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With competition intensifying across service-oriented business, customer satisfaction is the name of the game. If customers did not perceive the orgnisation well, the company will definitely run out of business. This paper analysed the data collected from customer service unit of a particular bank using Jupyter note - a framework under Python programming language to know customers need and to improve customer satisfaction. From the analysis, it was discovered that there were six (6) purposes of customers’ visitation to the banking hall i.e six services were rendered by the customer service unit of the bank, they are: account authentication; account list; authenticate user; balance check; fund transfer and register customer. All services except Balance Check and Fund Transfer are at their peak in the morning by 8am. Also, user authentication has highest queue length of 450 customers in the morning (8:00am). It was also discovered that customers call for services in the early part of the day and keeps decreasing until the break period when customers will be able to visit bank to make their transactions. Among all the services rendered by the bank, account authentication has the highest average queue length, followed by fund transfer, customers registration, user authentication, balance check and account listing with values 141.000, 131.600, 104.100, 103.500, 96.625 and 51.500 respectively for the month of April. This study was able to learn how customers really feel about the services rendered by the bank and the bank also has been able to know the level of the customers satisfaction, how to improve on the services render and where the immediate focus need to be in order to accelerate the bank growth because satisfied customers will buy more, stay longer and share their positive experience.

Evaluation of Customer Service Delivery in Banking Operation Using Python