Why You Want to Watch Out for Related Features

How to build experimentation processes to continuously update your most important decisions.

Cumulative advantage can increase the randomnes in ad performance. We have some ways to see through it, and use it.

We use a different type of statistics (Bayesian) that gives you the probability each option is the best, both during and after your tests.

How Deciding Data's A/B testing service works, providing deeper insights and clearer direction for your ad campaigns.

Experiments that focus on the ideas you are testing, rather than the platform, can help you learn even faster.

A quick overview of the differences between Split Testing and Dynamic Creative on Facebook. They have complimentary goals, so can accomplish great things together.

We help you understand your experiments, by carefully designing their structure and using a type of machine learning that allows easier interpretation.

Happily, there is a technique that does a great job finding the best balance between testing new ads and using the best ones we've found.

A/B ad tests are the easiest way to tell what part of your ad is lifting performance.