When most people hear “Social Network Analysis (SNA)” today, they usually think about Facebook or Xing. However, Social Network Analysis is actually an empirical method that has been well-established even before the age of personal computers.
Rooted in Sociology, SNA is intended to help companies better understand human social interactions and relations to help them improve their marketing methods. It “is the mapping and measuring of relationships and flows between people, groups, organisations, computers, URLs, and other connected information/knowledge entities.”
Each network is represented by a set of nodes (e.g. people) and their connections (e.g. communication between two people). Typically, quantifying those connections required difficult field work and involved asking questions such as “Who do you ask for help?”, “Do these people ask you for help in return?”, and “With whom do you communicate on a regular basis and how often?”.
The collected data had to be digitized before the actual analytics was conducted, which is an inefficient use of resources and time.
But this has changed since the Web now provides a lot of input data in digital form. User interactions on Web 2.0 platforms, such as blogging or commenting and befriending someone on Facebook, provide a continuous stream of real-time customer generated intelligence and opinion.
While SNA has been around for a while, it has only recently entered the business context. SNA can help companies better understand their customers and their interactions by making who communicates with whom, how ideas are spreading within the customer base and who the opinion leaders are more apparent.
This can efficiently help companies reduce churn rates, reach the right customers with targeted advertising campaigns or boost viral marketing campaigns through leveraging the influence of opinion leaders.
An example of how SNA can help to reduce churn rates is analysing the social network of mobile phone users. By statistically evaluating call detail records (CDRs), SNA identifies the people with the highest influence in the customer network.
These customers could be given a positive incentive in the form of special benefits, such as free text messages or additional talk minutes, in order to increase their loyalty to the company. The idea is that these influential customers will promote this loyalty to other potential customers. On the other end, companies can save money by not spending any effort on customers that are likely to churn, bring low revenue, or become isolated from other users of the network.
With the growing presence of ubiquitous user-generated content, it will be interesting to see how SNA will compete with traditional pen- and paper- based marketing methods. Real time is the factor that differentiates SNA from those older models.
By analysing communication flows and changing customer relationships on social media platforms, companies will definitely be able to extract relevant and timely information to stay ahead of the competition.