Is the content armageddon nearly upon us?

Nate Silver, author of The Signal And The Noise, has a nice line about the connection between big data and truth - namely, that as the amount of information/content/opinion rises exponentially, the amount of objective truth remains constant.

In a similar vein, the amount of content being shared on social networks is rising hugely - the challenge for both individuals and organisations is to work out coping strategies to try and sift out the signal from the noise. And if the signal remains fairly constant, how do we navigate through the ever rising volume of content noise? The problem is that some of the solutions offered may actually help to exacerbate the problem.

I should stress I’m by no means the first to highlight this issue - Mark Schaefer wrote a widely read and commented on piece back in January (Content Shock: Why content marketing is not a sustainable strategy).

But ironically, as more data becomes available to allow us to understand the true scale of the issue (such as real Twitter impression data), the challenge of getting any kind of decent return on content curation and creation gets harder.

As per my earlier post, the emerging picture of both Facebook and Twitter is of two platforms that are suffering from the same issue - ever increasing content, but a constant number of hours and minutes in which to view, read, react and share that content.

In both cases, organic reach (as a percentage of the overall potential audience) is being reduced - the number of people who even have a chance of seeing your content seems to be declining rather than rising.

The conclusion some are drawing from this is to simply post more content more often - either by curating other people’s stuff or creating your own. Both have implications for budget and resources. The curation route may seem attractive e.g. your key challenge is identifying the right kind of content to share - but even with value added curation (such as adding comment and context) you are still ultimately driving your audience to other people’s content. At some point you need to create your own content and probably curate other’s too.

From the content consumption perspective, one coping strategy is to simply increase the amount of time consuming content. As per today’s Ofcom report, that certainly appears to be the trend in the UK - for example, the average UK adult now spends more time using media or communications (8 hours 41 minutes) than they do sleeping (8 hours 21 minutes – the UK average).Indeed, 16-24 year olds spend the most time on media and communications, cramming over 14 hours of media and communications activity into 9 hours 8 minutes each day by multi-tasking, using different media and devices at the same time. However, there is clearly a finite limit to how much content consumption you can cram into a day.

Part of the challenge for brands and organisations seeking to reach any audience is that for all of the data and tools available to us to determine what people may or may not like or respond to, we are basing this on past performance. In reality you have no 100 percent guarantee in advance what will or won’t work. Of course, you could say that some outcomes are more likely than others - but who is prepared to go to the trouble of working out all the possible outcomes and assigning a probability to them? Then again, perhaps Monte Carlo simulations are the way forward...

So where does this leave us?

I have no doubt some people will try to put forward the business case for increased investment in content creation - that the only solution to the content visibility problem is more content, posted more frequently - but if everyone does this, are we entering a never ending content arms race where we all ultimately drown in a surfeit of stuff? Will our audiences become numbed by the sheer weight and volume of content available? Will any of us actually get any real work done?

Ultimately, we have no choice but to rely upon the past as a guide to the future - imperfect as that might be. We will almost certainly have to get better at creating valid tests and experiments to understand which approaches have a higher probability of working than not. And we will probably have to convince ever sceptical senior management that it is worthwhile investing in an ongoing experimental mindset - that we don’t have a magic crystal ball with which to second guess the future. But that a more rigorous and scientific approach should at least reduce the probability of less successful outcomes.