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by g_p
1324 days ago
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This is an interesting example, and perhaps pushes part of the blame and dislike for A/B testing onto tech companies' incentives. If you're building a tool to make life easier for the user, something that gives them a better experience is your optimal outcome. This seems like a scenario where A/B can produce a good outcome. The challenge is when you throw in an ad-based revenue model, and the A/B testing is then optimized for the opposite (eyeball-hours, linear metres scrolled per session, ad spots passed, ads clicked) - engagement-based business models end up (I'd argue) A/B optimizing for the opposite of what their users want, to get them to spend longer doing a task they could have done quicker. |
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The funny thing is - the ad-based revenue model is not the only possible variant. Last time I’ve checked Facebook’s profits per user were $7 per quarter, that is $28 a year. At the same time I am paying LiveJournal $25 a year for the ad-free version. Just taking my money looks like a much better model in many respects:
- less overhead: a lot of people doing these studies how to force me to look at something I do not want to look at will be free to do something more useful to the society;
- streamlined relationship between me and my publisher: in this model there is no advertiser who can say “I do not like these texts, no revenue for you”.
That’s why I prefer to pay for some Substack authors, like Matt Taibbi and Glen Greenwald, than to try to fish their texts for free amid some sea of “clever” advertising (hey AI testers, I bought this thing already, what’s the point of forcing it on me again and again?).
I kinda wish that Brave model (my money distributed between sites I visited) got more traction. It looks much more healthy.