Author : Joel J. Davis
Release : 2017-10-20
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Book Rating : 471/5 ( reviews)

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Google Optimize Demystified - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Google Optimize Demystified write by Joel J. Davis. This book was released on 2017-10-20. Google Optimize Demystified available in PDF, EPUB and Kindle. A comprehensive, step-by-step guide to Google's free website testing, optimization and personalization tool. Website experimentation is an important way to better understand your site visitors' preferences and behaviors and to dramatically improve your site's success. Experiments allow you to explore the impact of changes to site design or content so you can better see how even small modifications can lead to large differences in visitor response and outcomes. Google Optimize Demystified explains how to use Google Optimize to conduct website experiments that help you capitalize on current site strengths and minimize or eliminate current site weaknesses. Unfortunately, many site owners/managers are reluctant to experiment. This is due to the beliefs that experiments are: complicated and requite special expertise to plan, too expensive and disruptive, not relevant to my site's goals and objectives, and difficult to interpret, especially the statistics. Fortunately, Google Optimize eliminates all of these problems. Once you're familiar with Optimize, you'll be able to plan and deploy an experiment in about 10 minutes with no cumbersome HTML programming and without jeopardizing current site response. Additionally, Optimize presents results based on your existing metrics and business objectives to make it easy to see what you should do next to improve site success. The core of Google Optimize Demystified focuses on the three types of experiments you can conduct via Optimize: A/B, Redirect and Multivariate. Each type is explained via a case study and each step of the development and analysis process is explained clearly and concisely. But, the book goes beyond simply explaining how to plan, conduct and analyze an Optimize experiment. The book also provides clear and comprehensive discussions of additional topics that contribute to a broader range of planning and analysis options. All of these aspects of the book are illustrated in it's organization and approach. Google Optimize Demystified presents nine sections of content: Section I presents an overview of Google Optimize characteristics and benefits, explains the three types of experiments that can be conducted, describes the steps involved in planning an experiment and explains the characteristics of successful experiments. Section II discusses characteristics and application of regular expressions, goals, events, and segments as they apply to Optimize experiments. Section III discusses the steps you'll use to configure your Google Optimize account. Sections IV through VI each focus on a specific type of experiment. Each section consists of nine chapters that take you through step-by-step creation and interpretation of an A/B, multivariate, or redirect experiment, respectively. The Visual Editor is the free tool you will use to create your experimental variations. The chapters in Section VII explain the Editor's features and describe how to easily create experimental variations by editing text, images, links, and CSS. Targeting is how you specify an experiment's timing and participant characteristics. Section VIII provides a detailed, yet easy to follow discussion of the variations available within four commonly used targeting options: URL, Behavior, Geographic, and Technology. Section IX discusses an additional targeting option: Query parameter targeting. This approach is particularly useful when you are trying to optimize the landing page viewed when your external referral links are clicked. The chapters in this section show you how to add query strings to your referral links, how to target using query parameter information, and how to use this information to conduct a landing page optimization experiment.