Tagged: Twitter

Per Axbom reply Twitter

↪ Replying to @JesperBylund

@JesperBylund I do think the minority aspect is a feature of A/B-testing that should be called out. A/B-testing can (sometimes) be effective in boosting profits, but can be at the expense of select people being sidestepped - which the test will rarely show. So - yes - skewed, with real impact.

@JesperBylund And of course I'm also critical of the dogma. :)

@JesperBylund If you test blue and pink cupcakes against each other you may find more blue cupcakes eaten at the time, place and by the people you test them with. But if you don't talk to people you won't find out about allergies. And why a number of people still preferred the pink ones.

🔗 Originally posted on Twitter

Per Axbom reply Twitter

↪ Replying to @JesperBylund

@JesperBylund Not at all. I would argue it all depends on what you're trying to achieve, and what you believe the data is saying. Understanding the data is key, not a focus on declaring "winning" designs.

@JesperBylund You do need to complement statistical testing with focused qualitative research with a diversity in health, experience, status, ability, etceteras – if you are trying to achieve inclusive design.

🔗 Originally posted on Twitter

Per Axbom Twitter

This x 1000 🔥🔥🔥

A/B-testing excludes minorities by design.

A/B-testing promotes the way of the majority. If you are harmed by the design you may ignore it, make mistakes and/or have autonomy/health/privacy stolen from you. But it won't make a blip in an A/B-test. x.com/beantin/status…

And of course an A/B test also won't uncover harm to the majority as long as it's hidden from them. How well that harm is hidden is perfectly optimized with an—you guessed it—A/B test.

🔗 Originally posted on Twitter