The “Social Media Marketing Paradox” explained with chaos theory, neurochemistry and jellyfish

This agency earned its money... er...

This agency earned its money… er…

A moment of clarity is a rare thing in the world of social networks. We can’t really describe their purpose, exactly, but we use them all the time. We get value from them but it’s hard to measure, hard to predict and for social media marketing teams around the world, hard to get the results they want when they try to get them… but surprisingly easy to get a result when they’re not expecting it.

In the midst of everyone (well, about 25% of them) in the world using social networks in some way, the commericial elephant in the room is the same as it was a decade ago when Facebook launched “How do we use this for business?” There isn’t an answer yet, either. Conventional wisdom has been to see social media as a new raft of channels for PR, advertising and marketing. In fact almost the whole agenda of Social Media Week London is devoted to it. But it’s not working. Yet another epic social media fail by brand X? Really, after so long? Did that happen with Billboards? Magazines? Radio? TVs? Cinemas? Websites? A decade after they came along? No.

Social media loves that sort of branded public screw up, but have you ever considered this:

The reason we love epic social media fails is the reason they keep happening. It’s why brands keep paying for them and agencies keep dishing them up… even though they don’t know they’re doing it at the time.

For business, this inherent unpredictability in public media channels has never existed before and many companies aren’t geared up to think about the problem appropriately because the reasons behind it aren’t commercial problems to solve, they’re behavioural. Not the type of economic behaviours businesses expect, or social behaviours that advertisers and marketers understand. They’re distributed social computing behaviours, something more complex than supply and demand or lifestyle and shopping. Which makes social media a business thinking problem. And ManVsBrain loves a thinking problem…

 

Don’t shoot the messenger

2012 is a very significant date for businesses. It’s the first year since 2005 where the global music industry recorded a profit as opposed to a loss. In the same time period, music piracy halved. Profits are rising, piracy is falling. The reasons for it are obvious. The old music industry resisted digital demand for music downloads and streaming media. They wanted us to buy CDs. The demand ruptured their supply side economics through peer-to-peer file sharing (piracy). Once the major labels started offering digital downloads and started working with new streaming media services, many pirates went back to buying music. At the time, the music industry (and the Federation Against Copyright Theft, FACT) spent a lot of time telling us that people were all basically thieves.

They weren’t. They just wanted to consume music differently. But the idea that out there, in the world of social networks, there’s a society that’s hostile to the interests of business persists. Is it possible we are somehow subverting traditional business models ourselves? Yes, obviously. Every time an ad campaign goes wrong or a PR disaster occurs, it’s because of the unruly behaviour of the public. Hijacking McDonalds, Xfactor or Nestle (et al) with some sort of “rabble rousing” as Simon Cowell said about the campaign to get Rage Against The Machine’s “killing in the name” (a.k.a “fuck you I won’t do what you tell me”) to number 1 in the UK chart back in 2009.

But the explanation for this phenomenon isn’t just the commercial equivalent of civil disobedience, it is rooted in chaos theory and human evolution. It’s the paradox of social media, and it’s actually predictable when you realise there is a categorical difference between one person with a computer and a network full of them. It’s also a good example of deterministic chaos theory, summed up by mathematician Edward Lorenz as “Chaos: When the present determines the future, but the approximate present does not approximately determine the future.”

 

The predictable order in the social chaos

Most people’s timelines are a bit like channel surfing your old TV at 1 a.m. when you stagger in from the pub. You might catch an old movie where a young Lee Majors kidnaps a nun (Weekend of Terror, 1970), an informercial for a steam cleaner that you secretly want to buy (even though you know one day it will give you severe burns and melt your bathroom floor) or a documentary series about crab fishermen that makes you feel seasick as you pass out on the sofa.

Like our late night telly flicking, our social media feeds aren’t themed around a topic or a genre, it feels random.

