Katie Bauer!

I was recently talking to a friend who is also a DS, and the idea of a "data science spidey sense" came up. It's a goofy name, but a real thing--substantive expertise. IMO this is the most underrated part of the famous Drew Conway data science Venn diagram.

"Math and stats knowledge" and "hacking skills" are crucial too, but they're more generalizable and (at least these days) have more widely available learning resources. It's much harder to study your way to being an industry insider, especially since your network is part of that

The good news is that there's One Simple Trick for getting your bearings quickly. If you understand the business model of your company or the product you're working on, everything is a lot easier.

To determine your business model, ask yourself what your users or customers need to do for your team to be successful. Sometimes this is directly tied to money (the user needs to see ads so we can generate revenue), sometimes it's not (the user needs to create new content).

Once you've got metrics, you can get into benchmarks. It's obvious that you should compare yourself to competitors in your vertical, but how do you compare to non-competitors that have the same business model?

This isn't to tell you where you should be, per se, more of a way of understanding how other businesses use these metrics to measure their strategy. To make this a little more concrete, let's compare two hypothetical businesses.

Company A sells a subscription box for hiking snacks called GORPorate. Company B is a productivity suite called SrsBsnss. Both are fundamentally based around subscriptions, and as a result, both care about conversions and churn, as well as customer acquisition costs.