Abstract:
This paper describes the research and development of a methodology for
optimising the customer support in contact centres (CC) using a soft computing
approach. The methodology provides the categorisation of customer and customer
service advisor (CSA) within CC. Within the current contact centre environment
there is a problem of high staff turnover and lack of trained staff at the right
place for the right kind of customer. Business needs to assign any available
advisor to a customer and provide consistent and good quality of service. There
is a need to identify the right amount of information to be displayed on the
screen considering both the customer and the assigned advisor background. On the
basis of data collected through case studies carried out within five customer
contact centres, two step clustering analysis was used to derive the categories
for customers and advisors based on demographic, experience, business value and
behavioural attributes. We provide the methodology to develop a fuzzy expert
system which assigns a new customer or advisor to the pre-defined categories.
The authors have explained the steps which were followed for the development of
the fuzzy expert system. A prototype system has been designed and developed to
identify the type of customer and CSA based on the demographic, experience and
behavioural attributes. The authors illustrate analysis with real data, based on
the work with large scale customer contact centres. The CSA’s can play different
roles and have different level of autonomy, but at the end they are humans with
heart and voice. While product purchases, lifestyle information and billing data
provide important information about customers, it is call detail records that
describe a customer’s behavior and define their satisfaction with the services
offered. Call detail records describe the transactions between customer and the
company. This study describes the research and development of methodology for
categorizing customer and customer service advisor within contact centre
environment. On the basis of the categories derived for customer and service
advisor; the minimum amount of information required by the CSA to serve the
customer is analysed and discussed within the paper. The information requirement
framework provides the amount of information which is required by the CSA on the
basis of {customer, advisor} relationship. A promising area for future work is
that of data mining the records within contact centres. The methodology for
proposed fuzzy expert system and its application to CC setting should be of
interest to many industry sectors including telecommunications and contact
centre environme