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Exploring the Extent of Relevance of XR and AI (Chat GPT) Application in the Marketing of Technological
Industrial Products From the Buyer Journey Perspective, 2023
ABSTRACT
Over the years of collaboration between the author and small and medium-sized enterprises (hereinafter,
SMEs) involved in the manufacturing and marketing of technological industrial products, a need for tailored
marketing strategies for that type of product has emerged. Technological industrial products are technologies
developed for and sold in industrial markets.
Strategies for marketing of technological industrial products deviate notably from marketing strategies applied to
consumer goods. Simultaneously, the wholesale adoption of digital technologies, though effective in consumer
goods marketing, (e.g., Berman B., Pollack D., 2021; Cranmer, Dieck, & Fountoulaki, 2020; etc.) does not
seamlessly translate to the realm of technological industrial products.
Consumer marketing strategies are initially deeply rooted in comprehending consumer psychology and behavior
(Kotler,2012; Kotler & Keller, 2012). The buyer journey for consumer goods involves a spectrum of choices
influenced by behavioral, psychological, and demographic factors (Kotler, Armstrong & Harris, 2019; Hollesen,
2019). Frequently, the buyer and user coincide, resulting in swift and impulsive purchasing decisions.
In contrast, within the domain of technological industrial products, a distinct disparity emerges. The complexity
of these products makes a meaningful user participation in decision-making highly implausible (Saavedra,
2018). Instead, the onus of product selection rests upon specialized buyers, delegating users the role of
influencers, at best. Within this context, purchasing decisions are complex and well-calculated (Hall, 2020; Hall,
2017), (Hollesen, 2019).
The disparity mentioned has ignited the author´s curiosity regarding the integration mechanisms of digital
technologies, specifically extended reality (XR) and artificial intelligence (AI/ChatGPT), within the technological
industrial products marketing strategies. While studies exist exploring the application of XR in various consumer
goods contexts, the potential of applying these same technologies to technological industrial products remains
largely uncharted.
This curiosity has created the starting point for the inception of the current study.
This contribution endeavors to address two (2) primary objectives within the context of a Danish technological
SME operating in industrial markets. The company manufactures a technological product within the heating,
ventilation, air conditioning (HVAC) industry and finds the application for its products primarily within industrial
construction markets.
Primarily, the study aims to outline the challenges encountered by the case study company while applying
digital technologies in its marketing activities, with a focus on buyer journey milestones for a technological
industrial product buyer.
SMEs engaged in manufacturing and marketing of technological industrial products recognize the imperative of
adopting digital technologies into their processes, including their marketing activities. As mentioned above, the
existing successful practices and theories predominantly focus on consumer product marketing. As a result of
the lack of existing practices and theories, these companies implement digital technologies as effectively as
possible and develop their own unique practices. This study focuses on exploring these practices as they are
applied by the case study company with the purpose of making a contribution to the theory developing.
Secondly, the study homes in on the specific hindrances encountered when implementing XR and AI (ChatGPT)
technologies in this context. SMEs involved in manufacturing and marketing technological industrial products
appear to apply these technologies differently in the buyer journey compared to their application in consumer
product marketing. E.g. this is evident in activities like applying an XR technology for a product prototyping that
is facilitated by virtual reality (VR) (Christiansen, Borregaard, G. Antonsen, S.Laursen & D. Brunoe,, 2021).
Through this contribution, the author aims to gain insights into the current challenges experienced by the case
study company as it undertakes the digitization of its marketing activities, while analyzing the nature of the buyer
journey of a technological industrial product buyer.
The chosen methodology for this research is a single case study, employing both the methodological framework
proposed by Yin (2003, 2014) and an exploratory qualitative approach (Stebbins, 2001). The selection of the
case study company followed a purposeful sampling technique (Kelly, 2010; Palinkas et al., 2015), which
facilitated a comprehensive exploration of multifaceted challenges within an authentic business setting. Within
the business science domain, the case study methodology, as endorsed by Yin (2003, 2014), aligns suitably
with researching XR and AI(ChatGPT) technologies' applications throughout a case study company's marketing
activities along the buyer journey.
Triangulation, advocated by Dubois and Gibbert (2010), was essential for this case study research to gather
data from multiple sources. This strategy enhances the study's validity and dependability, especially when
conducting qualitative research in the realm of industrial marketing (Farquhar et al., 2020).
The primary data was collected through semi-structured interviews (Brinkmann & Kvale, 2009) and
observational studies (Morgan et al., 2016). Following Eisenhardt and Graebner's (2007) recommendations,
relevant managers from the case study company were engaged in interviews, as they hold diverse perspectives
on the study phenomenon. This approach facilitates a comprehensive understanding of the case study.
Three (3) extensive interviews were conducted with experts from leading Danish digital marketing technology
agencies specializing in XR product development. These experts were unrelated to the case study company,
ensuring impartiality. These interviews yielded a comprehensive analysis after accumulating sufficient data and
understanding the phenomenon.
The extensive semi-structured interviews were done using a question guide encompassing open-ended
inquiries spanning various subjects relevant to the case study. This approach enables productive dialogues,
providing a lot of details beyond our initial expectations. The collected data undergoes rigorous analysis using
qualitative content analysis (Mayring, 2014).
In addition to interviews, the sales and marketing processes of the case study company are observed to gain a
deeper comprehension of their operations. This strategy offers a heightened perspective on the study
phenomenon and facilitates a comprehensive grasp of the data. Observations encompass digital content such
as the website, white papers, blogs, social media presence, and the company's activities on these platforms.
The mix of data from interviews and observations (Dubois and Gibbert, 2010; Farquhar et al., 2020) provide a
holistic understanding of the application XR and AI (Chapt GPT) technologies in general and how the case
study company applied these.
The empirical findings offer tangible insights into the relevance of application and significance of XR and AI
(Chat GPT) technologies in the case study company's marketing activities. The uniqueness of this study lies in
addressing the challenges that SMEs involved in manufacturing and marketing technological industrial products
encounter when selecting suitable digital technologies for their marketing activities. As a fundamental stepping
stone, this contribution sets the stage for further exploration, promising enriched insights across a broader
spectrum.
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