With all of the recent debate over the future of news as we know it, I have been thinking about the way media coverage is evolving. The idea I’ve been mulling is something I’m calling “content density”, and it’s related to a number of terms we’re already familiar with, such as “popular,” “viral,” “trend,” “meme” and a host of other names that seemed to be getting used almost interchangeably. When boiled down to their most fundamental level, they deal with the relationship between two variables: volume and time. When relatively high volumes of content are produced in a relatively short period of time, producing high “content density,” the result is a “trend” (I’ll try to stick with that term for the purpose of continuity, though it certainly carries proprietary connotations which I don’t necessarily mean to imply). Represented graphically, it’s the peak of the curve.
It’s important to recognize here that I’m using the word “trend” to mean the high point of total exposure across all media. The actual thing being exposed can be nearly anything: a news article, a viral video, a song, a particular brand or product, an advertising campaign – whatever. If it can be read about, seen, listened to, and shared (by means digital or otherwise), it counts.
Trends have been around forever and will continue to be around for a long time. It’s human nature. But the internet is adding all kinds of new twists to the scenario represented in the graph above. For example, while the time axis might previously have been measured in weeks or months, it’s now more appropriate to measure in hours, days, minutes – even seconds. And while we might have once measured the volume of content in sources like magazines and newspapers, the atomic unit of content is shrinking almost constantly, leaving us to measure in articles, blog posts, reactions, comments, tweets, text messages, even individual keywords. Though it comes as no surprise to any of us, what this means is that we are producing more content than ever, faster than ever.
But if we’re interested in content density, we simply adjust the scale of the axes and our graph looks pretty much the same.* But when we take a look at the composition of that content, we find that things have changed dramatically. Where is this content being produced? Who is producing it? And what relative value does it all have? This is where things get interesting. My money bets on a breakdown that looks something like the following graph:
There are several possible variations on this representation, each can be supported by case studies that detail where and when media influence was founded, how it traveled, and which of these tranches carried the load. For this post, suffice it to say that these relationships are changing every day and new models are emerging constantly.
The graph shows traditional “Old Media” producing the least amount of content over the shortest amount of time. I think that current market conditions and changing information consumption patterns will continue to exert downward pressure on this segment of the content landscape. I believe some of these institutions will survive; others, it seems nearly certain, will not.
The second and biggest tier I’ve labeled New Media and Value-Add Social Media. This needs a bit of an explanation. By “New Media” I mean blogs and other blog-like publications that are filling the gap being vacated by traditional media outlets and serving smaller niche markets that previously existed only in much smaller, more diffuse communities. “Value-Add Social Media” refers to any number of media activities that include the sharing, repurposing, and responding to of other original media. In short, it’s any form of media that uses and explicitly references a previously produced piece of content as its basis for creation or main point of contention. Examples of this behavior can be found on almost every “social media” platform, from Facebook and YouTube to newer applications like Twitter, Tumblr, and Posterous (though I think Twitter behavior more often falls into the third tranche).
The third tier I’ve labeled Simple Sharing, and it’s meant to represent the behavior of sharing content without modification or addition. In this category I’d put most Facebook shares, almost all retweets and a good portion of ‘regular’ tweets, and various other sharing actions that don’t add significant value to the content being shared. This is a hugely important tier in the total content volume makeup and it will continue to grow taller over time. But it’s important to realize that this segment and the one below it are complementary – that is, they will help each other continue to realize growth. Much to Rupert Murdoch’s dismay, this growth has negative effects for the Old Media cohort.
My point from all of this is that a few simple rules of media still apply. Where media is being produced and consumed, people will gather. Where people gather, influence can be gained, and wherever influence is being gained, from Jakarta to Brooklyn, advertisers, marketers, and salespeople will arrive in short order.
Let’s return to the graph, shall we?
Google is making loads of cash by advertising against search results and established media outlets that have audiences large enough to drive high CPMs. With enough eyeballs, any destination media outlet can drive revenues with advertising, and Google is quite happy to be the conduit through which that revenue travels.
Twitter (and to some extent Facebook, though it’s a different beast) is leveraging the top of the curve to harvest data that it believes is valuable. This is the real-time search, trending topics bet that’s gaining a lot of steam lately. Time will tell if these wagers will pay, but at the moment there are a lot of very smart people who seem to think they will.
Then there’s the middle. No gargantuan captive audiences, no oodles of instantaneous reaction, but lots and lots of high-quality media being produced. The supply is so large as to drive the market price of this content to zero, and the breadth of suppliers and their lack of retention mitigates the effectiveness of broadcast marketing. In other words, individual entities find themselves in a conundrum: they’re not quite unique enough to generate subscription revenue, not quite big enough to live on advertising. But the content is there, and the composite audience is there. In the aggregate, this market may well be the biggest of all.
In my next post, I’ll elaborate on this concept and make an argument for the type of entity that’s necessary to take advantage of this opportunity and help create a new media ecosystem that’s distributed, egalitarian, and economically revolutionary.
*Data supports an argument that the volume of content is increasing at a significantly greater rate than its velocity, but for the purpose of this post, I’ll assume the rates of change are about the same. I’m more concerned with the composition of the total content volume, whatever its relative scale.
and I am a one of the Co-founders here at Pinyadda. I will be blogging frequently about a number of topics including news about Pinyadda’s progress, our company culture, the social media industry, and a series of posts focusing on social network analysis (SNA).