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Use of Artificial Intelligence in Marketing
Dalir Khabibulin
Student of Oxbridge International School,
Marketing Faculty, Tashkent, Uzbekistan
Abstract
It is Universally known that Artificial Intelligence refers to the simulation of human intelligence in
machines that are programmed to think and act like humans by using big data and algorithms to
achieve essential techniques. AI has been used more than ever across different jobs and industries
which means that we are in touch with it everyday even if we don’t notice that. Whether we are
watching recommended videos in social media or unlocking phone with Face ID.
The review analyzes the changes in advertising and using AI to develop customer experience. The
methodology describes what information and methods were used to write the article. Data such as
case analysis, research of scientific literature, data on real Nike initiatives, etc. The conclusion
summarizing the results of the study, focusing on the main advantages and challenges of using AI
in marketing.
Keywords:
AI, Nike, Marketing, customers, clients, effectiveness, analytics, advertisement.
JEL Classification codes:
M31, O33.
Suggested citation:
Khabibulin, D. (2024). Use of Artificial Intelligence in Marketing.
European
Journal of Management, Economics and Business, 1
(3), 217-221. DOI: 10.59324/ejmeb.2024.1(3).18
Introduction
Artificial intelligence (AI) is increasingly being used in a wide variety of fields, including marketing.
At the moment, using the example of Nike, you can clearly see all the advantages of using artificial
intelligence in marketing. Since Nike is a company that is completely dependent on consumers, this
directly means that artificial intelligence in this example is necessary for a dense analysis of each
client and their tastes, which makes it important for the effectiveness of a marketing strategy.
Ultimately, in order to verify the effectiveness of using artificial intelligence, it is necessary to
compare forecasts made by humans and forecasts made by artificial intelligence. These types of
studies can help determine which direction to move and improve (Verma, et al., 2021).
Nike is the world largest sports clothes company which actively using AI for more than 13 years.
Delving into the details, the main features that are impacting Nike customers experiences are
Personalized Recommendations, Virtual assistants, AI-Based Insights and etc. From 2016 Nike
started to actively use algorithms for personalized customer experiences and recommendations as
therefore they include AI into Nike+ app that offer products based on customers preferences. Two
years later, in 2018 Nike bough companies Zodiac and Celect which are specialized on the analytics
of data which therefore furtherly develop participation of AI in Nike. Closer to 2020 Nike
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announced special design app called “Nike By You” which engaging with its customers by
satisfying expectations of the customers and making it possible for them to create their own pair
of sneakers. This system is able to design shoes almost instantly (Mathews, 2024).
That process is an integral part of the “Nike by You “scheme which most of the time includes
completely customization of the product which therefore made all through the AI machine. As
soon as customer has designed their shoe online, they can share it with their friends on social media
which therefore enhances user experience.
In 2024 Nike add “Generative AI for Product Design (2024) & Athlete Imagined Revolution
(A.I.R.) Project” (AI, Data & Analytics Network, 2024). The main objective of this research is to
analyze the use of the AI in Marketing, especially in Nike. Moreover, this research is going to list
advantages and disadvantages of AI in marketing and analyze experiences of other companies that
are using similar technique.
Methodology
This study employs a comprehensive analysis of Nike's implementation of artificial intelligence
across its operations, customer engagement, and product design. A case study approach is chosen,
as Nike’s extensive AI adoption provides a well-documented framework for assessing the
effectiveness of AI in a leading global company. By focusing on Nike’s use of AI, the study
illustrates the broader impact of these technologies within the sportswear industry.
Literature Review
In the modern world, production, customer service, design and of course use are actively
developing. Nike, a major brand and company, has successfully used Nike to customize customer
service and optimize supply chains.
Artificial intelligence helps not only manage, but also communicate with customers and solve their
problems. There are usually three main areas in scientific articles about the introduction of artificial
intelligence into business: understanding customer needs, improving operational efficiency, and
stimulating innovation. In these areas, artificial intelligence dominates human capabilities in terms
of the time for analysis and execution. One of the most significant advantages of artificial
intelligence is its ability to quickly and efficiently analyze large amounts of data, which of course
would take a lot of time for a person, while AI ultimately allows companies to provide services and
products personalized for each client separately.
In a study conducted in 2018 by Davenport and colleagues, it was demonstrated and proven that
artificial intelligence can greatly expand personalization opportunities and is particularly relevant in
customer-focused industries. Furthermore, artificial intelligence can be used to optimize various
aspects of business, such as inventory management and demand forecasting. A 2021 study by
Thorton and colleagues showed that artificial intelligence-based demand forecasts used by Nike
helped to better understand customer needs and optimize supply chains.
Artificial intelligence plays a crucial role in product development, allowing companies to predict
trends. According to Marr's (2022) research, companies investing in the development of artificial
intelligence-based products benefit from faster production cycles and the creation of more targeted
products.
