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Designing with Data: Improving the User Experience with A/B Testing by [King, Rochelle, Churchill, Elizabeth F, Tan, Caitlin]
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Designing with Data: Improving the User Experience with A/B Testing 1st , Kindle Edition

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About the Author

Rochelle King is Global VP of Design and User Experience at Spotify where she is responsible for the teams that oversee user research and craft the product experience at Spotify. Prior to Spotify, Rochelle was VP of User Experience and Product Services at Netflix. where she managed the Design, Enhanced Content, Content Marketing and Localization teams at Netflix. Collectively, these groups were responsible for the UI, layout, meta-data (editorial and visual assets) and presentation of the Netflix service internationally across all platforms. Rochelle has over 14 years of experience working on consumer facing products. @rochelleking

Dr. Elizabeth Churchill is a an applied social scientist working in the area of social media, interaction design and mobile/ubiquitous computing. She is currently Director of Human Computer Interaction at eBay Research Labs (ERL) in San Jose, California.

She was formerly a Principal Research Scientist at Yahoo! Research, where she founded, staffed and managed the Internet Experiences Group. Until September of 2006, she worked at the Palo Alto Research Center (PARC), California, in the Computing Science Lab (CSL). Prior to that she formed and led the Social Computing Group at FX Palo Laboratory, Fuji Xerox’s research lab in Palo Alto.

Originally a psychologist by training, throughout her career Elizabeth has focused on understanding people’s social and collaborative interactions in their everyday digital and physical contexts. She has studied, designed and collaborated in creating online collaboration tools (e.g. virtual worlds, collaboration/chat spaces), applications and services for mobile and personal devices, and media installations in public spaces for distributed collaboration and communication. In addition to being instrumental in the creation of innovative technologies, she has contributed to academic research through her publications in theoretical and applied psychology, cognitive science, human-computer interaction and computer supported cooperative work. With over 100 peer reviewed publications and 5 edited books, topics she has written about include implicit learning, human-agent systems, mixed initiative dialogue systems, social aspects of information seeking, digital archive and memory, and the development of emplaced media spaces. She has been a regular columnist for ACM interactions since 2008.

Elizabeth has a BSc in Experimental Psychology, an MSc in Knowledge Based Systems, both from the University of Sussex, and a PhD in Cognitive Science from the University of Cambridge. In 2010, she was recognised as a Distinguished Scientist by the Association for Computing Machinery (ACM). Elizabeth s the current Executive Vice President of ACM SigCHI (Human Computer Interaction Special Interest Group). She is a Distinguished Visiting Scholar at Stanford University’s Media X, the industry affiliate program to Stanford’s H-STAR Institute. @xeeliz

Product details

  • Format: Kindle Edition
  • File Size: 5433 KB
  • Print Length: 372 pages
  • Page Numbers Source ISBN: 1449334830
  • Simultaneous Device Usage: Unlimited
  • Publisher: O'Reilly Media; 1 edition (29 Mar. 2017)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B06XY9TTN8
  • Text-to-Speech: Enabled
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  • Average Customer Review: Be the first to review this item
  • Amazon Bestsellers Rank: #641,943 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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1 of 1 people found the following review helpful
5.0 out of 5 stars The old is new again. 24 Jun. 2017
By Jerry Saperstein - Published on Amazon.com
Format: Paperback Vine Customer Review of Free Product ( What's this? )
I cut my teeth on mail-order marketing, what they now call direct-response. Might even be called something else now.

One of the cardinal rules of mail-order marketing was – and remains – test, test, test.

You tested everything. The headline, the copy, the color of the paper, its weight, everything until you had tested enough determine the most efficient marketing package.

This book’s primary authors are eminently qualified and highly experienced. Even better, they are graceful writers.

The authors define “A/B testing [as] a methodology to compare two or more versions of an experience to see which one performs the best relative to some objective measure”. In other words, you test to find out what works best.

The book is intended to acquaint designers and product managers in launching digital products using data to guide the product’s refinement. In other words, the book how to show designers and product managers how to use the wealth of data available to better market their product.

