They are in fact flip sides of the same coin – the ever democratisation of media. Both speaks of media, that can be produced by everyone, and is distributed by everyone. These two terms can however also capture a distinction in approach to democratised media. How so?

Let me explain. Please note that for the sake of clarity, I am going to generalise. The distinction between different forms of media has never been absolutely clear cut. (Some forms of social media are over a century old.) And the distinctions are even less so now. But here goes my little polemic.

But they differ in important respects:

How to make sense of all this?

Here at RAAK we like to think before we do. If you are a regular reader of our newsletter you’d have noticed that we are rather skeptical of some of the central tenets of the social media dogma. Like the ridiculous one that was so big until quite recently amongst the likes of gurus like Chris Brogan: Following somebody back when they follow you as a matter of course.

Don’t get me wrong. We do think its pretty obvious that the continuous drop in the cost of publishing – the democratisation of media, is revolutionary. But we don’t think that the basic rules of media or how people behave have changed. It’s just that the rules now apply to everybody – because we all can be media.

That means, for example, that attention remains finite. And it is silly to pretend you can meaningfully follow 20,000 people. That means Stephen Frye might be a person, but he is also a broadcaster.

So what does all this mean for organisations in practise?

In most instances, what companies and organisations should do when using media for getting their message out (note – a very specific part of marketing), is ‘content’ and not ‘social’. It fits their goals much better. Most companies want to achieve some kind of scale – an audience and not a community.

You often hear social media consultants say to companies, just join this or that service – it’s not rocket science. Yeah, that might be fine for Joe Blogs who has 130 friends and no need to communicate at scale.

Companies and organisations tend to want to excel and stand out. Create a brand. The only way to do this (besides the obvious one of having a great product) is to produce quality content that’s remarkable. And that is freaking hard. It requires a combination of talent and graft. You often need to throw money at the problem – At companies like RAAK They need to hire journalists, creative programmers, film makers – not marketeers or community managers.

Unfortunately doing things at scale cause more noise (See Gina’s post above). Many blogs have started to switch off their comnents. (I’m not necessarily suggesting you do that). But look at hyper successful Burberry and what they do on their Facebook page. They never reply to customers. They are broadcasting.

Click to enlarge – the most important digital skills 2012 – Econsultancy.

To reiterate – I am not saying that relationships and two way interaction with your audience is of no import when getting your message out. It has always been. Just look at how much radio has made use of the phone-ins over the years. And now this interaction is even easier.

So depending of the company, the brand they are trying to project (aloof, part of the crowd), and their size, the answer to how one-to-one a company should be, will vary.

And social media still has a direct roll in other sphere’s of the company operations. For market research social media is gold dust. It has a massive roll to play in informing product development. Creating forums where customers can help themselves is yet another example where social is king.

It’s earned media, that’s earned through blood sweat and tears

AND it’s hard to do content marketing itself well, without listening what’s going on at the coal face of social media – because that’s where it will be distributed. AND even when creating content, you can harness the power of the crowd. (See our logo and logo crowd sourcing experiment). So this is not an argument against social media per se. But it is an argument for a shift in emphasis to take it far more seriously. A few Tweets, and a few replies won’t cut it.

Bottom-line: There are many more media channels today (we all are), and they vary tremendously in size. And so the scope of these media channels for behaving as broadcasters (Stephen Frye) or conversationalists (The Hackney Gazette) vary greatly too.

But really, if your serious about communicating far and wide, you know which one you want to be.

We’ve created a graph that plots Twitter’s exact number of registered users over time, dynamically. In other words, you can follow it as it happens.

How did we arrive at this graph?

Each tweet on Twitter has a rather big collection of user data embedded in it. From your bio, to your profile background and much more. Which is why Tweets are so much bigger in data terms, than SMS. But for our purposes two of these data fields are of particular interest: the time a user has joined Twitter, and a numerical user identifier.

We noticed that the user id’s always increased when time increased, and wanted to check if they are assigned one after the other, in a linear way. This means the total amount of users at the time when a user joins Twitter, is a function of the user id the user gets assigned. In other words, in its simplest form, the first user got id 1, the second user id 2, and so forth.

We captured hundreds of thousands of Tweets as they flew by in real time. And with the Tweets we got users’ information, and plotted the user ids on one axis and the time the user joined on the other. We then compared these with a few “known points” – points where Twitter actually released their stats.

