Using Artificial Intelligence in Business-to-Business (B2B) Marketing: Challenges and Future Directions

As artificial intelligence (AI) gains traction in revolutionizing business-to-business (B2B) marketing, there's an increasing need to fully grasp its adoption and utilization for enhancing B2B marketing strategies. This research delves into the realm of AI techniques and their application throughout the four stages of the customer life cycle in B2B marketing: reaching out, acquiring, converting, and retaining clients. Additionally, it evaluates findings from five surveys within the B2B industry, aiming to: 1) assess B2B marketers' familiarity and attitudes towards AI implementation, 2) outline the diverse applications of AI in B2B marketing, and 3) examine the perceived advantages and obstacles associated with its use in this domain. The study amalgamates various machine learning (ML) methods suitable for B2B marketers and utilizes the technology acceptance model (TAM) to gauge how these professionals perceive AI's benefits. Moreover, it explores impediments to AI adoption, such as concerns regarding data privacy and potential job displacement. To underscore the advantages of AI, the research presents three instances of successful AI integration in B2B marketing practices. Ultimately, the paper wraps up by summarizing the theoretical and managerial implications of AI adoption in B2B marketing, along with suggesting avenues for future research.

کلیدواژه های Using Artificial Intelligence in Business-to-Business (B2B) Marketing: Challenges and Future Directions:

Artificial intelligence ، Machine learning ، Propensity model ، Deep learning ، B2B marketing