The WhatsApp Business Experience in Customer Relationship Management: An LDA Analysis of User Reviews

Abstract

Purpose – The aim of this study is to analyze user experiences related to WhatsApp Business and to reveal user feedback on digital communication tools within the context of Customer Relationship Management (CRM). Based on user reviews, themes related to satisfaction and problem areas were identified, and the dimensions of user experience regarding the application were examined.
Design/methodology/approach – In this research, 1,459 WhatsApp Business reviews posted by users in Australia, Canada, and the United States between 2019 and 2024 were analyzed. The dataset was obtained from the Kaggle platform and consists of secondary data compiled from Apple App Store user reviews. Latent Dirichlet Allocation (LDA), a topic modeling method within Natural Language Processing (NLP) techniques, was employed to identify latent themes in the reviews. The data preprocessing and modeling procedures were conducted using the Python programming language.
Results – The analysis revealed that user reviews were clustered under five main themes: “Blocked accounts and experienced issues” (25.7%), “Application performance and errors” (20.7%), “Requests for new features and ease of use” (19.6%), “Updates and overall satisfaction” (17.5%), and “Multilingual comments and appreciation messages” (16.4%). Examination of the rating distribution indicated that users predominantly provided extreme evaluations, reflecting either very high satisfaction or strong dissatisfaction.