Not only did this cross-check across all the known points, it also yielded the coefficient we had to multiply the user id with to get the total amount of subscribed users at that point (this happened to be one, by the way – in other words, the user id numbers are dished out in straight forward sequence).

Al that remained was to make the graph dynamic (it collects more data as we speak, so will always stay updated), and write a function that continuously weed out the extra data we don’t need (to stop the graph from becoming slower and slower over time).

Solution: Discount products by getting customers to Tweet them, with the size of the discount dependent on the customers’ Klout scores.

I have made my favourite Miista shoes 3% cheaper by sending this tweet! miista.com/shop/batilda-t… twitter.com/loriannl/statu…

— Loriann Luckings (@loriannl) January 13, 2012

Klout is one of many services that purport to measure influence online. It’s hardly flawless, but it’s a far better and more sophisticated measure than simply counting Twitter followers, which can be gamed very easily.

Importantly we wanted to avoid the elitist way many Klout campaigns have been implemented, where only users with high scores get access to perks. Miista’s brand values is very much at odds with treating their customers differently depending on status. We wanted to turn Klout into a good for everybody. So the behaviour we designed for was to get users with higher influence to Tweet, as they could make the price drop faster for everybody.

We came up with an exponential discount drop, to reflect Klout’s exponential nature. It is much easier to move from 10 to 40 on Klout, than from 50 to 60 for example. And from there on upwards, it only gets harder.

So how did it go?

We got our exponential graph wrong at first. On the Tuesday when we launched we learned a few valuable lessons … like, how quickly people would catch on to it. Even though Miista is a small independent brand, this really took off faster than we had thought it would.

Many mid sized fashion bloggers with Klout scores of 40 to 50 had a big impact. And since customers were only limited to one Tweet per product, they quickly teamed up and moved from product to product to create sizable price drops.

So we did two things:

• We adapted the discount algorithm on day two, as per this chart. It does not look like a huge change, but it moved the percentage drops further down the line. There are not that many people with Klout scores above 55 and people that typically have these scores have much larger audiences.
• We limited users to one Tweet overall. This had exactly the desired effect. Twitter users started asking their followers to help them, thereby bringing new customers to Miista.

please tweet and make these @miistashoes shoes cheaper for me! wanna see how far they can go down! miista.com/shop/dina-blac…

— Kristabel P. (@fashionknitsta) January 6, 2012

Some stats so far.

Clever marketing in #socialmedia: in return for tweeting about the brand, you can get discounts from Miista shoes benlik.es/ztdQHD

— Ben Wagenaar (@BenWagenaar) January 9, 2012

We could easily count the potential reach of all the people who Tweeted and produce stratospheric numbers. But what really matters is who visited the Miista site. Miista has increased its unique users per day more than ten fold since the campaign, with 62% of the visitors never having visited the site before. Average time on the site has gone from over 3 minutes to over 8 minutes. Pages per visit is up from 2.5 to 5.2.

They have received coverage in the UK’s two premier digital marketing blogs, The Wall and The Drum. And many more in Fashion blogs. Many top fashion bloggers Tweeted the campaign, including 5 Inch and Up, Suzie Bubble, Cocorosa, What Katie Wore, Garbage Dress, Song of Style, Studded Hearts, Late Afternoon, Lulu and Your Mom, and Kingdom of Style. Drapers – the leading UK industry magazine in the fashion industry is doing a story. And we even had a Tweet from a celebrity, Paloma Faith.

Bribing customers to be brand advocates

This Tweet, by Facebook’s PR Burson-Marsteller was one of the funnier ones about the campaign. That’s one way of putting it:

Check out shoe brand Miista miista.com Good example of using #Twitter to bribe customers to be ambassadors for your product

— be more… (@bemorecomms) January 6, 2012

Full disclosure. Miista was founded by my partner Laura Villasesnin.

To test this, I set up an experiment, which involves four Twitter bots that automatically tweet the output of the Unix fortune command-line application.

Fortune randomly outputs mildly humorous quotes, and was often used on Unix to produce a ‘welcome message of the day’ upon login.

The four bots Tweet once every minute, once every five minutes, once every fifteen minutes and once every thirty minutes respectively. They are completely anonymous, have no avatars or custom user profiles set, and do not follow anyone.

Now, after 80 days of running the experiment (Jules Verne style), there’s a set of pretty hot data available.

