Artificial Intelligence (AI) is a powerful tool for marketing applications (Overgoor, Chica, Rand, and Weishampel 2019: 156). The field of International Business has transformed, from an industrial (predominantly product based), perspective, to a knowledge-based perspective (Paschen, Kietzmann and Kietzmann 2019: 1410). In the knowledge economy (Aliyev 2021: 66), knowledge has become the main factor in the development of society. There is no shortcut to this, and organizations must keep informed about the ways in which their sectors are disrupted by technological advancements (McKinsey Global Institute 2013).
From the large sum of quality information/ data gathered by organizations today, knowledge has become a necessary, and sought-after resource as it has overtaken physical capital in terms of organizational importance (Archer-Brown and Kietzmann, 2018; Paschen, Kietzmann, and Kietzmann 2019). Knowledge is currently at the centre of marketing, as informed marketing towers over all strategies, and firms that implement this gain competitive advantage. Informed marketing leads to customer centric strategies that lead to productive steps in an organization’s business process.
For B2B businesses specifically, it is critical to create and offer services from an informed and analytical stance with market knowledge such as consumer demographics, consumer personas, plus audience views and perspectives. Systematic management of knowledge-based marketing decisions into effective B2B marketing strategies is critical for the survival of an organization in today’s business environment (Shaw et al., 2001). As organizations carry out social media marketing, they can gather data on customers. This data is collected through AI tools already present on social media sites.
Artificial Intelligence (AI) tools have enabled for the effective management of knowledge by businesses enabling them to gather more insights on customers, reach more customers, and create more personalized experiences using the demographics and data acquired (Song 2020). Companies that utilize customer insights and analysis tools to create informed marketing strategies have reported proper and more valid leads as compared to those who do not (Bellatreche 2020; Bovée and Thill 2020). Aside from this, AI systems aid in optimizing marketing strategies once the right data driven tools are utilized.
These tools effectively target a firm’s current and most active customer base, to prevent the conundrum that stems from ‘marketing into the dark’ (Apogaeis 2022). While using ads for social media marketing, firms must utilize AI tools to understand consumer behaviour, mine relevant data, and generate the right personalized content guaranteed to catch the eye of the consumer (Scott 2022). The advantage that AI tools have over statistical approaches is that AI has machine learning qualities that enable adaptability to market behavioural changes, and continually improve the performance of the firm as more data is generated from consumers (Apogaeis 2022).
This is vital in today’s ever-changing nature of International Business (Peng and Meyer 2019). As market dynamics and consumer behaviour changes, so should the strategies that marketers use. Data drawn from AI systems within social media apps helps marketing teams track and predict trends, and choose which trends are most compatible with their marketing strategy. Artificial Intelligence is the term used to refer to the algorithms, technologies, and mathematics that make machines quicker and smarter (Scott 2022).
Recommendation systems, such as the ones on Youtube, Twitter, Tiktok, Facebook, and LinkedIn, gather data from users and push to these users the type of content they like (Keegan and Canhoto 2022). The users find this content interesting and regularly visit the sites pushed to them. This shows that a large aspect of consumers’ online lives is already AI powered, with machines running in the background to guide them to content that they will fancy, such that they may interact with it, and generate more information for future recommendations.
In this way, each user has tailored their online atmosphere with the power of AI tools that work as guidance systems in the background of social media apps.
This works hand in hand with the advancement of machine learning and natural language processing that give insight into the personality of the customer, which organizations can access through demographic details, and leverage to tailor proper customer relationship management (Davenport et al. 2020).
References.
Aliyev Alovsat G (2021) ‘Development System of Hierarchical Indicators for Analyzing and Measuring the Level of Growth of Information and Knowledge Economy’, Management dynamics in the knowledge economy, 9(1), pp. 65–80. doi:10.2478/mdke-2021-0005.
Apogaeis. (2022). How Artificial Intelligence Will Change Business Forever. Available from: https://www.apogaeis.com/blog/how-artificial-intelligence-will-change-business-forever/ (Accessed 20/062022).
Archer-Brown, C. and Kietzmann, J.(2018), “Strategic knowledge management and enterprise social media”, Journal of Knowledge Management, Vol. 22 No. 6, pp. 1288-1309
Bellatreche, L. (2020) Big data analytics: 8th International Conference, BDA 2020, Sonepat, India, December 15-18, 2020, proceedings. 1st ed. 2020. Edited by L. Bellatreche. Cham, Switzerland: Springer. Available at: https://doi.org/10.1007/978-3-030-66665-1.
Bovée, C.L. and Thill, J.V. (2020) Business in action. Ninth, Global edition. Harlow, England: Pearson.
Davenport, T., Guha, A., Grewal, D. and Bressgott, T. (2020), “How artificial intelligence will change the future of marketing”, Journal of the Academy of Marketing Science, Vol. 48 No. 1, pp. 24-42.
Keegan, B.J., Canhoto, A.I. and Yen, D.A. (2022) ‘Power negotiation on the tango dancefloor: The adoption of AI in B2B marketing’, Industrial marketing management, 100, pp. 36–48. Available at: https://doi.org/10.1016/j.indmarman.2021.11.001.
McKinsey Global Institute. (2013). Disruptive technologies: Advances that will transform life, business, and the global economy. 1 (1
Overgoor, G. et al. (2019) ‘Letting the Computers Take Over: Using AI to Solve Marketing Problems’, California management review, 61(4), pp. 156–185. doi:10.1177/0008125619859318.
Paschen, J., Kietzmann, J. and Kietzmann, T.C. (2019) ‘Artificial intelligence (AI) and its implications for market knowledge in B2B marketing’, The Journal of business & industrial marketing, 34(7), pp. 1410–1419. doi:10.1108/JBIM-10-2018-0295.
Peng, M.W. and Meyer, K. (2019) International business. Third edition. Australia: Cengage Learning.
Shaw, M.J., Subramaniam, C., Tan, G.W. and Welge, M.E. (2001), “Knowledge management and data mining for marketing”, Decision Support Systems, Vol. 31 No. 1, pp. 127-137.
Song, M. (2020) Big data analytics and knowledge discovery : 22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14-17, 2020, proceedings. 1st ed. 2020. Edited by M. Song. Cham, Switzerland: Springer. Available at: https://doi.org/10.1007/978-3-030-59065-9.
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