How AI competencies can make B2B marketing smarter: strategies to boost customer lifetime value.

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Frontiers in Artificial Intelligence Pub Date : 2024-12-18 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1451228
Tayyeba Bashir, Tan Zhongfu, Burhan Sadiq, Ammara Naseem
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Abstract

There has been a rapid rise in utilization of artificial intelligence (AI) in many different sectors in the last several years. However, business-to-business (B2B) marketing is one of the more notable examples. The initial assessments emphasize the significant advantages of AI in B2B marketing, including its knack for yielding unique understandings into consumer behaviors, recognizing crucial market trends, and improving operational efficiency. However, there seems to be a limited grasp of the optimal way to develop artificial intelligence competencies (AIC) for B2B marketing and how these attributes inevitably affect customer lifetime value (CLV). Equipped with AIC and B2B marketing literary fiction, this research unveils a theoretical research framework for evaluating the repercussions of AIC on B2B marketing capabilities and, subsequently, on CLV. We analyze the suggested research model using partial least squares structural equation modeling (PLS-SEM), leveraging 367 survey replies from Pakistani companies. The outcomes show a significant relationship that describe the ability to leverage AIC to enhance CLV, and also signifies the mediating role of B2B marketing capabilities to enhance CLV by integrating AIC in internet marketing. The findings of this study provide practical implications for marketers to monetize their marketing skills to enhance CLV and researchers with theoretical underpinnings of integration of AIC into marketing.

人工智能能力如何使B2B营销更智能:提高客户终身价值的策略。
在过去几年中,人工智能(AI)在许多不同领域的应用迅速增加。然而,企业对企业(B2B)营销是一个更显著的例子。初步评估强调了人工智能在B2B营销中的显著优势,包括其对消费者行为的独特理解、识别关键市场趋势以及提高运营效率的能力。然而,对于为B2B营销开发人工智能能力(AIC)的最佳方式,以及这些属性如何不可避免地影响客户终身价值(CLV),似乎掌握有限。本研究结合AIC和B2B营销文学小说,揭示了一个理论研究框架,以评估AIC对B2B营销能力的影响,进而对CLV的影响。我们使用偏最小二乘结构方程模型(PLS-SEM)分析了建议的研究模型,利用了来自巴基斯坦公司的367份调查回复。结果显示了显著的关系,描述了利用AIC提高CLV的能力,也表明了B2B营销能力通过将AIC整合到网络营销中来提高CLV的中介作用。本研究结果为营销人员将营销技巧货币化以提高CLV提供了实践启示,也为研究人员将AIC整合到营销中提供了理论基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
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