Intention Analysis for Sales, Marketing and Customer Service
Cohan Sujay Carlos, Madhulika Yalamanchi · International Conference on Computational Linguistics · 2012
In recent years, social media has become a customer touch-point for the business functions of marketing, sales and customer service. We aim to show that intention analysis might be useful to these business functions and that it can be performed effectively on short texts (at the granularity level of a single sentence). We demonstrate a scheme of categorization of intentions that is amenable to automation using simple machine learning techniques that are language-independent. We discuss the grounding that this scheme of categorization has in speech act theory. In the demonstration we go over a number of usage scenarios in an attempt to show that the use of automatic intention detection tools would benefit the business functions of sales, marketing and service. We also show that social media can be used not just to convey pleasure or displeasure (that is, to express sentiment) but also to discuss personal needs and to report problems (to express intentions). We evaluate methods for automatically discovering intentions in text, and establish that it is possible to perform intention analysis on social media with an accuracy of 66.97%±0.10%.