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     2026:7/2

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN: (Print) | 2582-7138 (Online) | Impact Factor: 9.54 | Open Access

AI-Driven Next Best Action Models Integrated in Veeva CRM: Architecting Personalization for Healthcare Providers

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Abstract

The healthcare industry is undergoing a significant transformation, with artificial intelligence (AI) playing an important role in enhancing healthcare provider (HCP) engagement. AI-driven Next Best Action (NBA) models are at the forefront of this change, allowing life sciences organizations to deliver personalized, timely, and relevant interactions with HCPs. By analyzing vast datasets, these models provide actionable insights that inform the most effective communication strategies, thereby improving engagement and outcomes. Veeva CRM serves as a strong platform facilitating the integration and execution of NBA models. Its suite of tools, including Veeva Vault CRM, Engage, and Approved Email, allows for seamless orchestration of personalized HCP experiences across multiple channels. These tools ensure that field teams can access comprehensive customer insights, enabling them to engage HCPs with the right information at the right time, while maintaining compliance with industry regulations. 
This whitepaper aims to inform and guide cross-functional implementation teams on the strategic integration of AI-driven NBA models within Veeva CRM. It explores the benefits of personalized HCP engagement, outlines the operational considerations for successful implementation, and discusses the potential challenges and solutions. By maximizing the capabilities of AI and Veeva CRM, organizations can enhance their engagement strategies, drive efficiency, and ultimately improve patient care outcomes
 

How to Cite This Article

Maneesh Gupta (2024). AI-Driven Next Best Action Models Integrated in Veeva CRM: Architecting Personalization for Healthcare Providers . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 5(1), 1725-1729. DOI: https://doi.org/10.54660/.IJMRGE.2024.5.1.1725-1729

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