Background:A US based telecom client that provides wireless service to customers wants to address customer concerns expressed in social media platforms like Facebook, Twitter, Blogs, Company Forums. This client uses Attensity 360 & Radian6 as the listening platforms to capture data posted on various social media platforms. The objective of this project was to accurately classify customer posts into sentiments- Positive Feedback, Negative Feedback (Actionable & Non Actionable)

Approach: AA series of simulation based key word/words algorithm was built in a statistical software. The accuracy of the algorithm was tested on the manual classification of the posts.

Impact: This project helped the client to accurately identify both direct & indirect mentions. The client is on able to reach out to customers with concerns more effectively than before. This helped increase customer loyalty, resulting in the increase of CSAT scores.