Segmentation Strat Egy of Consumer Interest in Contemporary Coffee Shop Using RFM Model

  • Raja Aulia Passalaras Universitas Bakrie
  • Risma Yanti Daulay Universitas Bakrie
  • Jerry Heikal Universitas Bakrie

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.

References

Adam Startup (2023). Customer Segmentation with RFM Analysis | Google sheet/ Excel | Indonesia | 2023. [Video]. Youtube. https://www.youtube.com/watch?v=5BgAfG4e1wY&t=150s

A. M. Hughes. Strategic database marketing, Chicago, Probus Publishing Company.

A T Widiyanto, A Witanti (2020). Customer Segmentation Based on RFM Analysis Using the K-Means Algorithm as a Basis for Marketing Strategy (Case Study of PT Coversuper Indonesia Global). CONSTELLATION: Convergence of Technology and Information Systems.

B. E. Adiana, i. Soesanti and A. E. Permanasari, (2018). Analisis Segmentasi Pelanggan Menggunakan Kombinasi RFM Model dan Teknik Clustering. Jurnal Terapan Teknologi Informasi, vol. 2, pp. 23-32, 2018.

Beta Estri Adiana, Indah Soesanti, Adhistya Erna Permanasari (2018). Analysis Customer Segmentation Using a Combination of RFM Models and Clustering Techniques. JUTEI Edition Volume.2 No.1 April 2018 ISSN 2579-3675, e-ISSN 2579-5538 DOI 10.21460/jutei.2017.21.76

Bob Foster (2016). Impact of Brand Image on Purchasing Decision on Mineral Water Product “Amidis” (Case Study on Bintang Trading Company). American Research Journal, Vol. 2, No. 1,Hal. 1-11

C.H dan Y.S Chen (2009). Classifying the Segmentation of Customer value via RFM model and RS Theory. Expert Systems with Application, Vol. 36 Issue 4 No.2, hal 216-221

Fakhri Hadi, Dini Octari Rahmadia, Ferdian Hadi Nugraha, Nada Putri Bulan, Mustakim, Siti Monalisa (2017). Application of K-Means Clustering Based on RFM Mofek as Mapping and Supporting Customer Management Strategy (Case Study: PT. Herbal Penawar Alwahidah Indonesia Pekanbaru). Journal of Science, Technology and Industry, Vol. 15, no. 1, December 2017, pp.69 – 76

Khairi Nisa, Jerry Heikal (2023), Manja Beauty Skincare Customer Segmentation Strategy using the Analytical RFM Model. JATI (Information Engineering Student Journal).

Tsiptsis, K. and A. Chorianopoulos. (2009). Data mining techniques in CRM: inside customer segmentation. Chichester. West Sussex. United Kingdom : Wiley.

William Tanuwijaya, Steven Tandrayuwana, Adriana Aprilia. (2022). Influence Product Innovation on Interest in Buying Coffee Drinks Through Motivation as a Moderating Generation Variable for Generation Z in the City of Surabaya. Journal of Hospitality Management, Vol. 8, no. 1, March 2022, 50–58.

Wiratama Ahsani Taqwim, Nanang Yudi Setiawan, Fitra A. Bachtiar, (2019). Customer Segmentation Analysis Using the RFM Model at Pt. Arthamas Citra Mandiri Using the Fuzzy C-Means Clustering Method. Journal of Information Technology and Computer Science Development.
Published
2024-04-04
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