Google Cloud Platform Services in Build Out of a Digital Contact Center
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V5I3P114Keywords:
Digital Contact Centers, Google Contact Center AI (CCAI), Cloud-Native Architecture, Conversational Artificial Intelligence, Intelligent Customer Engagement, Event-Driven Architectures, Customer Experience AnalyticsAbstract
Contact center architectures are becoming increasingly important in response to customer journey complexities and digital communication channels. Traditional contact center on-premise solutions experience problems with channel management fragmentation, scalability issues, and insufficient analytics; as a result they cannot meet the demand for modern customer interaction needs for real time, personalized interactions. This paper will explore the design, deployment, and operation of a cloud native digital contact center using Google Cloud Platform (GCP) to determine how the GCP platform and Google Contact Center AI (CCAI) can provide customer service operations with AI driven automation, microservice based scalability, and data focused decision support. This study will examine the capabilities of the GCP ecosystem including CCAI to transform the way customers interact with companies and the processes used to support those interactions. A qualitative architecture centered research method will be employed to evaluate critical components of the solution such as Dialogflow CX for conversational agents, intelligent routing of customer interactions and agent support, event based orchestration with Cloud Pub/Sub, containerized services on Google Kubernetes Engine, and advanced analytics provided by BigQuery and CCAI Insights. Additionally, the study will investigate best practices for securely integrating digital contact center solutions with enterprise CRM systems and the importance of end-to-end observability. Research results indicate that digital contact centers deployed on the GCP platform will produce significant improvements in key contact center metrics including decreased average handling times, higher use of virtual agents, increased customer satisfaction ratings, and higher levels of operational visibility. However, the study also identifies several key challenges related to data governance, regulatory compliance, and continuous improvement of AI models. Combining the architectural design aspects of digital contact centers with observed operational results provides an actionable reference model for organizations seeking to modernize their contact center operations and outlines potential areas for future research, specifically regarding the use of generative AI to enhance personalization and predictively drive customer engagement.
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