We're now in part 11 of the The Noisy Data Arc. We ended part 10 recognizing that you can create reports about machine components and, while these are higher level reports, they don't require as much data as general level reports.
Here we discover that this model isn't necessarily true when reporting on the humans using the machine components.
Answering questions about humans interacting with information (which is what NextStage does) is a different matter because people have this nasty habit of not being simple machines, and this swings us back into standards and the current state of behavioral metrics. Equating an individual clicking on an ad with anything other than a click on an ad is (to me) dangerous. Human activity is not easily deconstructed into a series of subsystems (my apologies to Skinnerites everywhere). A simple report such as "Are people having a good or bad experience on a site?"
requires the same data as the "drill-down" report "Why are people having a bad experience?" because people don't have a good or bad experience simply because they're having a good or bad experience. There's a reason they're perceiving their experience the way they are, such as "They didn't understand what was offered", "There wasn't enough information for them to make a decision" or "They didn't see what they wanted"
. Know why someone is having a good or bad experience in a cognitive, motivational/effective or behavioral way and you can address their reasons accordingly. Simplify the offering, add more information, add an image; whatever is required to address your market and your business model (for the curious few, yes, these are genuine NextStage reports and demonstrate the kinds of information we provide our clients).
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