Passalaras, Raja Aulia
Unknown Affiliation

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

Segmentation Strat Egy of Consumer Interest in Contemporary Coffee Shop Using RFM Model Passalaras, Raja Aulia; Daulay, Risma Yanti; Heikal, Jerry
BUDGETING : Journal of Business, Management and Accounting Vol 5 No 2 (2024): BUDGETING : Journal of Business, Management and Accounting
Publisher : Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/budgeting.v5i2.9030

Abstract

Increase customer loyalty by grouping customers into several groups and determining appropriate and effective marketing strategies for each group. Customer segmentation can be done through the clustering method. This research aims to analyze customer Recency, Frequency and Monetary (RFM) from the segmentation results of 5 contemporary coffee shops, namely Janji Jiwa, Kopi Kenangan, Tomoro Coffee, Fore Coffee, and Fami Cafe, from Persona Analysis Research and segmentation of consumer interest in contemporary coffee shops. Previously it could be summarized that cluster 3 or potential customers were the targets of the research by implementing appropriate marketing strategies based on the characteristics and profiles of the respondents. This cluster consists of 31 respondents, most of whom are women aged 24-28 years with a bachelor's degree and work as private employees in Jakarta. Interestingly, cluster 3 is divided between coffee fans and those who don't like coffee. Respondents in this study tended to prefer Tomoro Coffee, while those who didn't like coffee preferred Fami Cafe. In cluster 3, there are 29 people who are active Instagram users. The analysis used includes descriptive analysis where the data used is primary data. The data collection technique used is the observation method and distributing questionnaires to customers who are in cluster 3. The results of the research show that based on the results of the revenue segmentation analysis for the Tomoro Coffee and Fami Cafe coffee shops, it can be concluded that customers in cluster 3 consist of 3 segments. namely recency 3 which consists of 16 active customers who are very loyal and faithful. The strategy to retain these customers is by personalizing customer data to understand product/service shortcomings and knowing customer individual preference needs in order to attract them back. Keywords: Frequency, Monetary, Recency.
Customer Segmentation Using K-Means Clustering with SPSS Program in a Case Study of Consumer Interest in Current Coffee Shop Daulay, Risma Yanti; Passalaras, Raja Aulia; Heikal, Jerry
BUDGETING : Journal of Business, Management and Accounting Vol 5 No 2 (2024): BUDGETING : Journal of Business, Management and Accounting
Publisher : Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/budgeting.v5i2.9288

Abstract

This research aims to segment customers using the K-Means Clustering method in a case study of consumer interest in current coffee shops such as Kopi Kenangan, Kopi Janji Jiwa, Tomoro Coffee, Fore Coffee and Fami Cafe. Customer segmentation is useful for knowing consumer preferences such as interests, background, lifestyle, service quality and consumer characteristics that are useful for knowing the right persona and marketing strategy as well as the value proposition, especially at the Kopi Kenangan, Janji Jiwa, Tomoro Coffee, Fore Coffee and Fami Cafe coffee shops. The analytical method used in this research is data collection by distributing questionnaires to respondents with predetermined criteria in the Jakarta area and outside Jakarta. The questionnaire was distributed in November 2023. The survey results were analyzed using the K-Means Clustering method in the SPSS 23 program to group consumers based on certain attributes such as age, education, domicile, income, occupation, frequently used social media and most popular coffee shop preferences. such as coffee and non-coffee variants, price, service quality and recommending it to other people. Based on the results of K-Means Clustering data processing, there are 3 clusters, namely cluster 1 (Consumptive Customer), cluster 2 (Standard Young Customer), cluster 3 (Potential Customer) which can be concluded that cluster 3 is a potential cluster that is the target of this research, where cluster 3 consists of respondents who are coffee fans and don't like coffee but are very active in using social media and have made online food transactions and always dine in when making transactions at coffee shops. So it can be seen that cluster 3 can be explored and used as a marketing target by carrying out promotions on various social media applications by offering various choices of coffee and non-coffee variants in order to attract customers who don't like coffee so they are interested and want to try the products offered. . The value proposition for current coffee shops is to give the impression of Coffee Vibes and focus on providing a unique and unforgettable coffee experience by presenting innovative flavor variants and creative coffee presentations, exploring new flavors and offering premium quality that can be enjoyed by all groups and creating an atmosphere comfortable and Instagram- worthy to provide a pleasant customer experience that fits the rhythm of modern life. Keywords: Cluster Analysis, Current Coffee, Customer Segmentation, K-Means SPSS,.