Abstract

Fulfilling customer satisfaction gives significant impact to any business including in the electricity industry. The key to achieving customer satisfaction is by providing them the best quality services at fair and reasonable costs. Customer complaints must be managed professionally and appropriately, and be leveraged to improve the quality of services and operational efficiency. In this regard, identifying the root cause of the problems becomes paramount in improving customer service for future improvement. The accumulated customer complaints generate massive data which can be fully utilised by using big data analytics. The purpose of this paper is to determine frequent customer complaint regarding electricity issue and review various methods of big data analytics that have been used to identify valuable insights within the data and to analyse the pattern that can be useful to find solutions to the problem, thus improving the electricity industry services especially in terms of complaint management. On the basis of a study of the different researches, different techniques of machine learning have been used because of its accuracy and in finding a pattern to solve the relevant electrical problem such as predicting power demand, managing power loads, and enhancing strategic planning.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.