Data-Informed Product Design

Use data from a variety of sources to inform your design—analytics, A/B tests, social media sentiment, customer service logs, sales data, surveys, interviews, usability tests, contextual research, and other studies.
Include numbers and context. Whether you call them quantitative and qualitative, studies and nonstudies, or Big Data and thick data, you need the numbers and the context to tell the real story.
Ensure that data is sensitive to the complexity of the human experience. Use averages sparingly, infer with caution, corroborate liberally.
Use data to track changes over time, explore new patterns, and dig deeper on problems

No process is one-size-fits-all, though. Depending on the goal, different combinations of data sources might be more actionable.
For acquisitions, you might want to pair analytics and competitive data from a source such as Alexa or SimilarWeb. To understand content strategy, combining specialized analytics from Chartbeat with intercepts might be the way to go. Understanding the recommendation cycle might require a combination of NPS scoring with interviews and social listening. The key is to create a multidimensional pictu

Bringing in more sources of data can reduce bias, but all data has some kind of bias.