A/B testing is a simple way to reduce uncertainty in decision making by providing a data-driven way to determine which version of a product is most effective. The concept of A/B testing is simple.
- Imagine you're at a friend's birthday party. You've worked hard to perfect your cookie recipe. You think you've perfected it, but you don't know if people will prefer the cookie with or without oats. In your opinion, the oats give the cookie a nice chewy texture. However, you're not sure if this is a widely held opinion or just a personal preference.
- You end up showing up at the party with two different versions of the cookie: Cookie A has oatmeal in it and Cookie B doesn't. You randomly give half of your friends Cookie A and the other half Cookie B.
- You decide that the cookie that gets the most “mmm”s is the best cookie.
- Once everyone has tried the cookie, they discover that Cookie B has more “deliciousness” and conclude that it is the best cookie.
