DATA MANAGEMENT - FREE TEXT MINING. THE CHALLENGE. How does an organisation develop internal and external strategies to
DATA MANAGEMENT - FREE TEXT MINING THE CHALLENGE How does an organisation develop internal and external strategies to improve business performance and increase overall customer satisfaction - especially when it is difficult to measure the underlying issues facing different customer groups in the first place?
ACC’s business service centre logged all customer-related interactions in a system including; inbound, outbound, and internal communications. While comprehensive in the amount of information the system holds, it was essentially a free text record of all activity within the business service centre. Although notes were time stamped and linked to an account number, there was no other classification system for storing basic interaction activity such as whether a call is inbound, outbound or internal.
As part of ACC’s overall strategy of improving customer satisfaction, Datamine was asked to assist in managing the wealth of information available. The main purpose of the project was to identify and understand groups of customers and the issues they face when dealing with the company via the business service centre.
Inbound calls
Internal communications
Outbound calls
Talisman free system text system free text
Customer group profiles
Purpose of call
Improved customer interactions
THE SOLUTION The specific objectives of the project were to determine: •
The purpose of a call to the service centre in relation to an invoice e.g., required more information, clarification, reaction to an invoice itself, or a debt related query
•
Understanding the profiles of different customer groups based on their amount and type of interactions with the business service centre
The objectives of this project were realised by incorporating and time-aligning call centre note data alongside other data sources such as existing customer information and invoicing data.
Analysing the approximately 500,000 free text notes was only made possible by building an extensive data dictionary of words, as well as determining as many traditional and non-traditional abbreviations and permutations of those words as possible. From there the words within notes were looked at in context to each other, enabling Datamine to accurately assign over 90% of the notes to various classification levels such as call type (inbound, outbound, or internal), and even down to the exact reason for the note itself e.g., a debt related query.
THE RESULTS ACC was provided with a comprehensive look at the profiles of various groups of customers, and the reasons for their interaction with the ‘business service centre’ at different levels. The analysis enabled the company to identify and change processes to better meet the needs of their customers - thereby increasing their level of satisfaction. These included simplifying collateral and creating new communications to meet specific needs.
