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Vol.12, No.4, November 2023. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Potential Customer Analysis Based on Gender, Age, Retention, Motivation Using K-Means and Octalysis Gamification Approach
Fitri Marisa, Titien Agustina, Devi Rusvitawati, Mardiana Andarwati, Rudi Hariyanto, Endah Tri Esti Handayani, Enes Sukić
© 2023 Fitri Marisa, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 12, Issue 4, Pages 2541-2551, ISSN 2217-8309, DOI: 10.18421/TEM124-66 November 2023.
Received: 30 June 2023. Revised: 26 September 2023.
Abstract:
This study aims to analyze the role of gender, age, retention, and motivation on the high and low opportunities of potential customers using the K-means clustering approach and gamification octalysis. This research resulted in several new knowledge contributions. Female customers are the most potential customers in a retail company. On the other hand, male customers are the least potential customers. The motivation to buy is relatively high across all genders and ages, as evidenced by the average "core drive" score, which tends to be high in the customer cluster segment with various age groups. The amount of customer motivation to buy products does not affect purchase retention, which several factors outside this study can cause. Based on customer expectation and customer impression data, low-price offers and product discount offers are dominantly in demand by customers, and this is also in line with the core drive "development" and "scarcity" scores which tend to be high. The age maturity of customers is directly proportional to purchase retention, and this is entirely rational when considering the buying ability of customers where the more mature age group has a higher purchasing power.
Keywords – Potential customer, small medium enterprise, k-means, octalysis gamification framework. |
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