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Marketing strategies for fintech companies: text data analysis of social media posts

Sungwon Oh (Department of Big Data MBA, Business School Lausanne, Chavannes, Switzerland)
Min Jae Park (Department of e-Business, Ajou University, Suwon, Republic of South Korea)
Tae You Kim (Department of Healthcare and Artificial Intelligence, Catholic University of Korea–Songsin Campus, Seoul, Republic of South Korea)
Jiho Shin (Department of Big Data MBA, Business School Lausanne, Chavannes, Switzerland)

Management Decision

ISSN: 0025-1747

Article publication date: 17 November 2022

Issue publication date: 17 January 2023

1273

Abstract

Purpose

This study aimed to present the methodology of the text data analysis to establish marketing strategies for fintech companies in a practical way. Specifically, the methodology was presented to convert customers' review data, which consisted of the text data (unstructured data), to the numerical data (structured data) by using a text mining algorithm “Global Vectors for Word Representation,” abbreviated as “GloVe”; additionally, the authors presented the methodology to deploy the numerical data for marketing strategies with eliminate-reduce-raise-create (ERRC) value factor analytics.

Design/methodology/approach

First, the authors defined the background, features and contents of fintech services based on a review of related literature review. Additionally, they examined business strategies, the importance of social media for fintech services and fintech technology trends based on the literature review. Next, they analyzed the similarity between fintech-related keywords, which represent the trends in fintech services, and the text data related to fintech corporations and their services posted on Facebook and Twitter, which are two of the most popular social media globally, during the period 2017–2019. The similarity was then quantified and categorized in terms of the representative global fintech companies and the status of each fintech service sector. Furthermore, the similarity was visualized, and value elements were rebuilt using ERRC strategy analytics.

Findings

This study is meaningful in that it quantifies the degree of similarity between customers' responses, experiences and expectations regarding the rapidly growing global fintech firms' services and trends in fintech services.

Originality/value

This study suggests a practical way to apply in business by providing a method for transforming unstructured text data into structured numerical data it is measurable. It is expected that this study can be used as the basis for exploring sustainable development strategies for the fintech industry.

Keywords

Acknowledgements

Funding: This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A5A8065886).

Citation

Oh, S., Park, M.J., Kim, T.Y. and Shin, J. (2023), "Marketing strategies for fintech companies: text data analysis of social media posts", Management Decision, Vol. 61 No. 1, pp. 243-268. https://doi.org/10.1108/MD-09-2021-1183

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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