Improving Digital Marketing Through Analyzing Arabic Customer Reviews by Natural Language Processing

Digital marketing has become a practical part of modern business strategies, allowing companies to reach wider audiences and engage with customers innovatively. Understanding customer sentiment towards products, services, and experiences is essential for effective marketing campaigns. In this line, Sentiment Analysis (SA), a task of Natural Language Processing, offers valuable insights by automatically analyzing and categorizing opinions expressed in textual data. Consequently, this paper studies different aspect-based approaches to SA in digital marketing and provides a literature review on the most recent studies in Middle East, that focuses on reviews analysis. Note that Arabic Chat Alphabet (ACA) is the informal language used in online chats, social media platforms, and instant messaging applications in the Middle east. This paper highlights the substantial gap in the in the ABSA literature concerning aca across different dialects—particularly the Egyptian dialect, also referred to as Egyptizi., showing that the demand for developing new models capable of mining and evaluating the ACA continues to grow to help analyze the reviews written in ACA to assist personalization and digital marketing.