as multistate and uplift modeling
Use advanced statistical techniques to model multidimensional systems
Do all of this in R (with sample code available in a separate code manual)

Build better theories and metrics, and drive more of the behaviors you want
Model, understand, and alter customer behavior to increase revenue and retention
Construct better frameworks for examining why your customers do what they do
Develop core metrics for user analytics, and conduct more effective A/B tests
Master key techniques that most books ignore, including statistical matching and uplift modeling
Use R and this book’s many R examples to implement these techniques yourself

Use data science and social science to generate real changes in customer behavior

Build better theories and metrics, and drive more of the behaviors you want
Model, understand, and alter customer behavior to increase revenue and retention
Construct better frameworks for examining why your customers do what they do
Develop core metrics for user analytics, and conduct more effective A/B tests
Master key techniques that most books ignore, including statistical matching and uplift modeling
Use R and this book’s many R examples to implement these techniques yourself

About the Author

Joanne Rodrigues is an experienced data scientist with master’s degrees in mathematics, political science, and demography. She has six years of experience in statistical computing and R programming, as well as experience with Python for data science applications. Her management experience at enterprise companies leverages her ability to understand human behavior by using economic and sociological theory in the context of complex mathematical models.

Product details

Publisher ‏ : ‎ Addison-Wesley Professional; 1st edition (October 1, 2020)
Language ‏ : ‎ English
Paperback ‏ : ‎ 360 pages
ISBN-10 ‏ : ‎ 0135258529
ISBN-13 ‏ : ‎ 978-0135258521
Item Weight ‏ : ‎ 1.5 pounds
Dimensions ‏ : ‎ 7 x 1.01 x 9.13 inches

Best Sellers Rank: #971,928 in Books (See Top 100 in Books)
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- #464 in Data Mining (Books)

Customer Reviews:
21 ratings

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Joanne Rodrigues

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I am an experienced data scientist and enterprise manager with expertise in both mathematics and the social sciences and an insatiable intellectual curiosity to understand human behavior with data. I'm currently building the company, ClinicPriceCheck.com, to facilitate easy price comparison of health services at nearby providers by aggregating health provider pricing and quality information in an easy-to-use, consumer-friendly format. Book website: actiondatascience.com. Video course: https://www.oreilly.com/videos/product-analytics-for/9780137907748/.

Customer reviews

4 out of 5

21 global ratings

5 star		44%
4 star		23%
3 star		20%
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Andrew

Surprisingly awful

Reviewed in the United States 🇺🇸 on October 31, 2022

Verified Purchase

This book is absolutely riddled with typos, but it goes beyond that. Time and again the author is straight up wrong when it comes to the definitions of key terms (skew and kurtosis for example), explanation of theory, and the math itself. It reminded me of reading a book report written by someone who had only read the the book’s wikipedia entry.

I recommend you get anything but this book. This book will leave you misinformed and your time wasted. Take a look at the table of contents and then look online, there are a lot of good resources available.

I gave it two stars rather than one for two reasons:
1) People tend to ignore one star reviews
2) While it poorly explains most concepts, it at least mentions concepts that are important. You could use it’s table of contents as a helpful list of things to learn, just don’t learn them from this book!

2 people found this helpful

Helpful

Dan

Every analyst should read this

Reviewed in the United States 🇺🇸 on May 13, 2021

Verified Purchase

I’m very happy someone finally wrote a book on product analytics. This is a model everyone analyst should strive for. Though I do believe there is a huge gap between the current way product analytics is done from the descriptive inferential way to the model put forth in this book and that mostly comes down to lack of time and statistical know-how. Nearly none of my clients would allow us the time needed to do the necessary statistics.

The only negative response I have, (and reason for taking away one star) is the repeated grammatical/spelling errors. It takes a very educated person and makes them seem like they are not paying attention to detail, which is incongruous with the content of the book. The publisher really needs a better editor/proof-reader.

3 people found this helpful

Helpful

Pearlo

Product analytics explained

Reviewed in the United States 🇺🇸 on March 21, 2021

Verified Purchase

Excellent book on the foundation of product analytics.. wish the font were a little bigger though..

