The new business challenges in the B2B sector are determined by connected ecosystems, where data-driven decision making is crucial for successful strategies. At the same time, the use of digital marketing as a communication and sales channel has led to the need and use of Customer Relationship Management (CRM) systems to correctly manage company information. The understanding of B2B traditional Marketing strategies that use CRMs that work with Artificial Intelligence (AI) has been studied, however, research focused on the understanding and application of these technologies in B2B digital marketing is scarce. To cover this gap in the literature, this study develops a literature review on the main academic contributions in this area. To visualize the outcomes of the literature review, the results are then analyzed using a statistical approach known as Multiple Correspondence Analysis (MCA) under the homogeneity analysis of variance by means of alternating least squares (HOMALS) framework programmed in the R language. The research results classify the types of CRMs and their typologies and explore the main techniques and uses of AI-based CRMs in B2B digital marketing. In addition, a discussion, directions and propositions for future research are presented.

B2B 领域的新业务挑战由互联生态系统决定，其中数据驱动的决策对于成功的战略至关重要。同时，使用数字营销作为沟通和销售渠道导致需要和使用客户关系管理 (CRM) 系统来正确管理公司信息。已经研究了对使用与人工智能 (AI) 协同工作的 CRM 的 B2B 传统营销策略的理解，但是，专注于这些技术在 B2B 数字营销中的理解和应用的研究很少。为了弥补文献中的这一空白，本研究对这一领域的主要学术贡献进行了文献综述。为了可视化文献综述的结果，然后使用称为多重对应分析 (MCA) 的统计方法在方差齐性分析下通过交替最小二乘法 (HOMALS) 框架对结果进行分析，该框架以 R 语言编程。研究结果对 CRM 的类型及其类型进行了分类，并探讨了基于 AI 的 CRM 在 B2B 数字营销中的主要技术和用途。此外，还提出了未来研究的讨论、方向和建议。