The Data (the good)

Let’s start off by simply plotting the amount of followers for each bot against time:

(Click to enlarge)

We can clearly see from this graph (quite surprisingly), that each bot accumulated followers linearly. Also, it seems the more they tweeted, the steeper the follower accumulation rate is, without any drop off, even for the bot that tweets every minute.

This brings us to a question: Can these graphs in some way be normalized? Surely the bot that Tweets at the annoying rate of once every minute, should get fewer followers per tweet as the one that Tweets at a more acceptable once every 30 minutes?

Let’s normalize the data by plotting the amount of followers against the amount of Tweets, thereby literally measuring the amount of followers per Tweet:

(Click to enlarge)

The scale is a bit awkward, but it seems that these bots are all more or less following the same slope, in other words, by the time the once every 30 minutes bot has tweeted as much as the once a minute bot, it will have the same amount of followers.

Let’s test this assumption, by plotting the curves over time again, including an amplification factor equal to the amount of minutes that lapse between Tweets. That means, we assume the once every 5 minutes bot would have had 5 times more followers if it Tweeted once every minute, etc:

(Click to enlarge)

Transient fluctuations aside, These curves really do seem to follow roughly the same path – linearly upwards.

That means, the more you Tweet, the more followers you get. Period. It doesn’t matter how often you tweet, you gain an equal amount of followers for every time you Tweet.

The Followers (the bad)

Now, on that bombshell … time for a sobering revelation:

Looking at the followers of these bots, many of them seem to be bots themselves (there are quite a few real people who attempt conversations with them, but they are in the minority). Most of these bots get triggered by keywords present in our bots’ Tweets, and then follow and retweet our bots’ Tweets. A good example is @BurroughsBot, which retweets Tweets that match the search term William Burroughs.

At this point I turned to Klout (which, incidentally, is the actual reason for setting up this experiment in the first place). Surely Klout should be able to make sense of this robotic mess (like Google does with link farms), shouldn’t it?

The Klout Scores (the ugly)

For all practical purposes though, no matter how I look at it, Klout seems to be broken.

Consider the following Klout scores, for the four bots:

Klout score for 'once a minute' bot

Klout Score for 'once every 5 minutes' bot

Klout Score for 'once every 15 minutes' bot

Klout Score for 'once every 30 minutes' bot

What’s wrong with this picture? To start off with, it should not really be possible for a bot to reach a Klout Score of 50 within 80 days merely by Tweeting random (yet entertaining) rubbish every minute, should it?

24 hours after the above klout scores were sampled, I took another set of samples, just to be sure:

Klout Score for 'once every minute' bot

Klout Score for 'once every 5 minutes' bot

Klout Score for 'once every 15 minutes' bot

Klout Score for 'once every 30 minutes' bot

Roughly the same result, except for huge fluctuations in transient metrics (see True Reach for Bot 1), which also seems a bit suspect. We can’t say for sure without knowledge of Klout’s exact algorithm.

The fact is, though, no matter how you look at it, unless Klout updates this aspect of their algorithm, in another 80 days Bot 1 could very well have the same Klout Score as @scobleizer!

Taking into account that many Twitter clients (like Hootsuite) and filter applications (like Datasift) are using Klout as a trusted way of filtering tweets, it means Klout will have to up their game on this one to stay in the game.

Or else, we might just be run by machines sooner than we think!

Update – 2010/12/: The Peerindex results are written up. Do check them out here.

If you find this post interesting, you might find our weekly Newsletter, The RAAKonteur, even more interesting. Sign up in the sidebar, top right.

It was BBH Labs’ logo project back in April 2009, where they got 1,700 logo submissions and chose one, that got us fired up about including the public in the creative process. Since then we’ve learnt a thing or two from using the crowdSpring platform and did our very own logo experiment, where we got ordinary people to design us an R, an A or a K without them knowing what it was for  (using Amazon’s Mechanical Turk platform).

Now we’re taking it a step further: a never-ending RAAK logo project that integrates individual letter submissions into a perpetually changing logo made by (hopefully)  hundreds of people.

A company for everybody – A funny take on corporate logo design

We were inspired by designer Phil Seddon’s enthusiastic feedback on our initial branding experiment. So this time, we are setting restrictions as to what people can do. After many discussions about grid patterns and freestyle, Phil has created a framework for design that we think will integrate submissions in our new website look and feel.

Still, if an identity is about making a fancy logo, then we’ll probably fail. But if branding is about

• 1. making you stand out
• 2. making people remember you
• 3. communicating the core values of the business

then we’re doing quite ok.

We want our brand to reflect what we’re about:

open, social, digital, participatory, creative and constantly changing.

So this branding exercise is as much about the process of open collaboration as about the result.

And all the designs will sit in our Logo Archive, with links to the URL of choice of their creators.

You can find more practical info about how it all works and submit your design on the Logo Project page.

PS: We reserve the right to delete really egregious designs.

Media invaders - EdgeRank vs PageRank

Until recently Google was the lone collosus bestriding the web world. Knowlege of how its system of ranking web pages in search results works (called PageRank) was a key bit of knowledge webmasters, SEO experts, marketing professionals needed.

But there’s a new upstart in town. With time spent on Facebook far exceeding that spent on Google, with traffic driven by Facebook matching and in some cases outstripping Google, the spotlight has turned onto Facebook and in particular it’s News Feed.

Jeff Jarvis calls the Newsfeed Facebook’s secret sauce. It’s the news according to your crowd. But what he failed to mention is not all members of your crowd’s News feed are treated equally. This blog post elaborates on how the feeds work:

To explain further, every Facebook profile has a live feed and a news feed. The feed is a stream of content and Facebook status updates coming from your friends, groups, causes and the pages you Like (also ads you have Liked – so-called social adds – end up in the feed). For every unique profile (or Facebook account) there is a unique feed. Your feed is different then mine because we each follow and friend different people/organizations. The live feed is a real-time stream of posts that populate as they occur.

The news feed is a little bit more complicated. Facebook determines what should go in your news feed based on your previous behaviors, and not everything makes the cut.

It’s important to understand that there is a view on the News Feed that allows you to see your friends’, Groups’, Likes’ updates – Twitter like – in real-time.

But the vast majority of users view their feed through the Top News feed (that’s the default setting).

Facebook EdgeRank Top News

And this is where EdgeRank comes in. EdgeRank is an algorithm like PageRank – it ranks content. You don’t get to see all status updates unless EdgeRank deems it important enough.

Some estimates have it that only 0.5% of status updates make it to Top News. In other words – if you have 200 Facebook fans or friends, and you publish a status update, on average only 1 of those 200 will see it!

Specialer than you

That is if EdgeRank does not deem you special.

You will notice that there are some persons or brands in your feed that show up regularly. And some people who you never see. Why? How does this work?

Lets have a closer look at EdgeRank – the arbiter of what you get to see.

The Edgerank algorithm

Affinity score
What is the relationship between the Edge Creator (The content creator) and the viewing user. Yeah, if you have not friended each other, or Liked you won’t even figure in feeds. But the more Friends or Followers have liked posts, commented on them, the more likely your Affinity Score will go up. What is not clear is if the number of mutual relationships play into these scores at all. At this stage it seems it does not.

Weight score
This is attached to the particular content you shared. The more Likes, the more Comments, the higher the weight of that content. It would seem – anecdotally that mutual relationships do play a role in pushing this score higher.

Time or Recency score
Content looses its mojo quickly. It’s seldom that you will see content in a Newsfeed that’s over 48 hours old. It’s very different from Google’s PageRank if you think about it. With PageRank content can accrue value over time.

Now this has a number of implications.

Things for you to consider:

• Affinity scores are the scores that really matter;
• New Facebook accounts will have a much harder time to get noticed since they have low Affinity scores;
• Google’s PageRank has an inherit bias towards good content, and to an extent this is true for EdgeRank. Although celebrity and relationships do muddy the waters, making it possible for inane content to figure more prominently if the affinity score is high enough.
• The so-called long tail does not apply in Facebook land in the same as it applies to search. Content falls from grace and out of mind quickly.
• Google’s PageRank encourages the creation of good content. The user behaviour of promiscuous people flitting between websites that have the best stuff, ignoring the brand of sites has become common. Facebook’s affinity score however encourages a return brand building.

Strategies for getting seen:

• Write compelling status updates – yes content is King;
• Diversify the types of content you share – Some of your followers of Friends might not be interested in what you have to say. You can get around that by posting content on divergent topics. If they interact with this, your overall score will go up, and all your content will be visible more prominently to them.
• Now and again, ask friends to Like or Comment on a particular bit of content;
• Use video as often as possible – Video is easy to dip into and engaging, and video makes great little thumbnails in the news feed – making your stuff stand out;
• Bear in mind when most people access Facebook and when most people are likely to see your content. It might be that posting late at night might be better as there are few bits of competing content, although you might have a

Hit the Like Button - Watch the future

Earlier this year during the World Cup Nike scored big.

Their ad “Write the Future” was all over television. But before it blanketed traditional media, Nike launched the video on Facebook. Reports Business Week:

The video started as an ad on the site. Then it was passed from friend to friend, often with comments and members recommending it. In the resulting discussions, the clip was played and commented on more than 9 million times by Facebook users—and helped Nike double its number of Facebook fans from 1.6 million to 3.1 million over a single weekend. Getting the ad onto Facebook cost a few million dollars, according to the companies. All that passing around was free. Davide Grasso, Nike’s chief marketing officer, says Facebook “is the equivalent for us to what TV was for marketers back in the 1960s. It’s an integral part of what we do now.”

The success of Google’s Adwords is legendary. But almost all of that success is a form of direct response. Brand advertising – the kind of advertising that commands the biggest share of the market by a country mile – has not taken off online at all. And it’s not as if companies like Google have not tried to make it work.

Sheryl Sandberg left Google for Facebook, for exactly this reason. She believed Facebook to be much better placed to address the $600 billion gorilla that is brand advertising.

Facebook has been making brand advertising look easy. Just recently Techcrunch reported that Yahoo! paid $1 per Like on the platform. Says Techcrunch:

Facebook Ads employ demographic characteristics (Age/ Sex / Location and Interests), which corporate brand managers and television ad buyers have been accustomed to purchasing for half a century. By contrast, Google AdWords target on the intent revealed by search queries, a practice that has seemed odd and new to Madison Avenue for the past decade and frankly has many of them worried for their jobs.

But before you train your budget on Facebook, a few things to note. Yes, Facebook has solved the internet advertising problem you’ve been moaning about: you can now reach almost everybody with one single ad spend.

But also consider the following. Facebook is a social space and it’s important that you don’t only understand it in terms of paid media. To maximize your spend you absolutely have to understand the importance of earned media.

If you are from an ad buying background, you might not even be familiar with the term. Earned media is a term originally coined in the world of public relations. It basically refers to those stories and mentions of a brand in the media that spread because they were considered news-worthy and were not paid for.

It is a term that has found new currency in social media. It’s become apparent that the former audience love sharing their opinions on almost everything – including products and brands – with their own small and sometimes not so small audiences.

In an excellent report Nielsen Research says explicitly:

“It’s critical that we understand advertising not just in terms of paid media, but also in terms of how earned media and social advocacy contribute to (paid for) campaigns.”

When buying Facebook ads there are in fact three types of ads you might be generating, whether you want to or not.

Facebook ads - social ads, organic impressions

But why are the last two types of impressions important? Consider the evidence.

Nielsen compared the responses of users who had seen ads with social context against users who saw ads with no social context from the same campaign, they saw a measurable lift in… well, lift.

Ads with a social context - recall, awareness, purchase intent

In fact it had better awareness, recall and purchase intent.

This was even more pronounced when a person saw both the normal impression and an organic impression.

Organic impressions - recall, awareness, purchase intent

Says Nielsen:

Those users exposed to both the “paid ad” and the organic impression remembered the ad at three times the rate of those just exposed to the paid homepage ad. We saw a similar effect for the other two metrics evaluated. Homepage ads increased awareness of the product or brand by 4% on average, but exposure to both homepage ads and organic ads increased awareness by a delta of 13% versus the control group. Exposure to organic impressions also impacted purchase intent as well, increasing the impact of the ad from 2% to 8%.

A fourfold increase in purchase intent. Very impressive indeed. But I hear you ask, what percentage of impressions have a social context, and what percentage would be organic? And, how do you plan for that?

The first answer is that it’s often small.

The second answer is that brands with large groups of Fans or Likes on Facebook has appreciably better chances – in a quite predictable way – of either. Have a look below.

Facebook Likes - Fan bases are key

And while it’s hard to scale organic impressions, ads with social advocacy can show the kind of reach associated with normal impressions.

A key take-away here is that the brand ads need to take a leaf from the earned media book. It needs to be very creative to be compelling. In old PR parlance: it has to have an angle, a story that will carry it. Nielsen agrees:

To maximize the reach of earned media, advertisers must start with interesting and engaging paid homepage impressions. Because the organic impressions are generated through interactions with the ad unit (which are then posted as stories in friends’ feeds), there is a strong relationship between the engagement rate of an ad campaign and the number of organic impressions.

Woosh, oh cool! You’ve unlocked the Goodie Green badge. As you turn to leave for work you can’t but help yourself; you suppress your smile. Sarah is now only one level higher. And besides – she has no points in ‘Neighbourhood Watch’. And in that group you accumulate badges much faster.

A screenshot of the causeworld app

In policy wonk theory talk abounds of libetarian paternalism – two concepts long thought to be at loggerheads. But it simply comes down to this. How a caring but non-pushy state can help irrational citizens make better decisions. It’s called nudging.

But how can the state help its citizens become more engaged? And can we use social media to achieve this?

When Foursquare wanted to get people to check into venues they correctly anticipated that their new network would need to incentivise its users. It was not like your friends – one major incentive to use these applications – were on Foursquare. But with rewards and badges, age old techniques from the world of gaming they managed to get people checking-in.

Tom Chatfield, author of Fun Inc and deputy editor of Prospect magazine, recently spoke at a TED event about the lessons from games. That is to say, the techniques used by games to increase engagement.

We evolved over hundreds of thousands of years to be satisfied by the world in particular ways; and to be intensely satisfied as a species by learning and problem-solving. Perhaps the most amazing thing about the virtual arenas that games create is that we are now able to reverse-engineer that, and to produce environments that exist expressly to tick our evolutionary boxes and to engage us.

Tom talks of having features in games like having an experience system, having multiple long and short term aims, rewarding for effort and giving rapid, clear and frequent feedback.

He explains how uncertainty could help.

“This is the real neurological gold mine so far as gaming is concerned. Dopamine elevates when you get a little prize for doing something, but what really lights up the brain is the unexpected reward: the one that couldn’t be predicted. And so the right amount of well-calibrated uncertainty can create intense engagement in all manner of tasks.”

He says these windows of enhanced attention can be a good time to teach a player something, or to impart information.

But what he finds most thrilling is the potential for collective engagement. That people don’t only do things for rewards but that they do it because there are other people around them.

Clay Shirky in his recent book Cognitive Surplus dwells very much on this same theme. He points out that groups of people can produce civic goods in their free time, and this is because of a number of innate human traits. Two of them are personal. The need for feeling autonomous and competent. Two of them are intensely social. The need to belong and to share.

But a simplified belief that people are good won’t do. Shirky points at mistakes made by eBay, before they had their reputation system in place: Some users cheated. And in another example he tells how two female artists, dressed as brides hitch-hiked across Europe and the Middle East. They came to grief. He contrasts this to the positive experience of thousands on Couchsurfing.org, including single female travellers. Here the system was designed to encourage (or ‘nudge’) for good behaviour.

There have been attempts at getting citizens more engaged.

Tim Berners-Lee last year helped get government departments to open up their data, in much the same way as the Obama administration has tried to do. The result is Data.gov, a repository for all kinds of government data, ready to be used by creative programmers for the good of society.

Says Tom Chatfield:

Politically, the idea is far from libertarian. There is still a vital role for the state in collecting, publishing and paying for data, and also in getting the best out of developers. But a world where mashers inherit the earth is also an oddly appropriate example of Cameron’s “big society.” For once, this is an area where those irritating buzzwords—“the wisdom of crowds,” “the long tail,” “nudge,” and the rest­—actually work, and where the ideas they enshrine mean citizens taking decisions for themselves rather than relying on the state.

But mash-ups are all good and well. They rarely encourage collective civic action like tools such as Ushahidi – the crisis information crowd sourcing tool.

Cameron is on record saying ‘the success of the Big Society will depend on the daily decisions of millions of people’. True. But perhaps there is a role for government in providing the platforms and systems that allow people to be their best.

Defra is under pressure. The scheme that pays farmers for protecting wildlife is also set to be cut. Can they be incentived through a digital system to continue doing this voluntarily? Arts funding is reported to be one of those areas that will be cut in the coming spending review. Is there a place for government in launching a social funding tool like Kickstarter?

Yet there are still many that are oblivious as to how Google’s Pagerank works. In this video I explain how PageRank works.

Google themselves defines their ranking system, called PageRank like this:

‘PageRank relies on the uniquely democratic nature of the web by using its vast link structure as an indicator of an individual page’s value. In essence, Google interprets a link from page A to page B as a vote, by page A, for page B. But, Google looks at more than the sheer volume of votes, or links a page receives; it also analyzes the page that casts the vote. Votes cast by pages that are themselves “important” weigh more heavily and help to make other pages “important”.’

Note Google does not talk about domain rank. It largely ignores domains – like wewillraakyou.com – but looks at the value of individual pages like wewillraakyou.com/hoes-does-google-page-rank-work/

Every page has a value merely for existing on the world wide web. When a page links to this page it transfers Pagerank to it. If a page has two links it splits the value it can transfer between these two links.

Google's PageRank formula - makes the web a meritocracy

In other words, links are like votes. But not all voters are equal. Voters that have received many links themselves can transfer more voting power.

Therefor the BBC site, which has a lot of amazing content and to which many people link, has pages with tremendous PageRank. If one of these pages link to your webpage, you are guaranteed to get a major Pagerank boost.

This system has meant that web search acts largely in a meritocratic fashion. If somebody does something remarkable, it tends to rise to the top.

It also means that if you have a mediocre website, content, service or product you will have to spend top dollar to get eyeballs. In other words, just as with social sharing the rule applies for search: advertising is a tax on an unremarkable product.

Ever since Unilever’s crowdsourced Peperami campaign, debates have raged (Brand Republic) about the future of crowdsourcing and its potential to encroach on the domain of agencies. On the other side of the pond, people like Bud Cadell have even wondered if the future needs an agency at all (Whatconsumesme).

Guided Collective is a hybrid between a traditional agency and a crowdsourcing platform. It is driven by a collective of top freelance creatives from all kinds of disciplines that use an online collaboration platform to pitch and collaborate on creative briefs.

The platform is invite-only, so we can't show what really is under the hood of Guided. But included in this post are some screengrabs that we made with dummy briefs & content

One of the main arguments for opening up the creative team is the range of skills now required when seeking to speak to consumers. Edward Boches, Chief Creative Officer and Chief Social Media Officer of US agency Mullen recently blogged (EdwardBoches.com):

“You can make ads with a writer and art director. But if you want to
conceive and execute platforms, utility and experiences, you need IA, UX, technology, connection planning and social media working together. This is a significant change for many agencies but one that is absolutely essential. It may come with pain and resistance but what choice to you really have? The post digital days are upon us.”

But crowdsourcing as the panacea is not without its detractors. It is argued that it does not take into account important agency functions, like account management, coordination (in particular with large transmedia campaigns) and long term strategic planning.

A second criticism is that it exploits creatives in a competitive free-for-all environment, where their chances of winning work are slim and the remuneration is paltry.

The Guided platform tries to address exactly these two issues. The platform itself is invite-only and restricted in size. It aims to have the UK’s best creative talent, across a number of disciplines. From copywriters and bloggers, to iPhone developers, social media strategists and directors.

Guided comes with an in-house account management team. Clients are familiar with that kind of dedicated attention and service.

And importantly creatives can earn money three different ways:

1. One is by coming up with a winning concept.
2. Secondly – and this is unique – part of the budget is ring-fenced for collaborating on a winning concept; to make it even better or by giving input that makes the idea go transmedia.
3. Lastly, creatives can win all or part of the actual production of a concept.

Sam Reid, founder of Guided studied research on crowdsourcing when planning the collective:

“When it comes to solving specialist problems, research shows that numbers are not necessarily the solution. They are great for simple yes/no stimuli but become quickly overwhelming for complex tasks. For this it’s better to have a range of different skills within a smaller network.

We have a heterogeneous but small crowd. This is a doubly good, because besides having cross-discipline inputs, creatives who are part of this crowd won’t feel like a number. And happy creatives means good work.”

So what did RAAK do? We helped Sam conceptualise the Guided way of working as well as the Guided platform. RAAK then went and built it.

The platform consists of two types of functionality. One set of functionality is community orientated, including what must be the sexiest ‘activity feed’ and member profile pages in any social network. But what really makes this platform significant and unique are the collaboration features.

Guided has bespoke functionality geared to make creatives happy, which is too often neglected. When we conducted focus groups, it was clear there was a concern amongst creatives that their peers could steal their ideas. So we included functionality to allow them to make their ideas visible only to members in other specialities than their own. So a director’s idea won’t be seen by other directors, if they so wish, but everybody else will.

Is the Guided platform perfect?

No. But it’s a very good first take on how we might source creative work to engage with customers on behalf of brands in the future. And we’ll be improving it constantly as we go along and discover more about collective and social creativity.

More about how Guided works in this lovely animation.