Using Social Network Analysis in Marketing

Customers usually get confused buying an item online. Therefore, they consult with their friends, use their past experience, and survey reviews from other customers. Some of the main findings from a survey conducted by eMarketer, in which each participant could choose multiple answers are as follows: a friend’s recommendation (76%), previous experiences you had with this company (68%), a recommendation in a newspaper/magazine (22%), advertisements (15%), and the company’s website (8%) [1].
The survey indicates that a significant proportion of customers trust their “friendship” network before deciding on a particular purchase. This communication between friends is mostly done via some form of social networks.
Thus, analyzing social networks to discover and utilize useful “patterns” from the data can yield effective marketing tactics which can save companies millions of dollars for marketing.
This project first recognizes relevant social networks within the potential customer base, and then it detects tightly bound cohesive subgraphs representing local “friendship” of “important” actors. Finally, we need to identify important community members using “ranking,” where the highly ranked individuals are likely the first to make purchasing decisions.

Faculty Supervisor:

Shahadat Hossain

Student:

Partner:

North Forge

Discipline:

Computer science

Sector:

Education; Management of companies and enterprises; Professional, scientific and technical services

University:

University of Lethbridge

Program: