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Fighting Churn with Data: The science and strategy of customer retention
The beating heart of any product or service business is returning clients. Don't let your hard-won customers vanish, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether.
Summary
The beating heart of any product or service business is returning clients. Don't let your hard-won customers vanish, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether. This hands-on guide is packed with techniques for converting raw data into measurable metrics, testing hypotheses, and presenting findings that are easily understandable to non-technical decision makers.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Keeping customers active and engaged is essential for any business that relies on recurring revenue and repeat sales. Customer turnover—or “churn”—is costly, frustrating, and preventable. By applying the techniques in this book, you can identify the warning signs of churn and learn to catch customers before they leave.
About the book
Fighting Churn with Data teaches developers and data scientists proven techniques for stopping churn before it happens. Packed with real-world use cases and examples, this book teaches you to convert raw data into measurable behavior metrics, calculate customer lifetime value, and improve churn forecasting with demographic data. By following Zuora Chief Data Scientist Carl Gold’s methods, you’ll reap the benefits of high customer retention.
What's inside
Calculating churn metrics
Identifying user behavior that predicts churn
Using churn reduction tactics with customer segmentation
Applying churn analysis techniques to other business areas
Using AI for accurate churn forecasting
About the reader
For readers with basic data analysis skills, including Python and SQL.
About the author
Carl Gold (PhD) is the Chief Data Scientist at Zuora, Inc., the industry-leading subscription management platform.
Table of
PART 1 - BUILDING YOUR ARSENAL
1 The world of churn
2 Measuring churn
3 Measuring customers
4 Observing renewal and churn
PART 2 - WAGING THE WAR
5 Understanding churn and behavior with metrics
6 Relationships between customer behaviors
7 Segmenting customers with advanced metrics
PART 3 - SPECIAL WEAPONS AND TACTICS
8 Forecasting churn
9 Forecast accuracy and machine learning
10 Churn demographics and firmographics
11 Leading the fight against churn
Summary
The beating heart of any product or service business is returning clients. Don't let your hard-won customers vanish, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether. This hands-on guide is packed with techniques for converting raw data into measurable metrics, testing hypotheses, and presenting findings that are easily understandable to non-technical decision makers.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Keeping customers active and engaged is essential for any business that relies on recurring revenue and repeat sales. Customer turnover—or “churn”—is costly, frustrating, and preventable. By applying the techniques in this book, you can identify the warning signs of churn and learn to catch customers before they leave.
About the book
Fighting Churn with Data teaches developers and data scientists proven techniques for stopping churn before it happens. Packed with real-world use cases and examples, this book teaches you to convert raw data into measurable behavior metrics, calculate customer lifetime value, and improve churn forecasting with demographic data. By following Zuora Chief Data Scientist Carl Gold’s methods, you’ll reap the benefits of high customer retention.
What's inside
Calculating churn metrics
Identifying user behavior that predicts churn
Using churn reduction tactics with customer segmentation
Applying churn analysis techniques to other business areas
Using AI for accurate churn forecasting
About the reader
For readers with basic data analysis skills, including Python and SQL.
About the author
Carl Gold (PhD) is the Chief Data Scientist at Zuora, Inc., the industry-leading subscription management platform.
Table of
PART 1 - BUILDING YOUR ARSENAL
1 The world of churn
2 Measuring churn
3 Measuring customers
4 Observing renewal and churn
PART 2 - WAGING THE WAR
5 Understanding churn and behavior with metrics
6 Relationships between customer behaviors
7 Segmenting customers with advanced metrics
PART 3 - SPECIAL WEAPONS AND TACTICS
8 Forecasting churn
9 Forecast accuracy and machine learning
10 Churn demographics and firmographics
11 Leading the fight against churn
- GenresBusiness
504 pages, Paperback
Published December 22, 2020
21 people are currently reading
130 people want to read
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Displaying 1 - 6 of 6 reviews
February 21, 2022
Carl Gold is one of those rare figures that can be said to have "written the book on churn analysis" both figuratively and literally. True Story.
This book is, by all measures, a veritable jewel in the body of literature for a field that has been long suffering from lazy exposition, unoriginal approaches, shallow techniques, and bloated texts.
Does the author resort to using the same tired benchmark datasets to carry out his analyses? Nope. He not only provides you with a completely novel, realistic, simulated social network dataset, but he also provides all of the code, schemas, wrappers, etc... so you can create these on your own to follow along, or adapt them to your own production use-cases. This alone is worth many times the price of the text.
Chapter One alone is by far the best opening chapter in any data science text available to date, and trust me, I read a lot of them... If you are not convinced by the time you are done with this chapter, then by all means, stop here and go no further.
The techniques go from the very basic to the advanced: data analysis, metric creation/feature engineering, loading matrices, dataset creation, variable grouping, cohort analysis, forecasting, and more.
So while you think you're just reading a book on "churn analysis", you're getting much more. It is essentially, a textbook on data science techniques and best practices applied to churn events. Substitute churn with some other event, and you can pretty much extend the ideas in here to just about any use-case you'll come across. It's 24K Gold.
I can't applaud the author enough for his intellectual generosity in capturing, synthesizing, and sharing his decades of experience on this field for the benefit of the rest of us. I can't wait to see what he comes up with next!
💯 - Highest Possible Recommendation - Must Read for all data scientists!
This book is, by all measures, a veritable jewel in the body of literature for a field that has been long suffering from lazy exposition, unoriginal approaches, shallow techniques, and bloated texts.
Does the author resort to using the same tired benchmark datasets to carry out his analyses? Nope. He not only provides you with a completely novel, realistic, simulated social network dataset, but he also provides all of the code, schemas, wrappers, etc... so you can create these on your own to follow along, or adapt them to your own production use-cases. This alone is worth many times the price of the text.
Chapter One alone is by far the best opening chapter in any data science text available to date, and trust me, I read a lot of them... If you are not convinced by the time you are done with this chapter, then by all means, stop here and go no further.
The techniques go from the very basic to the advanced: data analysis, metric creation/feature engineering, loading matrices, dataset creation, variable grouping, cohort analysis, forecasting, and more.
So while you think you're just reading a book on "churn analysis", you're getting much more. It is essentially, a textbook on data science techniques and best practices applied to churn events. Substitute churn with some other event, and you can pretty much extend the ideas in here to just about any use-case you'll come across. It's 24K Gold.
I can't applaud the author enough for his intellectual generosity in capturing, synthesizing, and sharing his decades of experience on this field for the benefit of the rest of us. I can't wait to see what he comes up with next!
💯 - Highest Possible Recommendation - Must Read for all data scientists!
November 14, 2021
Working with online retail, struggeling with retention? This is a great place to start and more!
I din't go deep on the technical part, but the business part (the first chapters) are totally worth the read if you're managing ideas, or looking for inspiration.
Happy read!
I din't go deep on the technical part, but the business part (the first chapters) are totally worth the read if you're managing ideas, or looking for inspiration.
Happy read!
September 24, 2023
This is so niche and specific and likely not of interest to anybody on my friends list, but it has been hugely helpful over the past couple years. My top reference book for work. I want to deduct a point for the stupid-ass picture on the cover, but I can't; it's been that helpful.
February 8, 2022
The most comprehensive guide on fighting churn.
April 15, 2024
I was impressed by how the author dealt with the churn problem, starting from basic solutions and progressing to more advanced ones. I enjoyed delving into the topics covered in this fantastic book. It's top-notch quality.
December 30, 2024
From all books related to churn and data, this is the most compact ones
Displaying 1 - 6 of 6 reviews