Hey, I was browsing youtube in private mode, and out of nowhere it started looking like this, I really hope this doesn’t go through lolol…

(the black square bottom right is probably an ad being blocked.

  • jimmydoreisalefty@lemmy.worldEnglish
    64·
    5 months ago

    They are always testing changes to different groups of people.

    Not too sure how that works, but if you wnat the old layout you can add extensions.

    Quick search results in:

    How to Undo YouTube’s Terrible New Layout [Jake Peterson | May 23 2024 | LifeHacker] https://lifehacker.com/tech/how-to-undo-youtubes-terrible-new-layout

    How to Get Old YouTube Layout Back: Simple Steps for Nostalgic Navigation [July 18, 2024 | bytebitebit] https://bytebitebit.com/tips-tricks/how-to-get-old-youtube-layout-back/

    • Schal330@lemmy.worldEnglish
      7·
      5 months ago

      It’s likely A/B Testing and when people receive the new layout, if Youtube sees a drop in engagement for their experiment they may just ditch it.

      • jimmydoreisalefty@lemmy.worldEnglish
        34·
        5 months ago

        Oh, thanks for the link!

        Edit: added a bit of information below for those interested

        A/B testing (also known as split testing or bucket testing) is a methodology for comparing two versions of a webpage or app against each other to determine which one performs better. A/B testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal

        In an A/B test, you take a webpage or app screen and modify it to create a second version of the same page. This change can be as simple as a single headline, button or be a complete redesign of the page. Then, half of your traffic is shown the original version of the page (known as control or A) and half are shown the modified version of the page (the variation or B).

        The following is an A/B testing framework you can use to start running tests:

        1. Collect data:
        2. Identify goals:
        3. Generate test hypothesis:
        4. Create different variations:
        5. Run experiment:
        6. Wait for the test results:
        7. Analyze results: