Conversion Rate Optimizer
April 29, 2024
Updated May 2, 2025
16 minute read
Conversion Rate Optimizer
Conversion Rate Optimization, often abbreviated as CRO, is a systematic process focused on increasing the percentage of website visitors or app users who take a desired action. This action could be anything from filling out a form, making a purchase, or signing up for a newsletter. At its core, CRO involves understanding how users navigate a digital property, what actions they take, and what stops them from completing specific goals.
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Reading list
We've selected some books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Conversion Rate Optimizer.
Is considered a definitive guide to A/B testing in an online setting, drawing on extensive experience from industry leaders at Google, LinkedIn, and Microsoft. It provides a strong foundation in the principles and practices of designing, running, and analyzing online controlled experiments. It is highly valuable for both students and professionals seeking to understand the nuances of trustworthy experimentation and is often referenced in the field.
This comprehensive guide by Tim Ash, an e-commerce conversion expert and founder of SiteTuners, provides a step-by-step approach to optimizing landing pages for maximum conversions. It covers everything from testing and analysis to design and copywriting best practices.
Offers a comprehensive and accessible deep dive into the statistical concepts underpinning online A/B testing. It is particularly useful for those who need to understand the mathematical and statistical rigor behind experiment analysis, covering topics like statistical inference and experiment design with practical examples. While it delves into formulas, it aims to be understandable for readers without extensive prior statistical knowledge.
This comprehensive guide by marketing expert Michael Aagaard covers the entire landing page optimization process, from design to testing to analytics. It provides practical tips and case studies to help you create high-converting landing pages.
Focuses on the strategic importance of experimentation in business and how organizations can build a culture of experimentation. It provides numerous examples of companies that have successfully leveraged experiments to drive innovation and improve decision-making. This book is excellent for understanding the 'why' behind A/B testing and its impact on business strategy, making it relevant for managers and leaders.
This comprehensive guide to conversion rate optimization covers everything from the basics to advanced techniques, making it a valuable resource for anyone looking to improve their website's performance.
This foundational book by conversion optimization pioneers Bryan and Jeffrey Eisenberg covers the entire conversion optimization process, with a focus on landing page optimization. It provides practical tips and case studies to help you improve your conversion rates.
Published recently, this book provides a practical guide to implementing A/B testing within product development teams. It offers step-by-step instructions for constructing and analyzing A/B tests, focusing on creating a culture of experimentation within an organization. is particularly useful for product managers and engineers.
Focused on the intersection of A/B testing and user experience (UX), this book guides readers on how to use data from experiments to inform design decisions. It is particularly valuable for UX researchers, designers, and product managers who want to integrate experimentation into their design process. The book emphasizes a data-driven approach to creating better user experiences.
Is geared towards engineers and technical practitioners involved in building and running online experiments. It covers the technical aspects of implementing A/B tests and more advanced experimental techniques. It's a valuable resource for understanding the infrastructure and technical considerations behind large-scale experimentation platforms.
While not exclusively about A/B testing, this foundational book on the Lean methodology heavily emphasizes the importance of validated learning through rapid experimentation, of which A/B testing key component. It provides a framework for building and iterating on products based on customer feedback and data, making it essential reading for anyone involved in product development and innovation.
Offers a practical guide to implementing A/B and multivariate testing specifically for website optimization. It covers the technical aspects of setting up and running tests, as well as analyzing the results to improve conversion rates. It's a useful resource for digital marketers and analysts focused on website performance.
Written by the founders of Optimizely, a leading A/B testing platform, this book provides an accessible introduction to A/B testing for business professionals. It focuses on the practical benefits of testing and how it can be used to improve online business metrics. While it may not delve into the deepest statistical theory, it's a solid starting point for understanding the value of A/B testing.
Offers a practical introduction to statistical concepts frequently used in data science, including those relevant to A/B testing analysis. It provides code examples in R and Python, making it useful for data scientists and analysts who need to apply statistical methods to their experiment data. It's a good resource for solidifying the statistical understanding needed for A/B testing.
