this post was submitted on 16 Sep 2023
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Jesus Christ, that is as hilarious as it is painful. You'd think they look at their own click-through stats for a site and realise that it's popular enough, but you'd be wrong.
Anyway, you earned yourself a bookmark.
Yes, exactly. I don't understand their need for content on a site. Shouldn't it be enough from their point of view to have a as most sites as possible integrating their ads? Why bother about the content?
Working in BI, I'm afraid I have a possible explanation for how it came along. It's a stupid one and may be entirely erroneous, but it lines up with what I know. Take it with a grain of salt, in any event.
It probably emerged from some analytics indicating that certain types of websites with certain traits retain a lot of long-term traffic, leading to terribly oversimplified assumptions and resulting guidelines about what makes a website profitable for them.
Knowing manglement and BI, they might not understand the full complexity of such analyses, and the analysts themselves may not understand it either, and the ones engineering the data models to feed the reports to detect those trends to inform management may have a flawed understanding of both the data structure and the semantics of it, and of the way their facts will filter through into insights and finally decisions.
So eventually, some analyst shows charts displaying X fact sliced by Y dimension, and the key influencers that emerge from those charts end up being "blog pulls more than no blog", "traffic scales with content" and so on, and from there, the executives decide the policy to favour sites with blogs and enough content.
You might be interested in one of my oldest posts: https://theluddite.org/#!post/why-attention-economy
It's about what you're saying. I come to an adjacent but slightly different conclusion than your comment.
So if I'm reading this right, what you're saying is that the content bloat exists so that existing engagement metrics look better? That tracks. The idea that they're grasping entirely wrong facts instead of "just" misunderstanding the dimensions' causal relations, didn't occur to me, but given that it's a simpler and still just as plausible explanation, Occam's Razor suggests it's more likely. In fact, I'd bet it's (more) correct.
In my naive position as BI developer, I tend to insist my "customers"/consumers focus on clarifying the questions they want to answer, so that I can find the appropriate measures to calculate, then work on narrowing down the disconnect between what data I have and what they want to know.
Of course, the situation "my consumers have latched on to this specific measure, how do I explain that it doesn't actually answer the question they're asking?" and the related problem of "how do I explain that the question they're asking isn't quite as simple?" occur often enough, but between the faith in my abilities and understanding of our data (on which I've become the de facto authority) and my own practice at picking examples that show such disconnects, it's usually little more than a routine exercise.
But most of my consumers (or at least the contacts for my models and reports) are operative or lower management that have either been relying on my service for years now or come to me after word-of-mouth from other people that have, so the bullheadedness of C-level executives just grabbing a single, intuitive measure and holding on to that - actual semantics be damned - is far from my daily business.
Yup that's about right. I think the obsession with engagement comes from a cultural desire to appear objective. It's performative more than it is rational.
Yeah, that one is on my To-Read-List still. I'll move it up.
Yeah, the broken Internet is just so much dumber than people think. Welcome aboard!