Off the point of Structured Journalism, but on the point of business models, some comments on this post that Ross sent me.
Basically, it’s about Demand Media and how, by algorithmically determining what people want to read, the company can predict associated ad revenue and build content to spec and cost – hence turning in some nice profits. It’s an interesting concept, although not necessarily directly related to journalism business models – but gives some interesting insights nonetheless on the notion of demand-led content and predictive models for ad revenue.
First, a side comment: At $15 a pop for content, frankly, Demand Media would be profitable regardless of what algorithm they use. Low content cost is probably a big part of their business model, never mind predictability of ad revenue. But of course being able to predict user demand means they waste less on content generation and drive margins up. But still.
More broadly, the question of being able to accurately predict ad revenue is an interesting one. Here’s a thought experiment: If we take the view that a journalism outfit wouldn’t want to produce only things that people are searching for, because there’s a public interest need, or a corporate mission, or a burning individual passion to cover something (not unlike an artist’s decision to create a piece of art he wants to, rather than what will sell), then let’s assume for the moment that the newsroom would still just work on what they want to work on. But what if the predictive model could tell you accurately which of those stories would make money and how much? How much would or should that change newsroom behavior?
What if we knew to the dollar how much each movie would make, before we made it? It doesn’t mean that we’d only see Transformers 5 in cinemas; lots of small indie movies make money too, and presumably would continue to be made. Will mediocre movies die out? Will people subsidize pet projects they know would be money-losers with more profitable ventures?
I don’t know, but it seems an interesting universe to inhabit.
That said, it’s a fair point to ask if journalists should just do what they want to do and not be influenced by the wishes of their readers. Of course they should know what people want – and that’s the point that Jay Rosen and others have made. A little knowledge is an important thing when it comes to reader metrics – even if journalists don’t usually like the answer.
But reader metrics aren’t everything either. And nor are algorithms, which nearly by definition measure what they’ve been tasked to measure. Google’s great, but at the end of the day it is a highly-tweaked engine that matches up some sets of human behaviors with word patterns and all that.
But that is useful knowledge – as long as we remember that there are limits to its wisdom.