This creates a complex issue for people who want to use social media for advertising, marketing or PR. In the past, those disciplines knew how to get a result from ordered, strategic approaches to achieve their targets. But those rules don’t apply in the chaos of social media, in fact, as the hashtag jacking of #AppleLive by other brands and the trolling of recent Twitter promos by Puma has proven, there’s nothing logical about thinking logically when it comes social media. The digital world has a tendency to mess with your plans.

The reason so many brands keep getting it wrong is misunderstanding the appearance of social media’s ‘anything goes’ model. Brands assume they can insert their content into the mix and it will, like all the random crap, blend in. But it doesn’t work like that. This is because social media isn’t really random at all. There’s order in that chaos.

It’s the expression of functional computing necessities in the networked age. To remain useful, social networks have to become less predictable and more chaotic. It’s a very strange idea, but unarguable. To explain, consider this:

When we knew precisely what computing was for, and how to extract value from computers, we didn’t need them or use them nearly as much as we do now.
 

Social media is functional, purposeful data processing… in disguise.

One of the systemic computing problems of the digital world is the overabundance of data. It’s a phenomenon that comes from “information parity”, which is the idea that we’re experiencing a shift from the pre-digital world (where information was expensive to create and distribute) to a world where creating and distributing information is a basic function of everyday life. This has subverted the power of traditional pillars of the social and economic order.

In the pre-digital world, data flowed from relatively few sources of information authority (governments, publishers, academics, news organisations and corporations) down to the masses (us). Today, in the social network era it’s a new world where there is more information generated by and between the masses, making control of that information by traditional sources of authority almost impossible.

It sounds complex, but actually it’s simple: there was a time when a politicians could flash his penis at a female constituent and we’d only know about it if it made the front page of the newspaper. If a brand gave one of its customers terrible service or made a duff product, it was between the customer and the company, the rest of the world didn’t know about it. This was the time before user reviews. Before the days where everyone went everywhere with a camera that could post pictures into the world, capturing everything with eyewitness news speed. A world where in-depth explanations of complex technical terms were kept in classrooms and textbooks, not open to all via wikipedia and so on.

Now it’s different. News, information and opinion flows endlessly around the world, and there’s not much governments or corporations can do to control it, try as they might. All the stuff that you don’t want out there… it’s already out there and more is on the way. That’s information parity at work.

This shift into information parity has created a unique problem. There is so much information out there that computers can’t organise it very effectively, which is a problem because the ability to organise large quantities of information is partly what computers were designed to do. The problem for managing information on the internet isn’t being solved by search methodology, the proverbial magic tool to find a needle in a haystack, because there’s so much information out there that we need tools that tell the difference between one needle and another in a haystack sized pile of needles.

Which is why social media is so compelling. Social networks are search engines for things we don’t know we’re looking for… and would be hard to find, even if we did. You might ask why you would look for something you don’t know you’re looking for, but it’s essentially the same motivation for flicking through TV channels or browsing in a shop, it’s a foraging behaviour. Our genetic makeup favours that kind of unknowing search. In fact, social media itself pushes a lot of our genetic problem solving buttons.
 

It’s partly genetically programmed problem solving…

We all share a desire to communicate information about ourselves and others (humans communicate more than any other species and uniquely the majority of that communication is about other humans) and when we communicate, our brains give us a hit of dopamine, the brain’s natural reward system. It’s an evolutionary imperative. The more we communicate, the better our chances of survival as a species.

Most creatures communicate the basics like “I see danger” or “I’m hungry” but we talk so much we inevitably find ourselves working out complex problems as a byproduct of conversations that all start with mundane “hey, how’s it going” chit chat. It’s how we went from being isolated troupes of bipedal apes to astronauts in only 2 million years or so. Jellyfish, on the other hand, have been around 500 million years but still have nothing to talk about.

