Not in the slightest unfortunately. Often customers don’t even know what customers want, and the subgroup that actually responds to these aren’t necessarily “average”
Not in the slightest unfortunately. Often customers don’t even know what customers want, and the subgroup that actually responds to these aren’t necessarily “average”
That seems like one hell of a hand waving away the opinion.
You do realize that was used for decades before computer’s and the Internet was a thing, right?
And they do things like blind tests so they get audiences that are average.
Actually, except for the deepest debugging data that only a programmer would want, you’re incorrect. And the conversation wasn’t just about that one minority type of data set.
All that information is important for the dev itself sure, but also for the UI people, the UX, the product manager, etc.
I mean, I just retired from a career as a self-employed incorporated UI/UX software developer for Fortune 100 companies, but what the fuck do I know, right?
The data telemetry that you are describing is data overload and ends up being not efficient to know. The truth gets lost in the quantity noise.
You have to study the usage patterns of how people use the software, by actually watching people use the app, and you don’t get that from just some counter in memory counting how many times a certain button was pressed, there’s no gestalt in that data set. Great data for selling to third parties, but not for helping you with the UX of an app.
It’s my professional advice that I feel confident in the opinion I expressed on this matter, learned from literal experience on the ground.
Focus groups and customer surveys work really well.
Not in the slightest unfortunately. Often customers don’t even know what customers want, and the subgroup that actually responds to these aren’t necessarily “average”
That seems like one hell of a hand waving away the opinion.
You do realize that was used for decades before computer’s and the Internet was a thing, right?
And they do things like blind tests so they get audiences that are average.
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Actually, except for the deepest debugging data that only a programmer would want, you’re incorrect. And the conversation wasn’t just about that one minority type of data set.
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I mean, I just retired from a career as a self-employed incorporated UI/UX software developer for Fortune 100 companies, but what the fuck do I know, right?
The data telemetry that you are describing is data overload and ends up being not efficient to know. The truth gets lost in the quantity noise.
You have to study the usage patterns of how people use the software, by actually watching people use the app, and you don’t get that from just some counter in memory counting how many times a certain button was pressed, there’s no gestalt in that data set. Great data for selling to third parties, but not for helping you with the UX of an app.
It’s my professional advice that I feel confident in the opinion I expressed on this matter, learned from literal experience on the ground.
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