The Quick and Dirty on A/B Testing, Statistical Significance, and Sample Sizes
Thursday, March 21st at 3 ET / 12 PT Approx 90 Minutes
Add some science to your digital program! A/B testing is a powerful way to optimize web pages, ads, emails, and other digital communications. Whether you’re raising money or activating audiences, testing can improve your results dramatically. In this webinar, you will learn the basics of test design, sample size selection, and calculating statistical significance. Plus many compelling case studies.
Co-Founder and CEO of Pantheon Analytics
Amelia Showalter is the Co-Founder and CEO of Pantheon Analytics. In 2012 Amelia served as Director of Digital Analytics for President Obama’s re-election campaign, where she led a cutting-edge team that designed and implemented hundreds of online experiments. Previously she provided data analysis and microtargeting to dozens of campaigns as a strategist at Changing Targets Media and MSHC Partners.
After the Obama campaign, Amelia established a solo consulting practice, helping her clients adopt data-driven strategy and a culture of rigorous testing. An experienced speaker and trainer, Amelia has given workshops and speeches around the world, including a popular TED talk about A/B testing at TEDxAthens. Amelia graduated cum laude from Harvard University and holds a Masters in Public Policy degree from the Harvard Kennedy School of Government
Digital Directors and organizational leadership this is an essential training in understanding how to power your engagement growth with A/B testing! From conversions on actions to increasing fundraising.
Data staffers, email campaigners, and anyone looking to develop a deeper understanding of A/B testing will appreciate will find real value in this training. Perfect for data nerding out.
If you love data but your organization isn’t that big yet this training will give you a deeper understanding where you can with A/B testing.
● What is A/B testing & why does it matter?
● Email testing
● Page testing
● Even more types of testing
● Statistical significance
● Sample sizes
● Case studies
● How to maintain a good testing program