Customer Service Automation Through Ai-Powered CRM: Impact On Marketing Target Accuracy
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Wiwin Riski Windarsari
This study addresses the limitations of traditional Customer Relationship Management (CRM) systems by analyzing the adoption and impact of Artificial Intelligence (AI) integration (AI-Powered CRM). Informed by the Technology Acceptance Model (TAM) for employee perception and the Resource-Based View (RBV) for strategic capability, the primary objective is to evaluate how AI-driven automation enhances customer service processes and, subsequently, impacts marketing efficiency. The research employs an exploratory qualitative case study design, utilizing in-depth interviews, document analysis, and system observation on a single organization to gather rich, contextual data. The results demonstrate that AI integration significantly accelerated service, with chatbots handling 65–70% of routine queries and drastically reducing response times. Operationally, these improvements fostered high employee acceptance (TAM). Strategically, the AI-Powered CRM generated refined predictive analytics, resulting in a 12–18% improvement in campaign conversion rates and efficient resource allocation, confirming that AI creates a valuable and difficult-to-imitate strategic capability (RBV). The study concludes that AI-Powered CRM is a critical enabler for both operational efficiency and long-term strategic competitiveness in digital markets.
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