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For the first, it's sufficient enough to just look at the number of page requests.

For the second, I never got explained to me how UX analysis really works for news sites. Isn't it enough to put 2 or 3 people in a room and show them a few variations of the UI? There isn't really much to publishing text, images, and a few graphs. Graphs are a very well explored field, I don't think you can learn more about them by just watching hot maps and click through rates.



I suspect there's lot of bullshitting happening around "UX analysis", with third-party "experts" offering analyses which may, or may not, show something significant. As long as everyone in the chain can convince their customer/superior that their work is useful, the money will flow, whether or not the work is actually useful.


That's one of the fundamental problems in tech today, namely:

"It is difficult to get a man to understand something, when his salary depends on his not understanding it.”


It absolutely isn't sufficient to look at the number of page requests. How do you discern like-reads vs hate-reads? How do you determine whether someone clicked on an article, read the first line, and then bailed vs read the whole thing? There are a heap of metrics used to determine engagement which factor into the material decisions referred to in the grandparent.


Why do you need to track user behavior across unrelated domains to achieve any of that?


It's pretty simple, try a few different designs with A/B testing and you will see which one has the most revenues.

However the result will usually be a lot of dark patterns. For instance, that's why you get popup to ask you to register.


Server logs just aren't sufficient, no matter how many times hn says so. You don't get enough data to make data-driven decisions. Thats like giving a data scientist 1/3rd of the available data, and saying "thats good enough".

You'd expect ux to be a small unit, but that includes everyone who works on revenue-generating ads. Moving one tiny thing has a direct impact on revenue, which affects every person employed by nyt.


>Thats like giving a data scientist 1/3rd of the available data, and saying "thats good enough".

And it could easily be enough. Having 1/3 of a quantity of something doesn't mean you barely had enough before.




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