Browse by author
Lookup NU author(s): Dr Eric See-To,
Professor Savvas Papagiannidis
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
The potential of big data analytics when it comes to gaining business insights, such as market trends and consumer preferences, has captured the interest of both scholars and business practitioners. However, the extant literature has so far provided limited empirical evidence to demonstrate how big data analytics can create business value. To address this research gap, this paper followed a novel big data analytical approach that involved analysing email archives about product/services demand clusters in a B2B setting. We analysed 621k emails exchanged between 2009 and 2018. We identified a number of discussion clusters that were considered proxies for the interest buyers expressed in the products/services on offer. These clusters and associated discussion trends were linked to the company’s revenues and financial performance, showing good predictive power. In doing this, we have demonstrated how widely available data, such as emails, which all companies have, can be used to underpin new methods for the early identification and monitoring of product demand trends, informing marketing strategies.
Author(s): Yang Y, See-To E, Papagiannidis S
Publication type: Article
Publication status: Published
Journal: Industrial Marketing Management
Print publication date: 01/04/2020
Online publication date: 01/02/2019
Acceptance date: 25/01/2019
Date deposited: 25/01/2019
ISSN (print): 0019-8501
Altmetrics provided by Altmetric