Over the course of the first six chapters, they do precisely that. This stuff is really good. The authors, one with Spotify in her background, the other with Netflix, truly understand the concept, mechanics and worth of testing.

The last two chapters smelled too much like political correctness for my taste and, in my opinion could have been left out without harming the value of the book.

If you are not thoroughly experienced with the concept of A/B testing in marketing vehicles, you will benefit from this book.

4.0 out of 5 stars Improve the user experience and the product and save money, touches on Six Sigma principals, but has it's own spin on the detail 7 July 2017
By Courtland J. Carpenter - Published on Amazon.com
Format: Paperback Vine Customer Review of Free Product ( What's this? )
The book could be more adaptable to various industry, but the work they do discuss reminds me of the test design and data used from a Six Sigma course I took from Purdue a few years back. You can design your process by creating process or experiments that show how you can improve the overall production. One of my professors described his best finder of flaws with walking the plant floor to discover where the process fell down and then when some of those flaws are fixed you stop getting outliers data and help to streamline the process.

While this is not exactly what the book is about, it's not totally Six Sigma, it does touch on the same things just from a more data centered way. What is does do is give you ideas how to design those experiments with the kind of data you use and then how to read the results. Testing itself is very data centered. I work as an embedded software tester, and the design starts with customer requirements, that turn into system requirements which include both hardware and software, then become software requirements for the testing I do from which I create software test verification requirements. Data becomes closer and closer the more you get removed from the customer requirements as a central part. It often becomes difficult going that path to get a good design.

Here's an example from my experience. A new type of emission control system was being put on all the trucks my former company produced. They had a new multiplexed line of Line Haul or what you may call Semi trucks coming out. They had a couple years to design the new emissions control system, but do to the pipeline of not going from the data needed to control the request system, the system requirements detailed a set of two state diagrams that described the function that were horrible. One had 13 state and over 30 transitions the other about 11 states and over 25 transitions, it was implemented correctly in software, but the operation was klugy at best. Engine variants made it worse and the vehicle launch had to be put back because of the failures. The test group and system group working from the data central side of things designed two state diagrams one with 4 states and 5 transitions, the other with 3 states and 4 transitions, and it did the same thing, but worked nearly flawless. It took six weeks working 7 days a week to re-implement the software, and the loss of revenue, and poor launch probably cost millions. Which shows one of the reasons to consider the methods this book supports. Not perfect, but a good start, recommended.
5.0 out of 5 stars Solid addition to the O'Reilly lineup, excellent book on data-driven design 29 Jun. 2017
By Larson - Published on Amazon.com
Format: Paperback Vine Customer Review of Free Product ( What's this? )
I've always been pleased with O'Reilly books, and this one is no exception.

A/B testing is kind of the gold standard when it comes to data-driven marketing, and this book does a pretty solid job of explaining it both from a conceptual level and a practical level.

Obviously, your testing will depend heavily on what you're hoping to measure, and this book has plenty of thorough examples of A/B implementations.

From a technical level, this is written for someone who is at least passing familiar with UI design and UX principles, but doesn't assume the reader is an expert. Like many O'Reilly books, the author does a good job of covering things in sufficient detail so that novices won't feel lost, but assumes that the reader is an intelligent person who will understand without belaboring things too much.
5.0 out of 5 stars Very good book, better than most in this field! 26 Jun. 2017
By Momma Mary - Published on Amazon.com
Format: Paperback Vine Customer Review of Free Product ( What's this? )
A/B testing isn't something that you hear about very often but has been becoming the standard for designing everything in our day and age. From a beginners perspective in this field I feel like this book did a really good job of establishing a baseline of what A/B testing is, the nuances of the field, and why it is so crucial in the technology field. Personally I really enjoyed the being able to see the real life, in-depth examples of how this testing can be applied. I think that also is a testament to how well versed these authors are in the subject matter. One other pet peeve of mine is when discussing such a technical matter often times these books are very dry and hard to read, but I found this book to be quite enjoyable.
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