This inbuilt problem solving function of human communication is truly remarkable. It also highlights something unique about human language itself, which is the only recursive language, i.e. the process of speaking actually helps you work out what you wanted to say before you started speaking (and also while you’re speaking). Which of course is something we all do, you know, when you’re having a conversation and you start using all manner of pre-conditioned phrases like “at the end of the day” or “yeah, but the thing you need to remember is…” before you’ve actually formed the crux of your argument into words in your head. Nothing else does this, not writing, not physical contact, not computer code, not cooking… all of those sorts of process require the idea to be formed before you begin, but with language it’s uniquely different. It’s a problem solving mechanism, a thinking process and a communication tool all at the same time.

Our neurochemical dependence on dopamine through sharing information is also the reason why we create so much information and plaster it all over the internet. Despite most of it being irrelevant, en masse it’s so useful that the thought of living or working without access some kind of internet based technology seems almost impossible to those of us fortunate to be living in the developed world.

In fact, it is a measure of poverty and inequality on a global scale to define how many people live without internet access. It’s currently around 60% of the world… which equates to roughly the number of people who are deemed to live below the $2.50 per day poverty line (just under 50%). Our way of life is defined by it.
 

Social networks are a computational necessity…

We now produce so much information in the public space that indexing and searching through all the data in the world is impractical. However, if you can see what other people are clicking on, sooner or later they’ll find you something of use just by virtue of the fact they’re looking for things that interest themselves. That’s because the people you connect with in social media are much like yourself, no matter how different they appear to be. They, like you, are filtering out the useful stuff from the crap and listing it on social networks for other people to find. If you’re good at it, people will follow you. If you’re not, we share such a compelling need to filter out all the shit, some people will follow you anyway just in case you might find something they can’t find for themselves.

Network analysis experiments to track the flow of information in social networks have shown that the people you know best are the worst for finding you things you won’t naturally find for yourself, because you have a lot more in common with their tastes and interests (which is how come you’re motivated to get to know them). People you know less well are much better at finding things you’re unlikely to happen upon organically yourself, because they have more varied tastes and interests.

Which means we all create networks of people we know well (called strong ties) and people we don’t know at all (weak ties). We’re most likely exchange messages with our strong ties and there are usually far fewer of them. The weak ties represent the outer limits of our networks, and we usually have more of them (people we don’t have regular conversations with but follow in some way). As in real life, we have more acquaintances and colleagues than we do close friends.

We use these networks of brains to filter out the things we want to see from the vast ocean of things to see out there in cyberspace. It’s called network intelligence, the propensity for groups of socially connected people to intelligently filter out consistent quality content from the mass of data online. Humans are good at this because we intuitively understand things like irony, humour, spam and so on in a way computers can’t, at least, not yet. So where search engine algorithms can be gamed by SEO techniques, humans can’t to the same extent, so the spam is less likely to diminish the quality of the content our human networks discover when compared to search engines.

Which brings us back to chaos theory because, although social network systems are deterministic, meaning they’re designed with a purpose in mind (connecting people together and sharing information) this doesn’t predict a strange mathematical twist that makes our social networks inherently unpredictable. Because there are a lot more people who fall into the category of being weak ties than strong ties, when you aggregate together all the things you read and click on in social networks, it turns out for many of us, people we hardly know (because they’re more numerous) are more influential over our consumption of data than the people we know well, who often find the same things we can find for ourselves without them.

This is, of course, how Google works. It’s the behaviour of millions of unknown people that guides the Google algorithm to serve up the results it calculates are probably the ones we’re looking for. The difference is depending on what you ask Google, you’ll get a different answer. In social network intelligence, we don’t ask any questions, we get the answers before we know what to ask.

 

The paradox of social computing revealed

Social computing is an expression of our collective social intelligence. The will of the crowd. The paradox this creates is simple: If you want to use social networks to influence individual behaviour, you have to influence group behaviour first, which means influencing individuals in order to influence the group. To make this even more self-referencing, the things you do to influence individuals to support your plans will also influence other individuals to oppose them. Which means, predicting the results of something that seems like a good idea at the time, is at best, guesswork.

