Một nghiên cứu liên ngành giữa phân tích phân khúc khách hàng trong marketing và phương pháp học máy

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Tác giả: Trung Thành Hồ, Đăng Sơn Nguyễn

Ngôn ngữ: vie

Ký hiệu phân loại: 006.31 Machine learning

Thông tin xuất bản: Phát triển Khoa học & Công nghệ: Khoa học - Kinh tế - Luật và Khoa học Quản lý (ĐHQG TP. Hồ Chí Minh), 2022

Mô tả vật lý: 2005-2015

Bộ sưu tập: Metadata

ID: 498895

Thêm vào giỏ

Customer segmentation is one of the key factors in managing customers and building the appropriate marketing strategies. Segmenting customer groups will help managers understand the characteristics of their customers or consumer behaviors, thereby reaching the right target customers, retaining customers (Customer Retention), increasing revenue and competitive advantages of the business. However, finding the right customer groups is a challenge that businesses need to solve on a solid and reliable basis. Along with the support from current technology solutions such as Customer Relationship Management (CRM) and the application of algorithms and methods including both qualitative and quantitative research to enable businesses to cluster customer groups in marketing analysis. This article concentrates on introducing a hybrid model that combines RFM (Recency, Frequency, Monetary) and Machine Learning to analyze customer segmentation. The study was conducted through an empirical method on a dataset with 541,909 transactions of online retail stores, clustering 5 customer segments with the characteristics of each cluster being tested for quality demonstrating the effectiveness and applicability of the study.Phân tích phân khúc khách hàng (Customer Segmentation) là một trong những vấn đề quan trọng trong việc quản lý khách hàng và xây dựng các chiến lược marketing phù hợp. Việc phân chia thành các nhóm khách hàng sẽ giúp những người quản lý nắm bắt rõ những đặc điểm của khách hàng hay hành vi tiêu dùng của họ, từ đó tiếp cận đúng khách hàng mục tiêu, giữ chân được khách hàng (Customer Retention), gia tăng được doanh thu và lợi thế cạnh tranh của doanh nghiệp. Tuy nhiên, phân tích để tìm ra đúng nhóm khách hàng là một vấn đề đặt ra mà doanh nghiệp cần giải quyết dựa trên cơ sở vững chắc và đáng tin cậy. Cùng với sự hỗ trợ từ các giải pháp công nghệ hiện nay như quản lý quan hệ khách hàng (Customer Relationship Management) và sự phát triển mạnh mẽ của công nghệ Khoa học dữ liệu, việc áp dụng các thuật toán, các phương pháp bao gồm cả định tính và định lượng nhằm giúp phân chia các nhóm khách hàng trong phân tích marketing. Bài báo này tập trung thực hiện một nghiên cứu liên ngành kết hợp giữa phương pháp RFM (Recency, Frequency, Monetary) và học máy (Machine Learning) để phân tích phân khúc khách hàng. Nghiên cứu được thực hiện thông qua phương pháp thực nghiệm trên tập dữ liệu (dataset) với 541,909 giao dịch của cửa hàng bán lẻ trực tuyến đã gom cụm được 5 phân khúc khách hàng với những đặc trưng của từng cụm được kiểm định chất lượng đã cho thấy tính hiệu quả và khả năng ứng dụng của nghiên cứu.

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