Automatically Quantifying Customer Need Tweets: Towards a Supervised Machine Learning Approach

Abstract

The elicitation of customer needs is an important task for businesses in order to design customer-centric products and services. While there are different approaches available, most lack automation, scalability and monitoring capabilities. In this work, we demonstrate the feasibility to automatically identify and quantify customer needs by training and evaluating on previously-labeled Twitter data. To achieve that, we utilize a supervised machine learning approach. Our results show that the classification performances are statistically superior-”but can be further improved in the future.