This is especially true for Nike, which uses 3D modeling and predictive analysis to fine-tune
product design, thereby bringing it in line with current trends and consumer preferences. Nike's
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application of artificial intelligence in marketing and customer engagement through artificial
intelligence is based on creating an improved personalized experience for users. Nike uses AI
algorithms in its applications to analyze customer behavior and provide product recommendations.
Customized customer experiences Powered by artificial intelligence such as Nike's SNKRS app,
Nike offers personalized approach by recommending products based on customers' purchase
history and preferences. During his review of Nike's strategy, Marr 2022 showed that these
recommendations were based on data analysis and have been shown to increase customer
satisfaction and engagement. Similarly, other studies such as Stone 2021 confirmed the
effectiveness of artificial intelligence in increasing customer loyalty through individual approaches.
The direct interaction strategy with consumers: Using artificial intelligence in Nike's DTC approach
allows brands to communicate directly with customers and reduces dependence on third-party
retailers. Aim Research reported in an article how artificial intelligence supports Nike's success in
making platform-based decisions based on customers' interactions (Mathews, 2024b). Nike uses
intelligent analytics to predict consumer demand, thereby preventing inventory shortages and
overproduction. Select, Nike's artificial intelligence company acquired in 2019, developed
algorithms that analyze historical sales data to predict future demand. The acquisition is part of
Nike's overall strategy to build a data-driven supply chain.
Research by industry experts such as Lu and others. It indicates that artificial intelligence has a
positive impact on the environment in terms of reducing resource consumption and reducing
production time, especially in areas where demand is fluctuating a lot, such as retail. As a result,
Nike's production planning was more efficient, not only increasing sustainability, but also making
it more dynamic to respond to changing consumer needs. Nike also uses 3D modeling technology
to add artificial intelligence to the product development process. Through the acquisition of
Invertex, Nike received technology to scan customers' feet and recommend the best products. This
innovation transformed the development of products, allowing Nike to create shoes that are more
suitable for customers' individual preferences. Marr (2022) notes that this form of artificial
intelligence application not only increases customer satisfaction but also reduces return rates, as
customers will receive products that meet their expectations more.
The use of artificial intelligence by Nike in marketing, operations and product development has
allowed the company to maintain competitiveness, increase consumer satisfaction and streamline
its supply chain. According to the research, Nike's data-based approach and smart acquisitions in
artificial intelligence have simplified the transition to a more sustainable and efficient business
model. This literature analysis shows that artificial intelligence influences other factors in business,
influencing operational decisions and product innovations, increasing growth and improving
customer service. For companies such as Nike, artificial intelligence is not only a tool today; it is a
cornerstone of future growth.
Discussion
Secondary data from academic journals, business reports, and case studies on AI in business,
particularly within the retail and sportswear sectors, were analyzed. Sources include articles from
business databases (e.g., JSTOR, Google Scholars), industry publications, and reports from
consulting firms such as McKinsey and Company (2023), and AIM Research (Mathews, 2024c).
This data provides foundational knowledge of AI applications and will be used to contextualize
Nike’s strategies within industry standards. Content Analysis of Nike’s Digital Platforms: Nike’s
online platforms, including its website, mobile applications such as Nike SNKRS (n.d.), and social
media channels, will be systematically reviewed. This analysis seeks to document instances of AI
usage, such as personalized recommendations, virtual try-on features, and interactive customer
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engagement tools. This approach helps gauge how Nike’s AI tools enhance customer experience
and engagement.
Qualitative data obtained from the literature review and content analysis are analyzed using
thematic analysis. This method involves encoding text to identify key topics related to the use of
artificial intelligence in marketing, supply chain, and Nike product development strategies. Topics
such as “customer personalization,” “supply chain optimization,” and “predictive analytics” are
emerging that highlight Nike's AI-focused goals. Furthermore, quantitative analysis will include
indicators such as Nike's reported sales growth, customer engagement levels, and operational
performance indicators before and after the introduction of artificial intelligence technologies. In
addition, quantitative data on user engagement such as application usage statistics and customer
satisfaction indicators were analyzed to assess the impact of artificial intelligence on the quality of
customer service.
However, limitations of the study include the use of secondary data, which may not fully reflect
Nike's own artificial intelligence processes. Since detailed data on Nike's internal algorithms and
technology stack is not available to the general public, the research is limited to observable
applications and documented reports. In addition, this case study approach is focused exclusively
on Nike and cannot be extended to other companies in the sportswear industry.
The study focuses on validity and reliability by triangulating multiple data sources. By combining
additional literature with primary content analysis, the study provides a reliable and comprehensive
view of Nike's artificial intelligence strategies. The results have been cross-checked from various
sources to ensure accuracy, which will enhance both the internal and external reliability of the study.
Conclusion
This methodology provides a structured approach for analyzing Nike's application of AI across
multiple business domains. By integrating diverse data sources and analytical methods, the study
seeks to comprehensively evaluate the impact and efficacy of AI in transforming Nike’s approach
to customer engagement, product design, and operational management. This approach offers a
valuable template for understanding how large enterprises can leverage AI in modern, data-driven
business environments.
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