PERSONA DEVELOPMENT FOR E-WALLET USERS IN INDONESIA USING CLUSTER ANALYSIS

• Main Author: Iffah Rizki, May
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/65617
• Institution: Institut Teknologi Bandung

Since 2016, e-wallet usage has been one of the cashless technologies for payment purposes that increased significantly in Indonesia. Most possibly due to the COVID19 pandemic, e-wallet adoption has been boosted to promote contactless payment for the sake of health protocols. E-wallet also play the role of financial inclusion in Indonesia which 90% financial inclusion is part of the government plan in 2024. As one of technology innovations, e-wallet are still relatively new and yet known how far it has actually been beneficial to its users. A user centered design approach called Persona is able to capture the target market of e-wallet in a simple and easy to understand form. Personas can capture the behavior, attitudes, goals, motivations, needs, frustrations, and characteristics of real e-wallet users. Understanding e-wallet personas gives stakeholders a deeper understanding of market needs and can further improve their current products. Hopefully, a better understanding of user needs can lead to higher adoption rates. Due to the urgent need to hire e-wallet users in Indonesia, not only fintech companies can collect e-wallet persona information, but also governments, scholars, and other related stakeholders who are directly involved in the user adoption growth. This research may also be beneficial to other countries seeking to increase acceptance of digital payments to improve citizens' financial inclusion. This study uses cluster analysis as a research framework. This methodology began by analyzing the dimensions needed to run a cluster using the Persona Toolkit, developed by George Olsen in 2004. After acquiring the dimensions on which the questions were based, this study conducted an online survey of 512 respondents, mainly in Greater Jakarta and Java, Indonesia. The survey was conducted for about 10 days from February to March 2022. This study then used the SPSS Statistics tool to perform data analysis and run a respondent results dataset. After iterating the cluster analysis several times, nine personas were obtained.