Semi-autonomous methodology to validate and update customer needs database through text data analytics |
| |
| Institution: | 1. Department of Engineering Science and Mathematics, Luleå University of Technology, Sweden;2. Hydcon KB, Sweden;1. Department of Industrial Systems and Engineering, Indian Institute of Technology-Kharagpur, Kharagpur, 721302, India;2. Reliability Engineering Centre, Indian Institute of Technology-Kharagpur, Kharagpur 721302, India;1. Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, Largo Lucio Lazzarino, 1, 56122 Pisa, Italy;2. Department of Enterprise Engineering, University of Rome Tor Vergata, Via Orazio Raimondo, 00173, Rome, Italy;1. Programa de Pós-Graduação em Informática, Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos, 274 – Bl. E – CCMN/NCE, 21.941-590, Cidade Universitária, Rio de Janeiro, RJ, Brazil;2. Departamento de Ciência da Computação, Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos, 274 – Bl. E – Room 1038 (NCE), 21.941-916, Cidade Universitária, Rio de Janeiro, RJ, Brazil;1. School of Business and Economics, Loughborough University, United Kingdom;2. The University of the West Indies, Department of Economics, Trinidad and Tobago;3. Aston Business School, Aston University, United Kingdom;4. Kent Business School, University of Kent, United Kingdom;1. Montclair State University, Department of Information Management and Business Analytics, Feliciano School of Business 1 University Ave., Montclair, NJ, 07043, United States;2. Baruch College, Department of Computer Information Systems and Statistics, Zicklin School of Business, 1 Bernard Baruch Way New York, NY, 10010, United States |
| |
| Abstract: | To develop highly competitive products, companies need to understand customer needs (CNs) by effectively gathering and analysing customer data. With the advances in Information Technology, customer data comes not only from surveys and focus groups but also from social media and networking sites. Few studies have focused on developing algorithms that are devised exclusively to help to understand customer needs from big opinion data. Topic mining, aspect-based sentiment analysis and word embedding are some of the techniques adopted to identify CNs from text data. However, most of them do not consider the possibility that part of the customer data analysed is already known by companies. With the aim to continuously enhance company understanding of CNs, this paper presents an autonomous methodology for automatically classifying a set of text data (customer sentences) as referring to known or unknown CN statements by the company. For verification purposes, an example regarding a set of customer answers from an open survey questionnaire regarding the climate system of a car is illustrated. Results indicate that the proposed methodology helps companies to validate and update the customer need database with an average of 90 % precision and 60 % recall. |
| |
| Keywords: | Customer need CN Company knowledge Text data |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
