Mixing Qualitative and Quantitative Feedback

Balancing quantitative and qualitative metrics

Quantitative metrics provide objective and numerical data, which can help eliminate bias and subjectivity. By analyzing these metrics, we can make informed decisions about the performance and efficiency of our API without being swayed by personal opinions or preferences.

Qualitative metrics, on the other hand, provide a more subjective evaluation of the API and can help identify areas that may not be captured by quantitative metrics. For example, customer feedback may highlight issues or concerns that are not reflected in numerical data. By gathering this type of data, we can get a better understanding of how an API is being used and perceived by our customers and address any potential blind spots or biases. Qualitative and quantitative data work well together because each kind fills in what the other lacks.

We might see patterns in the numbers we already track. For example, most of our customers don’t use a particular feature. Then, we could add qualitative research, such as one-on-one interviews, to find out why customers aren’t using that feature. The insights from the interviews will make it easier for us to figure out how to solve the problem. But remember that the information we get will only help if we know what we want to do. Set ambitious goals and use data to guide us towards them. Data may not tell us exactly where to go, but it can help us weigh the pros and cons of different ways to achieve our goals.

Qualitative and quantitative data are deeply connected to the product strategy and guide all product roadmaps in the right direction. They are the yin and yang of product insights. The following illustration shows us how product strategy is a good mix of qualitative and quantitative insights.