Serves as a practical guide for designing and running experiments to validate business ideas. It complements The Lean Startup by providing a structured approach to testing assumptions and reducing risk. While not solely focused on A/B testing, it offers valuable insights into the broader concept of experimentation in a business context.
A classic in the field of experimental design, this book provides a thorough grounding in the statistical principles necessary for designing and analyzing experiments across various disciplines. While not specific to A/B testing in a digital context, the fundamental concepts covered are directly applicable and provide a strong theoretical background for anyone serious about understanding the statistics behind testing.
Practical guide to conversion rate optimization for ecommerce businesses, providing a step-by-step process for identifying and fixing conversion problems.
Explores the broader impact of experiments on decision-making in various contexts, including business and public policy. It provides a good overview of why experimentation powerful tool for learning and innovation. It helps to place A/B testing within the larger landscape of evidence-based decision-making.
Focuses on using data and key metrics to guide product development and business growth in a Lean startup environment. It discusses various types of metrics and how to use them for decision-making, including insights relevant to interpreting A/B test results within a broader analytics framework. It's a good resource for understanding how A/B testing fits into a data-driven growth strategy.
This is another widely recognized classic textbook on the design and analysis of experiments. It covers a broad range of experimental designs and the statistical methods used to analyze them. Similar to Box, Hunter, and Hunter, this book provides foundational knowledge in experimental design that is highly relevant to A/B testing, particularly for those with a stronger statistical or engineering background.
Explores the irrational ways that people make decisions.
Is not specifically about conversion rate optimization, but it provides valuable insights into the psychology of persuasion, which is essential for understanding how to convert visitors into customers.
Explores the concept of pre-suasion, which is the art of influencing people before they are aware that they are being influenced.
Explores the role of habits in our lives and how we can change them.
While a more advanced topic, understanding causal inference is crucial for correctly interpreting the results of A/B tests and other experiments. provides an accessible introduction to methods for determining causal relationships from data. It is suitable for those with a solid statistical background looking to deepen their understanding of what A/B tests truly measure.
Provides a guide to designing and reporting experiments, with a focus on psychological research. It covers the principles of experimental design, data analysis, and reporting of findings. While the examples are from psychology, the core concepts of designing rigorous experiments are broadly applicable to A/B testing.
While not specific to multivariate testing, this book provides a comprehensive overview of website optimization, including how to improve conversion rates and user experience. Many of the techniques discussed in this book can be applied to multivariate testing.
While not specific to multivariate testing, this book provides a valuable overview of how to identify and validate business ideas that could potentially benefit from A/B testing in the future.
While not directly about A/B testing, this book is crucial for anyone building systems that support experimentation at scale. It covers the fundamental concepts of data systems, which are necessary for collecting, processing, and analyzing the data generated by A/B tests. It provides essential background knowledge for data engineers and architects in the experimentation space.
If you're interested in Bayesian methods, this book provides a comprehensive overview of Bayesian statistics, including how to apply it to multivariate testing. The authors have extensive experience in Bayesian analysis and provide clear explanations and examples.
This accessible guide to neuromarketing provides insights into how the brain responds to marketing stimuli. It covers a wide range of topics, including landing page optimization, advertising, and product design.
While not specific to multivariate testing, this book provides insights into how established companies can avoid being disrupted by new technologies. This is important for companies that are considering using multivariate testing to improve their products or services.
While not specific to multivariate testing, this book provides a solid foundation in machine learning algorithms, which can be used to create more sophisticated multivariate tests.
If you're new to data analytics, this book provides a solid foundation in the basics, including how to collect, clean, and analyze data. This knowledge can be applied to multivariate testing to help you make better decisions about your tests.
Offers a historical perspective on the concept of experimentation across various scientific disciplines. While not focused on A/B testing, it provides a broader appreciation for the scientific method and the design of experiments throughout history. It's a good choice for readers interested in the foundational ideas behind experimentation.
While not specific to multivariate testing, this book provides insights into how cognitive biases can lead to poor decision-making in business. This is important for companies that are considering using multivariate testing to improve their results.
For more information about how these books relate to this course, visit:
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