Analyzing the Customer Journey through Data Analytics

The quantitative content analysis identified five underlying themes of the customer journey, namely, service satisfaction, failure and recovery, co-creation, customer response, channels and technological disruption. The results section reviewed and discussed each theme and its sub-themes in turn. The review identified important gaps in the literature related to the key stages of a customer journey. Customer Journey Mapping (CJM) is pivotal for understanding and enhancing customer experiences across touchpoints. The integration of real-time data analytics into CJM has transformed this traditionally static tool into a dynamic framework capable of tracking and optimizing customer interactions. This paper explores the methodologies, tools, and benefits of combining real-time data analytics with CJM. The discussion includes a comprehensive review of related literature, implementation strategies, challenges, and future directions. This paper argues that real-time data analytics enhances CJM by enabling continuous adaptation to customer behaviour’s, resulting in improved customer satisfaction and business performance. Understanding and enhancing customer experiences has emerged as a central focus for businesses seeking to remain competitive in today’s dynamic market landscape. Customer Journey Mapping (CJM), a widely used methodology, provides a structured approach to visualizing the customer's interactions across various touchpoints with a business. The customer journey is becoming more complex due to digitization of business processes, broadening the gap between the proposed journey and the journey that is actually experienced by customers. Customer Journey Analytics (CJA) aims to detect and analyse pain points in the journey in order to improve the customer experience. This study proposes an extended version of the Customer Journey Mapping (CJM) model, to measure the impact of different types of touchpoints along the customer journey on customer experience, and to apply process mining to gain more insight in the gap between proposed and actual journeys. Moreover, this model is used to develop dedicated CJA based on process mining techniques. A case study on e-commerce applies the CJM-model in practice and shows how the combination of process mining techniques can answer the analysis questions that arise in customer journey management. This research contributes to both academic discourse and managerial practice by offering actionable insights into how brands can ethically and effectively engage with digital consumers. It underscores the necessity for marketers to balance technological innovation with consumer trust and transparency. Ultimately, this study provides a robust framework for understanding the digital consumer psyche and offers strategic recommendations for navigating the rapidly evolving landscape of social media marketing.