Title :
Monitoring and analyzing customer feedback through social media platforms for identifying and remedying customer problems
Author :
Bhatia, Sumit ; Jingxuan Li ; Wei Peng ; Tong Sun
Author_Institution :
Xerox Res. Centre, Webster, NY, USA
Abstract :
The tremendous growth and popularity of social media platforms like Twitter, Facebook, etc. provides business organizations an opportunity to monitor the feedback from its customers, identify their problems and take corrective measures. In this paper, we describe a system to automatically monitor and analyze customer feedback through various social media platforms like Facebook, Twitter, etc. and detect issues faced by the customers. Business organizations can use this system to engage with their customers and help alleviate the problems faced by them. The system uses statistical event detection techniques for identifying various customer issues. The system offers a batch version as well as real time version of event detection algorithm depending upon the client´s requirements. We also describe a few case studies illustrating the utility of our proposed system for business organizations in identifying issues faced by their customers through social media channels.
Keywords :
customer satisfaction; marketing data processing; social networking (online); statistical analysis; Facebook; Twitter; business organization; customer feedback; customer problem; social media platform; statistical event detection technique; Companies; Event detection; Media; Monitoring; Real-time systems; Twitter;
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
Conference_Location :
Niagara Falls, ON