2 people found this helpful

Helpful

dylan phila

Many many errors

Reviewed in the United States 🇺🇸 on December 31, 2021

many errors in statistics and ML. This is why product analytics should be a STEM job.
very disappointed reading the book.

4 people found this helpful

Helpful

Hubert V. Yee

Making sense out of massive data for product refinement with simple tools

Reviewed in the United States 🇺🇸 on December 25, 2021

Making sense out of massive data for product refinement with simple tools. This is what Joanne Rodrigues' goal is for her book Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights. It does the job well. The subject matter was written for applied practice by non academics. In addition the book is structured for quick referencing. Definition, real world examples and applications are included. This book is worthy to be part of your reference collection.

As you begin your read, note that the writing strives to be concise and understandable. This is one of important aspects of this book. It was written as a reference for techniques and the tools needed for successful product analytics and data analysis. The book even includes an introduction to R and a guided setup.

Another helpful aspect of Rodrigues' book is that sections are structured to cover each topic in depth. If you understand and have a good grasp of A/B testing, skip Chapter 6 and move to Chapter 7 which covers k-Means and PCA.

Last, real world examples emphasizing the techniques and tools are included in this book. Rodriques takes her time to provide explanations and techniques for product analytics. You'll find NBA players' heights used to explain mean, median, and mode. She even shares a behavioral change worksheet for A/B testing.

Succint and easily understandable, this book is an exciting intro for new folks in product analytics and an everlasting reference for long term practitioners. Making sense out of massive data for product refinement with simple tools. This is what Joanne Rodrigues' goal is for her book Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights. It does the job well. The subject matter was written for applied practice by non academics. In addition the book is structured for quick referencing. Definition, real world examples and applications are included. This book is worthy to be part of your reference collection.

As you begin your read, note that the writing strives to be concise and understandable. This is one of important aspects of this book. It was written as a reference for techniques and the tools needed for successful product analytics and data analysis. The book even includes an introduction to R and a guided setup.

Another helpful aspect of Rodrigues' book is that sections are structured to cover each topic in depth. If you understand and have a good grasp of A/B testing, skip Chapter 6 and move to Chapter 7 which covers k-Means and PCA.

Last, real world examples emphasizing the techniques and tools are included in this book. Rodriques takes her time to provide explanations and techniques for product analytics. You'll find NBA players' heights used to explain mean, median, and mode. She even shares a behavioral change worksheet for A/B testing.

Succint and easily understandable, this book is an exciting intro for new folks in product analytics and an everlasting reference for long term practitioners. data for product refinement with simple tools. This is what Joanne Rodrigues' goal is for her book Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights. It does the job well. The subject matter was written for applied practice by non academics. In addition the book is structured for quick referencing. Definition, real world examples and applications are included. This book is worthy to be part of your reference collection.

As you begin your read, note that the writing strives to be concise and understandable. This is one of important aspects of this book. It was written as a reference for techniques and the tools needed for successful product analytics and data analysis. The book even includes an introduction to R and a guided setup.

Another helpful aspect of Rodrigues' book is that sections are structured to cover each topic in depth. If you understand and have a good grasp of A/B testing, skip Chapter 6 and move to Chapter 7 which covers k-Means and PCA.

Last, real world examples emphasizing the techniques and tools are included in this book. Rodriques takes her time to provide explanations and techniques for product analytics. You'll find NBA players' heights used to explain mean, median, and mode. She even shares a behavioral change worksheet for A/B testing.

Succint and easily understandable, this book is an exciting intro for new folks in product analytics and an everlasting reference for long term practitioners.

Helpful

Anamika

Unique data science book

Reviewed in the United States 🇺🇸 on January 8, 2022

This book has some great insights for applied analytical questions, using a variety of techniques including casual inference not available in other books.

Very practical book that gives some good examples. Not too academic. Easily readable.

I was looking for a causal inference book without too much math. This book was much more readable and practical. Also some good demographic techniques.

Reviewed in the United States 🇺🇸 on February 27, 2021

Very insightful and easy to read and learn. I learned a lot from this book.

2 people found this helpful

Helpful

Lester Mascarenhas

Must read for folks pursuing a career as a data analyst

Reviewed in the United States 🇺🇸 on February 13, 2021