Network Analysis and social CRM

Course title
Network Analysis and social CRM
Course tag
Course status
Independent work
Teachers and associates
Assistant Professor PhD Robert Kopal
Josip Kunsabo, Instructor
Tamara Nemeth, Instructor
The course aims
The aim of the course is to familiarize students with the legality of network analysis and analysis of social networks with the application of the CRM system, focusing on social CRM. Linking the social network analysis method to social CRM significantly increases the usability of our own resources in communication and improving relationships with both existing and potential customers. The premises of the subject are to demonstrate to students the usefulness of products obtained through the methods of network analysis applied on data collected by social CRM at all levels within a business entity including marketing, finance, development, research.
Introduction to Network Analysis. Introduction to CRM. Planning and implementation of CRM system. Social CRM. Social CRM and Map of Connections. Analysis of social networks. Group analysis in the network. Diffusion analysis in the network. Dynamic network analysis. Functionality of software for social network analysis. Practical examples of analysis of social networks in business areas. Application of social network analysis in various areas of economy.
R.A. Hanneman, M. Riddle: Introduction to Social Network Methods
Supplementary literature

Minimum learning outcomes

  1. Select the level of network analysis.
  2. Present what analysis of social networks is and what are its goals.
  3. Recommend basic network measures and basic centralization measures.
  4. Arguing an opinion on CRM's basic ideas
  5. Recommend precautionary measures and groupings in the network
  6. Review the difference between traditional CRM and social CRM
  7. Rank the basic functionality of social network analysis software.

Preferred learning outcomes

  1. Review the basic goals of network analysis and the principles of networking.
  2. Rank according to the complexity of the connection distribution of multiple types of networks that appear in nature.
  3. Select centralization measures in network analysis.
  4. Review the planning and implementation phases of a CRM system in a business entity.
  5. Select the functionalities presented during lectures to analyze a more complex network with a larger number of entities.
  6. Support the collection of data using social network profiles (Facebook, Twitter and LinkedIn). Recommend the functionality of preparation of data collection and analysis functionality.
  7. Choose the specific software functionality used during the lecture.