In theory, these data collectors are getting their data from the best source — straight from the users themselves. But in both cases, it backfired. I assure you, it’s not just limited to these two examples. I’m talking about self-reported data, and I’m here to tell you that you should trust big data before you trust self-reported data every time. Every. Time.
In this data-driven world we are conditioned to believe that all data is good data. But self-reported data is especially faulty beyond just the usual margin of error from sampling errors or respondents just randomly completing the questions to get it over with. Usually, self-reported data falls short for three reasons:
The best way to analyze user behavior, preference, satisfaction, or feeling, is to analyze their actions, not their words. Where users browse online, what they click on, what they search for, at what point they abandon your cart, what they buy, what they listen to, what others who bought that item also buy, etc., will tell you a lot more about them than they themselves ever could.
This was not possible a few years ago, but this data and petabytes more can now be consumed by BI applications, predictive analytics tools, and machine learning software to predict user behavior and uncover detailed answers that no survey ever could.
Don’t trust self-reported data, report the data for the user.