January 27, 2019
One of the major projects I’m currently tackling at ScreenCloud is building the foundation of our data gathering and analysis infrastructure.
We’re growing quickly and as the company scales, so do the questions we have about our customers, product usage, financials, and more. This seems like a common issue when startups get close to the ~50 employee mark and start to outgrow tools like Mixpanel or Amplitude.
I’ve spent the last few weeks talking to experts, reading blog post, and analyzing the pros and cons of different analytics stacks. I decided to highlight some of the best writing I’ve found on the subject to make it easier to for anyone else that is looking to get their head around this space.
Tristan from Fishtown Analytics wrote a great guide called The Startup Founder’s Guide to Analytics – ThinkGrowth.org. What makes this a great starting point is that he doesn’t just prescribe a single “best” solution for everyone. Instead, he helpfully breaks down his advice by different startup stages.
Stephen Levin, who currently works at Zapier, has one posts in particular that would be helpful to read at this stage: Advanced startup analytics – Part 1 – Philosophy.
Another important concept to get your head around is what pieces an analytics stack actually consists of. Once again, Tristan has a short blog post where he describes what ETL, Databases, Data modeling, and BI tools are and what they do.
As Tristan mentioned in the first blog post I linked to above, if you’re a startup with less than 20 employees than you don’t need things like data warehouses, BI tools, etc. yet. Instead, install a tool like Mixpanel or Amplitude, which should give you more than enough information for now.
If that’s your current stage then I recommend reading through the content written by Ruben and the team over at the Practico Analytics blog. They have amazing in-depth guides on Mixpanel, Amplitude, setting up a tracking plan, and much more.
If you’re starting to outgrow these tools then read on.
Once you understand what’s involved in building out a stack, it’s time to choose the right tools.
ETL provider Fivetran published a short but useful overview of the best data warehouse options, including strengths and weaknesses, on their blog.
ETL, BI, Data Modeling
Stephen Levin wrote a series of blog posts comparing different tools. These should help you get an idea of what’s out there and what could be a good fit for your company.
I’ve talked to a number of people and while I haven’t worked with them (yet), they all came highly recommended. In case you’re looking to get help building out your analytics stack, these are a few people who know what they’re talking about:
I'm a fullstack marketing developer working remotely from Europe and Asia. Sign up below to get my posts delivered to your inbox.