Save Your Gut For Food: Embrace Data-Driven Decision Making

The following is a guest post by Victor Echevarria. If you’d like to contribute thinking here, please read the guidelines.

My gut is good for digesting food, telling me when I’ve eaten too much, and groaning loudly when I’m about to get hungry. Never, despite efforts to the contrary, has it helped me pick stellar stocks, win a poker tournament, or find the perfect product-market fit.

Yet how often in our professional lives do we catch ourselves saying “my gut tells me that ….” (fill in the blank with a massively self-biased view of the world) as a justification for a critical decision, be it personal or professional.

Nothing, however, can substitute good, old fashioned data as a structured way to guide your thinking. Gut checks certainly have their place – very few open up Excel to determine whom they should marry – but we tend to overly rely on gut because, let’s face it, collecting and analyzing data is hard.

Gut feelings have also led to world class companies – however, I’d call that form of gut feeling, “vision,” and most visions are wrong anyway.  Gut feelings may lead to ideas, but those ideas are hypotheses and should be tested rigorously and abandoned if the data indicate that you were wrong.

Basing a course of action on data involves two steps: collection and analysis.  And there are now many ways to collect illuminating data that are within the reach of all digital professionals:

  • Internet research – dig deep into Google, Wikipedia, Yahoo finance, company financials, blogs, etc.
  • Surveys – Ask your constituents the kinds of questions that will help guide your next actions.
  • Inexpensive experiments – Run AdWords campaigns or other paid tactics to gauge interest around an idea (the web makes this easy and affordable).
  • Collect data in your product – track a user’s clickstream, observe what they buy ask them about themselves, figure out where they came from.
  • Third party services – Google Analytics is your friend.  Or look at someone like Rapleaf or Qwerly that can give you additional insight into your individual users.
  • Look at the data you’ve already collected! – Even if your product’s database isn’t structured to collect tons of data, you already have tons of data like shopping carts, product reviews, or locations.

Analyzing data is a bit more nuanced, but you can still be systematic about it.

Some trends will be obvious, like finding that all your customers are concentrated in a single zip code or that every public company that specialized in subprime mortgage backed securities is in the dump.

Some trends are more subtle, and you can’t statistically analyze every data field in some magical multivariate linear correlation whozamawhatchit flux capacitor machine.

Rather, you have to hypothesize (i.e. use your gut feel) as to what trends you might spot and then analyze the data to prove or disprove your theory. Pivot tables and regression tests are invaluable tools to this end. Graph the data in case the side of your brain that likes pretty pictures is better suited to spotting trends. Use those trends to form new hypotheses and test them the same way.

We’ll all be better off in the long run using data to guide our thinking instead of throwing darts with our gut feelings.

Victor Echevarria is head of customer acquisition and retention for TaskRabbit where he builds strategies around a data driven customer discovery process.  He is a firm believer that a quantitative approach to product and marketing can generate tremendous word of mouth awareness. Follow Victor on Twitter, and check out the TaskRabbit Blog for more ideas from the TaskRabbit team.

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