Creation of unstructured big data from customer service: The case of parcel shipping companies on Twitter

Abstract

Purpose

Customer service provision is a growing phenomenon on social media and parcel shipping companies have been among the most prominent adopters. This has coincided with greater interest in the development of analysis techniques for unstructured big data from social media platforms, such as the micro-blogging platform, Twitter. Given the growing use of dedicated customer service accounts on Twitter, the purpose of this paper is to investigate the effectiveness with which parcel shipping companies use the platform.

Design/methodology/approach

This paper demonstrates the use of a combination of tools for retrieving, processing and analysing large volumes of customer service-related conversations generated between parcel shipping companies and their customers in Australia, UK and the USA. Extant studies using data from Twitter tend to focus on the contributions of individual entities and are unable to capture the insights provided by a holistic examination of the interactions.

Findings

This study identifies the key issues that trigger customer contact with parcel shipping companies on Twitter. It identifies similarities and differences in the approaches that these companies bring to customer engagement and identifies the opportunities for using the medium more effectively.

Originality/value

The development of consumer-centric supply chains and relevant theories require researchers and practitioners to have the ability to include insights from growing quantities of unstructured data gathered from consumer engagement. This study makes a methodological contribution by demonstrating the use of a set of tools to gather insight from a large volume of conversations on a social media platform.

Citation

Bhattacharjya, J., Ellison, A.B., Pang, V. and Gezdur, A. (2018), "Creation of unstructured big data from customer service: The case of parcel shipping companies on Twitter", The International Journal of Logistics Management, Vol. 29 No. 2, pp. 723-738. https://doi.org/10.1108/IJLM-06-2017-0157