Hypothesis-driven & pirate metrics

Pirate metrics, also known as AARRR metrics, are a set of key performance indicators (KPIs) that are commonly used to measure and improve the performance of a product or service. The metrics are acquisition, activation, retention, revenue, and referral, and they can be used to identify the strengths and weaknesses of a product or service.

To identify and execute hypothesis-driven experiments that will lead to step-change improvement in pirate metrics, you can follow these steps:

1. Define the problem: Identify which of the pirate metrics are performing poorly and need improvement. This could involve looking at data such as conversion rates, customer churn, revenue, and referral rates.
2. Generate hypotheses: Once you have identified the problem, generate a list of hypotheses that could explain why the metric is performing poorly. For example, if the retention rate is low, a hypothesis could be that users are finding the product difficult to use.
3. Prioritize hypotheses: Prioritize the hypotheses based on their potential impact on the pirate metrics and the feasibility of testing them.
4. Design experiments: Design experiments to test the prioritized hypotheses. The experiments should be designed to be hypothesis-driven, meaning that they should be designed to test a specific hypothesis.
5. Conduct experiments: Conduct the experiments and collect data. The data collected should be analyzed to determine whether the hypothesis was correct or not.
6. Draw conclusions: Based on the data collected, draw conclusions about whether the hypothesis was correct or not. If the hypothesis was correct, determine what changes need to be made to the product or service to improve the pirate metrics.
7. Implement changes: Implement the changes identified in step 6 and monitor the impact on the pirate metrics. If the changes lead to an improvement in the pirate metrics, the experiment was successful.
8. Iterate: Repeat the process, generating new hypotheses and designing experiments to test them. This iterative process will lead to continuous improvement in the pirate metrics.

In conclusion, identifying and executing hypothesis-driven experiments is a critical part of improving pirate metrics. By following the steps outlined above, you can identify the problem, generate hypotheses, prioritize them, design experiments, conduct experiments, draw conclusions, implement changes, and iterate to continuously improve the pirate metrics.