Constructing New Statistical Approaches with CRM to Determining Membership Value to Customers: Evidence from CBA Data

The legal profession, like many professions within the global economy, is undergoing significant change with advances in innovation and technologies and as geo-political and economic shifts are underway. As the only association representing the legal profession across the country, but also active in the global economy through various initiatives including international projects supported by partners such as the UN among others, the ability for the CBA to provide a path for the future of the legal profession is paramount for its membership and its role in supporting the justice system and the rule of law.
The availability of “Big Data” enables the use of sophisticated statistical methods – such as machine learning and text mining – that will help the CBA in better understanding the needs of its membership and how such tools can help delivering unique insights in an ever-evolving digital landscape.

Faculty Supervisor:

Anindya Sen

Student:

Rishav Raj Agarwal

Partner:

Canadian Bar Association

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Waterloo