We have been utilizing Causal for conducting feature and A/B tests. This tool has aided out decision-making process by providing detailed insights into each feature's performance. These insights empower us to make well informed, data driven decisions. Im a huge fan of Causals user interface, that has allowed us to directly set the new control value. This feaure not only expidites the decision-making process but also eliminates the need for code modifications after a decisions is made. This efficiency saves us valuable time and resources, ultimately streamlining our workflow.

For me, the best part about Causal Labs product has been their employees. Everyone I've interacted with there has been highly engaged, curious about how their work is perceived, how people use it, and whatever they can do to make it better. The employees are all strongly committed to their clients, trying to make their lives better by adding value in solving the problems that need to be solved.

1. Built-in statistical modeling that avoids common pitfalls in analyzing A/B tests. 2. Encourages structured, well-defined A/B tests. 3. Makes it easy to run tests that cross layers of the stack. 4. Provides easy integration with our data warehouse, even for event generation that is unrelated to a specific A/B test. 5. Installation of impression servers in our own cloud means that it has a very low impact on performance. 6. Causal team is fantastic and very responsive, including supporting our internal training and adoption.