Abstract
Join us for an informative webinar with Bertil Hatt, Experimentation Advocate at Split, as he simplifies the process of A/B testing and highlights its importance in understanding the impact of changes. In this session, Bertil will walk you through the concept of A/B testing, its limitations, and why it is a valuable approach for measuring subtle behavioral changes and user experiences. The presentation will focus on practical examples, avoiding complex statistical terminology, and using simple Excel queries to demystify A/B testing. Discover how you can leverage A/B testing to gain meaningful insights and make data-driven decisions without relying solely on statistics.
Gain a deeper understanding of survivor bias and the challenges associated with before-and-after tests. Bertil will also discuss the importance of controlling experiments and provide real-world examples across various domains, including medicine, business, and technology. Whether you are a technical leader, marketer, or business professional, this webinar will empower you to embrace A/B testing as a powerful tool for experimentation and decision-making.
The webinar focuses on simplifying A/B testing and highlighting its significance in understanding the impact of changes. It covers practical examples, avoids complex statistical terminology, and provides insights into survivor bias and the challenges of before-and-after tests.
Key Takeaways
- A/B testing is a valuable approach for measuring subtle behavioral changes and user experiences.
- A/B tests are not limited to statistical experts and can be understood using simple Excel queries.
- Before-and-after tests have limitations and can be influenced by factors such as overall trends, seasonality, and convergence to the mean.
- A/B testing helps to control experiments and avoid survivor bias, ensuring more accurate results.
- Examples from different domains, including medicine, business, and technology, highlight the importance of running A/B tests.
- A/B testing requires a significant sample size to obtain reliable and statistically significant results.
- Implementing A/B testing tools, like Split, can simplify the testing process and enhance decision-making capabilities.
- A/B testing allows for data-driven decision-making and optimization of strategies in various fields.
Overall, the webinar aims to demystify A/B testing, encourage its adoption, and empower participants to leverage it as a powerful tool for experimentation and decision-making.