Reading about audience data this week, I immediately had flashbacks to my undergrad years where we spoke at length about TV and radio ratings. Traditionally, for radio, these are carried out by survey, where audience members self-report their daily media consumption and answer a bunch of questions about their spending habits. Note, this survey is still done with paper and pen in NZ. TV ratings have developed a little more with the times and are completed by installing a little box on a household’s TV that would record everything they watched (like the Family Guy episode, if you’ve seen it). Over time there have been weird restrictions that serve to exclude anyone but nice, safe, upper middle class families. To once again use NZ as an example, there are 600 boxes for a population of 4.5 million people. Flawed is an understatement, and I could go on for hours pointing out the issues, but the thing is, ratings exist solely to quantify and serve up audiences to advertisers. That’s it. No matter how much time and effort and passion is put into creating quality content, in commercial media the only thing that matters is the ratings, because ratings equal money. The system is archaic and not even close to properly representative of what people actually engage with, but so long as it’s good enough for the advertisers, it’s good enough for the media companies.
Moving into the digital arena and the Amazon (as bookseller and TV producer)/GoodReads/Netflixes of the world, their use of data is different, largely because they’re no longer reliant on advertising revenue to exist. This is a pretty new phenomenon – advertising revenue has been the basis of most media business models for decades, so audience data has, until now, served that purpose. But when you take that structure away and at the same time have technology facilitating unprecedented data collection, what happens?
A radio station can show their advertisers that (in theory) their morning show attracts 180,000 mainly female listeners aged 16-35 so they can sell ads to the kinds of advertisers looking for that audience. The actual quality of the data doesn’t matter much if everyone is happy, and the world turns. However, Jellybooks knows that only 5% of readers finished over 75% of the books they tested, and Netflix knows who finishes what, when, and how many times (and if they had access to my assignment deadlines they’d know why as well). GoodReads’ data is different, but it’s still hugely valuable to the owner, Amazon. Aside from the incredible detail and scale of data that they collect, what they all have in common is that they aren’t using it to sell advertising to external parties, and this seems to be an advantage. It means they only have to focus on what is useful to them, and don’t have to share any of it with anyone. They’re still competing, but they can compete more with their carefully-constructed content and other conveniences and services they offer and they don’t have to worry about keeping advertisers sweet. The Netflix piece mentioned that traditional TV companies were annoyed that Netflix didn’t participate in the ratings system, but they have absolutely no reason to. They have everything they need already.
I’m fascinated by what this means for media industries generally. Advertising-reliant media aren’t facing competition from sales/subscription based media, but Google and Facebook are drawing advertisers away from traditional entertainment media entirely with their cheap, data driven, hyper-targeted advertising options. This puts the pressure on them to get creative, but history tells us that it’s actually likely to make them less creative. Times of financial pressure have led to media becoming extremely risk averse (see: all sequels, all the time). The pressure seems likely to go on traditional media to seek out the kind of data that the digital giants have, and use it to shape their content to play it safe, get their audience numbers, and keep their advertisers interested. But born-digital companies have a structure that supports and facilitates the kind of data collection most companies can only dream of, and it would be nigh on impossible to replicate. There’s a bit of a leap to make from paper surveys to big data.