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October 22, 2019

Data Analysis Toolkit for Early-Stage Startups

David Smith

A powerful compilation of free tools and custom code that any startup can adapt to turn raw data into visual insights.

Most of the world will make decisions by either guessing or using their gut. They will be either lucky or wrong — Mixpanel founder Suhail Doshi

If you can’t measure it, you can’t improve it — renowned management thinker Peter Drucker

Turn Data into Insights

There are lots of reasons why the data your startup is collecting is important: managing your team, impressing investors, delighting customers, planning for the future, etc. But which data? Where do you get it? How do you turn it from raw information into coherent story? And how can you do that on a tight budget? To answer those questions, TheVentureCity has released the Data Analysis Toolkit for Early-Stage Startups to help founding teams who want to supplement their gut and intuition with data-driven insights.

Measure What Matters for Growth

The Toolkit helps startups understand growth accounting, cohort retention, and engagement.

  • Growth accounting categorizes users each week or month according to when they last used the platform. This helps you understand both how quickly and efficiently the business is growing. The Quick Ratio is a metric that encapsulates growth and efficiency in one number; for a more in-depth discussion, see our post Quick Ratio as a Shortcut to Understand Product Growth.
  • Cohort retention metrics help us see how long users continue to use the product after the first time they use it. Good retention makes growth so much easier and efficient: newly-acquired users count toward user growth rather than having to replace lost users.
  • Engagement metrics gauge the extent to which users find value in the product by measuring the frequency with which they use it. In this way, we can use data to assess and track product-market fit, an important but tricky concept for which data and intuition are both important. Solid engagement sets the stage for retention over a long period of time.

Practical Tools

The Toolkit consists of a GitHub repository consisting of a series of Jupyter notebooks (published via Google Colaboratory), Python code, and sample data. These pieces interact with Google Sheets and Google Data Studio, free tools that enable data storage and visualization. By combining working Python code with a discussion of how it works and why it is important, we designed these notebooks to be practical tools that you can use right away or adapt for your business. In this way, you can learn on your own by analyzing of your startup’s data.

Even if you do not have a dedicated data analyst at this time — and most of early-stage teams of 5–10 members do not have that role — make sure there is somebody on your engineering team who is tasked with instrumentation and analysis. It is this person who most needs to review the Data Analysis Toolkit.

For more on data and growth from TheVentureCity, please visit:

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