Summary

What did we learn?

In this chapter, we learned that by aligning the incentives of various stakeholders while avoiding gameable metrics, cannibalizing metrics, and cognitive biases, we can create a more successful analytics strategy for our product.

It is important to ensure that everyone involved in the product has a clear understanding of the goals and objectives of the product, as well as how their work contributes to those goals. This can help ensure that stakeholders are aligned in their incentives and are working toward a common set of objectives, rather than pursuing their own agendas.

We learned how to avoid gameable metrics by choosing metrics that accurately reflect the desired outcomes and cannot be easily gamed or manipulated. We also learned how to avoid cannibalizing metrics by ensuring that the metrics being used to track the success of the API product do not conflict with or undermine the metrics being used to track the success of other products or initiatives.

Finally, by being aware of cognitive biases, we can be mindful of how our own beliefs, preconceptions, and mental shortcuts can influence our interpretation of data and our decision-making processes. By being aware of these biases and taking steps to mitigate their impact, product managers can make more objective and data-driven decisions.