Data-Informed Product Building by Sequoia (Mar, 2019)

The Bible for Giraffe Startups. An extense compilation of articles about how to build online products taking care of the data. The product life-cycle, most important metrics in every phase, retention, engagement and so on.

A Quantitative Approach to Product-Market Fit by Tribe Capital (Jul, 2019)

This article is a must. Product-Market Fit is hard to measure. However, this approach is awesome to put some light on what is happening with your users and how they interact with your product. They build a multidimensional plot to understand what is happening inside but for me the greatest creation is the generalization of "Product-Market Fit unit".

How Superhuman Built an Engine to Find Product-Market Fit by First Round (2018)

Yeah, Product-Market Fit is hard. This is a completely different approach that instead of user data, asks directly to the clients about how they feel about the product. Then NLP is used to improve the product focusing on fans' opinions.

• You can try their interactive tool with your own data.

The red flags and magic numbers that investors look for in your startup’s metrics by Andrew Chen (date?)

An essential article to understand growth. How to build acquisition and engagement loops. The basis of Reforge.

How to De-Risk a Startup by Leo Polovets at Coding VC (Oct, 2016)

A framework to see startups as a list of risks and then asses them individually. This one is difficult to apply because it uses qualitative information to asses a quantitative approximation. However, it's great to create discusions around your business and find weaknesses.

How to design a dashboard by Matt David at Chartio Data School (2019)

An introduction on how to choose metrics, how to measure them, what kinds of charts can be used and what matters on building your own dashboard.