The secret of getting it right is to be continuously present in the group and adapt your plans as you go along, which of course, means what you started out to achieve might not be what you end up choosing to do.

In the social network world, a bus full of teenagers using Whatsapp is more socially intelligent than a boffin with workstation. It’s a functional intelligence, a practical application of human needs and and instincts to solve a deeply complex abstract maths problem, filtering out different varieties of data into contextual categories of meaning, without even realising we’re doing it. It’s part evolutionary behaviour, part computing necessity. It requires a different approach to insert your business into that complex mix of unconscious motivations.

It’s counter-intuitive, but it’s the only explanation for why social networking has been so persistent and pervasive. We need it because without it computing would become too complex to remain useful to the vast number of casual users. Without social networks, computers would go back to being things we use for specific purposes rather than general purposes. This social, general purpose computing is a fundamental force of our social and economic development, if it wasn’t social networks would have been a fad, or perhaps, a hobby… like home computers used to be back in the 1980s.

You can’t apply the same business wisdom of the old world to this new one, especially when it comes to marketing and advertising. Our casual reliance on general purpose computing power has spawned a new kind of market that is both resistant to traditional business processes and compliant in seemingly random quantities. Every agency and business in the world claims to know this, they’ve all got strategies and plans to deliver social media wins but you can’t help thinking they don’t really, they’re just trying to make their old business rules fit into a new game.

Spend a while surfing the web for creative agencies and you’ll notice they’re all “innovators” new, and different. They claim uniqueness, en masse, which means (logically speaking) they can’t be. They all claim to produce their own unique recipe for success, but they always seem to churn out the same kind of thing. An advert is an advert, after all.

But more importantly, they’re still agencies (like in the last century) which means their clients ares still brands (also like in the last century). The social and economic relationships they represent would be recognisable to their forbears from the Mad Men days of the 1950s, but imagine trying to explain something like Facebook to someone back then. Or a smartphone.

“Hey 1950s marketing director, I’ve got a telephone smaller than a packet of cigarettes that can put you face to face with someone on the other side of the world, or share pictures of your holiday snaps taken underwater whilst actually underwater when you post them.. into a whole bunch of computers without any idea where they are or what they’re even called.”

They’d think you were crazy.

“Hey 1950’s marketing director, I work for an ad agency”.

They wouldn’t bat an eyelid. It can’t be purely coincidental that businesses are trying to do the same things they used to do before social networking and were very effective once, but can’t get it consistently right in the current networked world. Their model needs to change because we’ve changed, not just in how we relate to computers and the media, but in how we relate to the world around us through computing and creating our own content.

It’s a daunting challenge for the next generation of sales and marketing, product development and advertising industry leaders. They’re not just faced with finding a new way to connect with consumers, they’re faced with questioning their purpose. After all, if they can’t reliably create new products, help people market their products or boost sales through advertising, what are they getting paid for?

That’s the thing about chaos. It’s got a certain order to it. And in the age of information parity, the order is dominated by more questions than answers. That’s why nobody is surprised when we read about another epic social media fail by a brand with deep pockets and a top flight agency, except, of course, the brand and agency who got it so wrong by trying logically to get it right. How did they get it wrong? Surely they must have known? Why didn’t the same thing happen to a very similar campaign for a similar company? And so on.

There is a logical solution to the problem, however. Stop trying to get it right. Stop talking about campaigns, branding, sales and marketing. Stop trying to do business in the social network, and do something else instead. But if you can’t work out what that something else should be, keep getting it wrong because everyone loves it when you screw up.

In fact, if you want to get noticed like you used to, measure your success in terms of eyeballs and column inches… well… screwing up is working out fine. Ironically though, the chaos means if you deliberately try to screw it up, you’ll probably go unnoticed.