Understanding AI-driven Marketing Metrics

The integration of Artificial Intelligence (AI) in marketing has significantly transformed traditional marketing strategies, enhancing efficiency, customer engagement, and personalization. This study conducts a systematic literature review and meta-analysis to explore the impact of AI-driven marketing metrics on business performance. Marketing metrics, categorized into financial and non-financial measures, serve as essential tools for evaluating marketing effectiveness. AI-driven metrics such as customer lifetime value (CLV), return on investment (ROI), and customer acquisition cost (CAC) provide data-driven insights that optimize marketing strategies. The Technology Acceptance Model (TAM) is applied to assess the adoption of AI-based tools in business environments, revealing that perceived usefulness and ease of use significantly influence AI acceptance. Findings from the meta-analysis highlight that AI-driven personalization enhances customer satisfaction, while AI-powered customer service tools such as chatbots improve customer engagement. However, concerns related to data privacy and algorithmic biases remain critical barriers to widespread AI adoption. AI-driven customer relationship management (CRM) practices contribute to sustainable business growth, particularly for small and medium-sized enterprises (SMEs), by improving customer data management, segmentation, and predictive analytics. The study also underscores the role of AI in e-commerce, where predictive analytics, recommendation engines, and targeted advertising enhance customer retention and trust. Despite these benefits, challenges such as digital literacy gaps, regulatory concerns, and consumer trust issues persist. Overall, this study contributes to the existing body of knowledge by synthesizing empirical findings on AI-driven marketing strategies, providing insights for marketers, policymakers, and business stakeholders. It advocates for a balanced approach that combines AI’s analytical capabilities with human intuition to maximize marketing effectiveness while addressing ethical and privacy concerns.