B2B Marketing Automation: Evaluation and Dynamic Optimization
DOI:
https://doi.org/10.56397/JWE.2025.08.10Keywords:
B2B marketing automation, three-dimensional evaluation system, dynamic optimization algorithm, artificial intelligence, machine learning, customer conversion rate, marketing cost, customer satisfaction, data integration, process optimization, multi-channel collaboration, customer relationship management, digital marketing, intelligent marketingAbstract
Amidst intensified market competition and the increasing diversification of customer demands, B2B enterprises are confronted with unprecedented challenges in their marketing activities. Traditional marketing models are insufficient to meet the complex and ever-changing market demands. The advent of marketing automation technology has provided B2B companies with an efficient and precise marketing solution. However, numerous issues still exist in the implementation of B2B marketing automation, such as difficulties in data integration, inadequate process optimization, and the lack of scientific basis for effect evaluation. These problems restrict the further development and application of marketing automation. This study aims to construct a scientific B2B marketing automation evaluation system and dynamic optimization algorithm to enhance the marketing efficiency and effectiveness of B2B enterprises.
