Freemium Economics
Leveraging Analytics and User Segmentation to Drive Revenue
Published on 8. March 2014
Book
Paperback/Softback
254 pages
978-0-12-416690-5 (ISBN)
Description
Freemium Economics presents a practical, instructive approach to successfully implementing the freemium model into your software products by building analytics into product design from the earliest stages of development.
Your freemium product generates vast volumes of data, but using that data to maximize conversion, boost retention, and deliver revenue can be challenging if you don't fully understand the impact that small changes can have on revenue. In this book, author Eric Seufert provides clear guidelines for using data and analytics through all stages of development to optimize your implementation of the freemium model. Freemium Economics de-mystifies the freemium model through an exploration of its core, data-oriented tenets, so that you can apply it methodically rather than hoping that conversion and revenue will naturally follow product launch.
Your freemium product generates vast volumes of data, but using that data to maximize conversion, boost retention, and deliver revenue can be challenging if you don't fully understand the impact that small changes can have on revenue. In this book, author Eric Seufert provides clear guidelines for using data and analytics through all stages of development to optimize your implementation of the freemium model. Freemium Economics de-mystifies the freemium model through an exploration of its core, data-oriented tenets, so that you can apply it methodically rather than hoping that conversion and revenue will naturally follow product launch.
Reviews / Votes
"Seufert's book provides extensive guidance on analyzing the data generated by a freemium product to boost retention and drive revenue. By collecting and deploying analytics on large amounts of data generated by users of the product, through all stages of development and usage, the author explains how you can optimize your implementation of the freemium model." --Data and Technology Today, 2014More details
Series
Language
English
Place of publication
San Francisco
United States
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Analysts, user acquisition and product managers, mid- and senior-level managers in Freemium businesses
Illustrations
Illustrated
Dimensions
Height: 233 mm
Width: 187 mm
Thickness: 20 mm
Weight
540 gr
ISBN-13
978-0-12-416690-5 (9780124166905)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
E-Book
12/2013
Morgan Kaufmann
€38.95
Available for download
Person
Eric Seufert is a quantitative marketer with a passion for blending real-world problems with large amounts of data, econometric frameworks, and analytical systems. His professional specialty lies in programmatic statistical methods and predictive forecasting in freemium environments.Eric received an undergraduate degree in Finance from the University of Texas at Austin and an MA in Economics from University College London, where he was an Erasmus Mundus scholar. Eric joined Skype immediately out of graduate school and subsequently held marketing and strategy roles at Digital Chocolate and Wooga, where he is now the Head of Marketing. Prior to graduate school, Eric worked at uShip, the Austin-based marketplace for shipping services.Originally from Texas, Eric currently lives in Berlin. In his spare time, Eric enjoys traveling and writing.
Content
1. What is the Freemium Model?
2. Analytics as the Heart of Freemium
3. Quantitative Methods for Product Management
4. Freemium Metrics
5. Lifetime Customer Value
6. Monetization and Downstream Marketing
7. Virality
8. Optimized User Acquisition
2. Analytics as the Heart of Freemium
3. Quantitative Methods for Product Management
4. Freemium Metrics
5. Lifetime Customer Value
6. Monetization and Downstream Marketing
7. Virality
8. Optimized User Acquisition