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For Kitchen Nightmares that’s true, but Hell’s Kitchen is another story altogether for his persona.
You’re bang on. It’s called MaxDiff. I use it frequently in my line of work to prioritise product or service messaging with panel data. It’s better in some cases to use Inferred preference rather than stated, but generally good to keep the options comparable in “size” of offer.
I would never interpret a MaxDiff model low end result as “wow, 5% of people want slower browsers.” Instead I’m focusing on the top cluster. As with any model, they’re only ever so accurate. Don’t read into the questions too much.
It’s an Inferred importance method, as other users have commented it is likely that there are some calibration metrics in there. MaxDiff is the name of the approach if you want to check out more.
But hey, maybe you’d be able to score some valuable Beanie Babies.