Following on from that last post another quote that caught my attention last week was 10 words that summed up the economics of Free: “If you’re not paying, then you’re the product being sold“.
This of course is the economics of free media. The economics of free social media takes this idea a step further: “If you are not paying then your relationships are the product being sold”. This of course is the business of mapping and commoditizing the Social Graph and it forms much of the informed debate that is now being conducted over the relative merits of sorting and categorizing your world by Circles, Lists and Groups.
The next level of discussion above this is of course the idea that this rich personal data can then be traded in real-time ,just like shares on the stock market, to potential advertisers eager to reach the an audience of one matching the right customer profile.
Once this happens we achieve a kind of direct marketing nirvana and the biggest social network (be it Facebook, Google +, Twitter or some other next-gen entrant) wins the future of advertising.
Nice in theory but what happens if the growth in social networking isn’t a crowdsourced mapping the complexity social graph but merely gathering yet more data on how the web influences behaviour through the creation of massive feedback loops on a global scale? What if, as Neil Strauss has suggested, rather than sharing what makes us different we are busy sharing what makes us exactly the same? What if rather than creating a unique digital mirror of ourselves we are merely creating a digital mirror of our social selves (i.e. our commonwealth of interest).
What if the social graphs that are being mined are fundamentally worthless simply because in reality the only reason I am here sharing this with you this simply because everybody else is here doing this? More importantly the reason I have 20,000 friends is because the game being played across these networks is about accumulating influence and social presence (or at least being able to demonstrate the illusion of influence and social presence) and therefore the friends I have gathered are little more than an expression of my ability to create a personal feedback loop?
You see if all we doing is playing a global game of creating personal feedback loops then all of the social network theory goes out the window. Deep and meaningful So.Me ideas and though leadership like “To spread your brand on Facebook. Don’t target your fans– Target their friends“, “Seven Indicators of Twitter Influence“, “The state of influencer theory on the social web“, ”Topical storms brewing around influence“ and ”how to activate your brand’s super influencers ” may have a place within the context of network theory but are they still relevent within the context of discussing the nature and economics of igniting, fueling and managing the ubiquitous perpetual motion machines that are these global social feedback engines?
And what does it say about the future of the current crop of So.Me meta data start-ups like Klout and PeopleBrowsr? At the moment the focus is on monitoring and measuring. (e.g. You can’t keep your secrets from twitter) What happens when the focus is on manipulating and influencing? Today on Wall St “In high-frequency trading (HFT), programmers eke out every last incremental tick in performance to build algorithms that battle other algorithms for computational supremacy and millions in profits — and earn a lot in the process.” What happens when the same effort is put into creating algorithms that battle for social influence?
As I have said before within the context of a network the idea of monitoring, measuring, managing and manipulating relationships looks complex and time-consuming. However within the context of a feedback loop managing this “problem” appears to be as easy as turning the “knob” on the feedback controller… so long as you have access to the social feedback amplifier.
This then I suspect is the real So.Me challenge (much the same as it was with the original online media challenge). It isn’t about building the next global social network. The real challenge is to build an intelligent network (e.g. A network of human representative Bots of say 20,000 nodes that perform a function similar to that of Max Headroom) that allows you to monitor, measure, manage and manipulate the social feedback loop across all the established networks in real-time. Once you have achieved this you can just lease time on the “network” to advertisers and marketers seeking to reshape their “influence”.
That’s why I suspect the future of social media advertising will be about sitting in studios monitoring and mixing social influence by manipulating the global social feedback loop in much the same way we mixed in sound and visual effects when doing the post production for a TVCs. Understand this and you will see how easy it will be for very clever people to turn today’s So.Me pennies into tomorrow’s Feed.Me Dollars without having to put ads on the menu.
Postscript:
Not surprisingly it didn’t take long to find a Google quote that mirrored the idea of “If you’re not paying, then you’re the product being sold”.
“We are not Google’s customers: we are its product. We—our fancies, fetishes, predilections, and preferences—are what Google sells to advertisers.” – Siva Vaidhyanathan quoted by James Gelick in the New York Review of Books.
In the end Google didn’t so much invent the Web 1.0 Feedback Loop but certainly became the first to monetize it by tapping directly into the original source that fueled the growth of the web (i.e. PageRank = A hyperlink count = The basic metric of the creation+curation (i.e. the linkback)=creation feedback loop). Google was the first harvest the “wisdom of the crowd” embedded in the commons. Since then the rest of the market has been left with the challenge of manufacturing their own proprietary Feedback Loops (Think: Twitter with its Followers and Tweets and Facebook with its Fans and Likes). That’s why the Google Economy (i.e SEO, AdWords, AdSense etc) is easily the single biggest Feedback Loop on the web today.
Note: Feedback loops are synonymous with mathematical concepts like Fibonacci Numbers (i.e. Add the last two numbers to get the next number) and so I thought it may be worth looking at the growth in the social networks to see if there is a year on year pattern. Over the past 3 years Facebook, LinkedIn have both grown faster than the year on year Fibonacci projection by an additional year. We see a similar result if we take a look at the growth in internet subscribers for the period 1995-2010. The Fibonacci projection based on the 1995 estimates suggests the estimates for the 2010 level of subscribers would have been achieved in 2012. If we take a look at the growth in web sites then we discover the Fibonacci projection for the period 1995-2010 suggests there should have only be just over 9 Million web sites in the world in 2010. There was an estimated 234 Million. A number projected for 2018. Meanwhile if we look at Twitter’s growth over the past 3 years we discover no year on year or month by month correlation. Any correlation that does exist for Twitter requires manipulation of the time scale (i.e. A logarithmic transition from days, weeks, months to years as the network grows) to achieve a closer match in the Twitter growth pattern.
Posted on July 31, 2011
0