Customer Segmentation of Pabuaran Store on Shopee E-Commerce Using RFM Model Analysis (Case Study of H&M Brand Sales Products) - Arthanugraha, Adam; Azzuhri, Muhammad Basyar; Ramadhan, Yufiansyah Wahyu; Heikal, Jerry (BUDGETING : Journal of Business, Management and Accounting, 2024)
E-Commerce creates business activities that make it easier for people to be more effective because business transactions between sellers and buyers are not limited by space and time. Pabuaran store is one of the personal shopper service providers which started its business in 2019, the marketplace phenomenon in that year has increased massively and online business players in one of the marketplaces have also reached 7 (seven) million in 2019. Product graph seen in the Pabuaran Store's Services business tends to decline, this requires business actors to take strategic steps to maintain their existence in the business world. This is used encouraged service business owners to gain profits in the midst of the phenomenon that is occurring. In determining the variables, the general model used to group customers is the RFM (Recency, Frequency, Monetary) Model, which groups customers based on the time interval of the customer's last visit, frequency of visits, and the amount of value issued as company royalties(1). The recency value can determine the time span since the customer's last transaction. The frequency value can indicate how many transactions each customer conducts with the company. Additionally, the monetary value can reveal the amount of expenditure made by each customer in each transaction with Pabuaran Store on Shopee. The three segments have different campaign strategies. For Segment 1, a reactivation campaign is implemented, such as conducting live videos on Shopee. In Segment 2, a broadcast retention message is delivered to customers who have previously purchased products from Pabuaran Store. As for Segment 3, where loyal customers are identified, a loyalty point system is introduced to keep these customers engaged. Keywords: E-Commerce, Frequency, Monetary, Personal shopper, Recency.