Abstract
The financial services industry is known to be a competitive one, and literature
suggests that it has an abundance of data, otherwise known as big data (SAS,
2012a). The industry not only makes a large contribution to the national GDP, but
also has the most potential to embrace big data in order to have a competitive
advantage over the various other industries contributing to the national GDP.
However, in South Africa, this industry is currently perceived not to be leveraging its
data optimally, particularly from a marketing perspective, with more than 50% of
marketers stating that using data was last on their list of priorities when making
decisions (Spenner & Bird, 2012). Literature suggests that South African marketers
currently have a very vague formulation of who their customer is. In order for the
financial services industry to gain competitive advantage from a marketing
perspective, it needs to use data to better profile and understand their customer.
This will lead to more personalised relationship with the customer, and will ultimately
cement the relationship between the customer and the institution.
The primary objective of this study is therefore to discern the extent to which data is
used in a financial services institution from a marketing perspective. First, literature is
addressed which introduces an adapted model which was initially developed by
Byrom, Bennison, Hernández and Hooper (2001:336), which is used to guide the
study. The empirical study is qualitative in nature, using a case study approach in
order to meet primary and secondary objectives. A financial services institution was
chosen wherein employees working with big data from a marketing perspective were
identified through snowball sampling. In-depth personal interviews were conducted
with these employees, using a discussion guide which was based on the model
mentioned above.
The Morse and Field approach was used to analyse the data whereby when the
findings indicated that the institution analysed in this study is using various types of
data sources, some more comprehensively than others. The institution identifies the
importance of integrating various data sources, however this is not being done to the
fullest extent. The institution currently uses big data from a market perspective for
better customer profiling. The findings also revealed that the institution was highly
dependent on using big data to make decisions at an operational level.
M.Com. (Marketing Management)