Directional data (AKA directional indicators) signals trends or changes in KPIs, business metrics, or experimentation results
What is Directional Data?
Directional data (AKA directional indicators) is statistical insight that signals trends. In ecommerce experimentation, directional data provides teams with sufficient information to make observations and informed decisions about the impacts the test variants are having.
It differs from statistically significant data, which is precisely calculated to determine what experimentation results should be considered accurate (and the test components – like sample size and test duration – needed to achieve that level of accuracy) because directional data is about observing statistical results and extrapolating their meaning – being data-informed rather than data-driven.
Leaning more heavily on directional data indications than on formulating an experiment's framework on what's required for statistical significance removes much of the painstaking rigor and long wait times from the testing process. With the belief that tests don't have to be a perfect science, but also the readiness to re-implement or iterate tests to gather more insights, teams are empowered to make decisions faster, move faster, and scale experimentation faster.
