By Mylena Vazquez


Research data is like your password manager for marketing. 

Confused? Hear me out.

Password managers generate a bunch of nonsensical numbers for you to use as a password. You usually don’t get to see those, since the software manages them for you. But if you were to take a peek, you would see long numbers that just don’t make sense. However, when you use your password manager to log in to your site, it’s a breeze. The manager has done the work for you.

Much like password managers, research data can be extremely complex. It can present itself in a string of numbers in an Excel file that just don’t make any sense until you use the key—whether that be converting t-test outputs to “number” format, or sorting columns by responses, or using your criteria to interpret Qualtrics-assigned numbers. 

How you translate your research data matters, but how you interpret it is even more important. At face value, your series of research data numbers, even when organized, can seem to tell a certain story. But as any marketer worth their salt knows, looks can be deceiving. Just like password managers have a built-in interpreter of data, Excel and other software have functions that make it easy for us to know what the data is really saying—or shouting—to us. Running advanced analyses like t-tests and ANOVAs help us do just that.

Ultimately, research data is what gives you access to your audience. It allows you to understand their attitudes and behaviors, their pain points, and their wants. How you harness its power can be the make-it-or-break-it factor in your success as a marketing leader.


How has research data helped you transform into a marketing leader?

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