
A/B测试在wikipedia上的定义:
A/B testing, or split testing, is a method of advertising testing by which a baseline control sample is compared to a variety of single-variable test samples in order to improve response rates. A classic direct mail tactic, this method has been recently adopted within the interactive space to test tactics such as banner ads, emails and landing pages.
Significant improvements can be seen through testing elements like copy text, layouts, images and colors. However, not all elements produce the same improvements, and by looking at the results from different tests, it is possible to identify those elements that consistently tend to produce the greatest improvements.
既然是“a method of advertising testing”,再来看看在Adwords Help里的定义:
An A/B experiment allows you to test the performance of two (or more!) entirely different versions of a page. Start with your original test page — the page whose content you want to test — then create alternate versions of that page. You can change the content of a page, alter the look and feel, or move around the layout of your alternate pages — whatever you choose. We’ll vary traffic to your original page and your alternate versions, to see what users respond to best.
A/B测试使用范围:
A/B测试其实不单可评判网络广告有效性,在评估交互设计、信息架构有效性时同样可以使用。
A/B测试局限性:
- 只适用于那些有着一个清晰、且各方面都很重要的目标的项目
- 每次只能更改一个变量,当影响要素很多、关系复杂时会有干扰
- 只能使用完全实施好了的设计,这对于成本是一个考验
A/B测试注意事项:
- 每一次就更改一个元素
- A/B测试的时间应该在同一个时间区域
- A/B测试的单元应该使用相同的分析指标
- A/B测试的单元应该针对相同的客户群体
- 使用权重,避免一个未知的处理危险你的业务底线
其他参考: