Monday 31 December 2007
Following on from my previous post 'It's a small world', historically, and even now, service design has been all about understanding the motivations of the individual. Social network analysis on the other hand is based on the view that the attributes of individuals are less important than their relationships and ties with other actors within the network, and it is by exploiting these that you can really begin to focus on who's really important in your user network.
As an enterprise, social or otherwise, our users are most likely to belong to a random/exponential social network, but we want it to be a scale free network with hubs that positively reinforce our service. Now that we’re talking specifically about networks of people, this is where Tipping Point theory comes in. The tipping point is a concept related to collective behaviour and the fact that any behaviour pattern has a threshold at which point there is a sudden, marked and significant change. Tipping points are what makes marketing go viral; turning products into the epidemic type fads that companies dream about.
What’s relevant about Gladwell’s book in terms of networks and business intelligence, however, is that he identifies not only the importance of word of mouth and social interaction in the take-up of ideas, products and services, but also three key types of individual that are needed to achieve this - Connectors, Mavens and Salespersons. I’m not going to go into detail here, but Connectors are people with huge numbers of network links, Mavens are people who research everything before they buy, compare and search out all the best deals, and Salespersons are the persuaders i.e. the ones who find a good or deal and have the drive and power to convince others and sell their ideas.
In the real world, Connectors need charm and personality, but I’d argue that online it is different. Connectedness is much easier and more democratic online as people are already well connected through search engines. The really connected ones then are those who not only share their views, but those whose content or opinion is considered valuable by others and visited frequently, added to favourites and followed through RSS. These then, are our hubs. The ideal version are a personality combination of Maven and Salesperson, and if you are an enterprise, your dream hub is someone is also well connected offline too.
The first step is then to set up mechanisms to identify these ideal hubs. Second is to focus on these individuals and try and get them evangelising about our enterprise. In the bricks and mortar arena there is little hope of exploiting member networks because you have no easy way of getting people talking to each other. The online channel however, presents the perfect opportunity.
The basic framework needed in order to leverage the power of our member/user network is to make sure the website provides easy user friendly opportunities for people to comment, review and interact, possibly with profiles that display their activity along with incentives for them to share information. Basic web analytics software will help, but we're really going to need to invest in or develop network analytics software, involve some intelligent analysts who can both model the audience and help shift it from a random to a scale-free network, and of course use a forward thinking marketing approach to engage and increase the number of ‘hubs’ and really drive word of mouth take up.
As an enterprise, social or otherwise, our users are most likely to belong to a random/exponential social network, but we want it to be a scale free network with hubs that positively reinforce our service. Now that we’re talking specifically about networks of people, this is where Tipping Point theory comes in. The tipping point is a concept related to collective behaviour and the fact that any behaviour pattern has a threshold at which point there is a sudden, marked and significant change. Tipping points are what makes marketing go viral; turning products into the epidemic type fads that companies dream about.
What’s relevant about Gladwell’s book in terms of networks and business intelligence, however, is that he identifies not only the importance of word of mouth and social interaction in the take-up of ideas, products and services, but also three key types of individual that are needed to achieve this - Connectors, Mavens and Salespersons. I’m not going to go into detail here, but Connectors are people with huge numbers of network links, Mavens are people who research everything before they buy, compare and search out all the best deals, and Salespersons are the persuaders i.e. the ones who find a good or deal and have the drive and power to convince others and sell their ideas.
In the real world, Connectors need charm and personality, but I’d argue that online it is different. Connectedness is much easier and more democratic online as people are already well connected through search engines. The really connected ones then are those who not only share their views, but those whose content or opinion is considered valuable by others and visited frequently, added to favourites and followed through RSS. These then, are our hubs. The ideal version are a personality combination of Maven and Salesperson, and if you are an enterprise, your dream hub is someone is also well connected offline too.
The first step is then to set up mechanisms to identify these ideal hubs. Second is to focus on these individuals and try and get them evangelising about our enterprise. In the bricks and mortar arena there is little hope of exploiting member networks because you have no easy way of getting people talking to each other. The online channel however, presents the perfect opportunity.
The basic framework needed in order to leverage the power of our member/user network is to make sure the website provides easy user friendly opportunities for people to comment, review and interact, possibly with profiles that display their activity along with incentives for them to share information. Basic web analytics software will help, but we're really going to need to invest in or develop network analytics software, involve some intelligent analysts who can both model the audience and help shift it from a random to a scale-free network, and of course use a forward thinking marketing approach to engage and increase the number of ‘hubs’ and really drive word of mouth take up.
To start with, here are three books you should read
Why now? Because with the improvements in business intelligence and analytics modelling, we can now really begin to understand and map online networks, and identify the ‘hubs’ or key people that we should be engaging with to turn them into advocates in order to drive take-up through word of mouth. With the ubiquity and popularity of blogs, reviews and the web, this area is turning into an advocacy tool that should be taken extremely seriously. It might also help us figure out how a volunteer network might function and where we need to focus within it.
Complex networks like those involving people, although seemingly random, surprisingly do actually follow patterns that can be mapped, and essentially fall into two categories – small-world networks and scale free networks. If networks were linear i.e. A knows B, and B knows C, and so on... the link between A and Z would involve 26 steps; and any knowledge, opinion or influence Z might have would be pretty much inaccessible to A.
Small world networks however essentially describe a pattern of interconnectedness that involves a degree of randomness, i.e. maybe B also knows M and X, and maybe X knows Z, which dramatically improves the connectedness between A and Z. The originally studies in this area were carried out by Stanley Milgram who was responsible for identifying the phenomenon we now know as “6 degrees of separation”. Yes, it’s not a myth!
However real world natural networks do not work as simplistically as this. They have another property that’s even more crucial, known as preferential attachment. Preferential attachment is an example of a positive feedback cycle where initially random variations are automatically reinforced, thus greatly magnifying differences. In popular speak this is the 'Matthew effect' i.e. the rich get richer!
What this means is that the more connected something is, the more likely it is to gain new connections. In a social network this means that any new unconnected member is more likely to become acquainted with more visible members than with relative unknowns. These ‘visible’ elements are effectively hubs with lots of connections and therefore influence, and these networks show a pattern called the ‘Power law’, which basically means that doubling the number of hubs reduces the degrees of separation between elements in the network by a constant; in this case, our users.
In other words all our potential users are connected to one other, and although we all know this, so far I’ve not heard of anyone that’s really modelling this connectivity for the specific goal of building and improving online networks. Personally I'm fascinated by this area and reckon it’s part of the future of the web, which is why I'm keen to see if there's any way we can build some of this thinking into the way we set projects up.
- Small World - Mark Buchanan
- Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life - Albert-Laszlo Barabasi
- Tipping Point – Malcolm Gladwell
Why now? Because with the improvements in business intelligence and analytics modelling, we can now really begin to understand and map online networks, and identify the ‘hubs’ or key people that we should be engaging with to turn them into advocates in order to drive take-up through word of mouth. With the ubiquity and popularity of blogs, reviews and the web, this area is turning into an advocacy tool that should be taken extremely seriously. It might also help us figure out how a volunteer network might function and where we need to focus within it.
Complex networks like those involving people, although seemingly random, surprisingly do actually follow patterns that can be mapped, and essentially fall into two categories – small-world networks and scale free networks. If networks were linear i.e. A knows B, and B knows C, and so on... the link between A and Z would involve 26 steps; and any knowledge, opinion or influence Z might have would be pretty much inaccessible to A.
Small world networks however essentially describe a pattern of interconnectedness that involves a degree of randomness, i.e. maybe B also knows M and X, and maybe X knows Z, which dramatically improves the connectedness between A and Z. The originally studies in this area were carried out by Stanley Milgram who was responsible for identifying the phenomenon we now know as “6 degrees of separation”. Yes, it’s not a myth!
However real world natural networks do not work as simplistically as this. They have another property that’s even more crucial, known as preferential attachment. Preferential attachment is an example of a positive feedback cycle where initially random variations are automatically reinforced, thus greatly magnifying differences. In popular speak this is the 'Matthew effect' i.e. the rich get richer!
What this means is that the more connected something is, the more likely it is to gain new connections. In a social network this means that any new unconnected member is more likely to become acquainted with more visible members than with relative unknowns. These ‘visible’ elements are effectively hubs with lots of connections and therefore influence, and these networks show a pattern called the ‘Power law’, which basically means that doubling the number of hubs reduces the degrees of separation between elements in the network by a constant; in this case, our users.
In other words all our potential users are connected to one other, and although we all know this, so far I’ve not heard of anyone that’s really modelling this connectivity for the specific goal of building and improving online networks. Personally I'm fascinated by this area and reckon it’s part of the future of the web, which is why I'm keen to see if there's any way we can build some of this thinking into the way we set projects up.
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