Integrated Management Research Project

Introduction, context, and aims and objectives

Background

In this digitised business environment, employing AI (artificial intelligence) exert influence on operational actions in numerous sectors including fashion and fitness. AI technology has been reconstruct these industries by serving businesses to establish products that are more modified and wearable fitness trackers (Romero-Tapiador et al. 2023). Moreover, the possible of AI to generate customised training regimens and workout schedules is one of the technology’s most important effects on the fitness sector. An individual’s fitness objectives, present level of fitness, and any limits or predilections they can have are all taken into consideration by AI algorithms. AI can use this data to create customised workout plans that address each person’s unique goals, such as increasing cardiovascular fitness, decreasing weight, or gaining muscle. On the other hand, AI has also been helping companies to predict and analyse market trends as well as consumer preferences regarding fitness-related gadgets (Choudhury et al. 2023). Considering the position of AI in the development of fitness tracking gadgets and marketing, this research will emphasize critically evaluating its effectiveness for an organisation like Nike.

The rationale for this research

In recent years, the demand for fitness-tracking gadgets has increased among the global population. In this regard, sports fashion organisation like Nike has been emphasizing to fulfil customer demand regarding fitness tracking gadgets. In other words, Nike is one of the globally renowned apparel and footwear companies, which is based in the US that has been offering fitness tracking gadgets not only in the US but also in its other operating markets considering the consumer demand. In this context, it is noted that the wearable market size in the US has been growing with a CAGR (Compound Annual Growth Rate) of 30.4% between 2023 and 3030 (Grandview Research, 2023). Moreover, the worldwide wearable AI market size was valued at $21.2 billion in 2022 and is predicted to grow at a CAGR of 29.8% during the same period (Grandview Research, 2023) (Refer to appendix).

Figure 1: Nike’s global market cap

(Source: Companies Market Cap, 2023)

Considering this type of demand for wearable AI-powered gadgets, Nike has emphasized the production of fitness-tracking gadgets to satisfy its sports and fitness-loving customers. With approximately $184.98 billion market capitalisation, Nike is a market leader in the manufacturing and distribution of athletic footwear, gear, and accessories (Companies Market Cap, 2023). Nike has a number of wrist-worn wearable available in the wearable market that provides customers with a variety of features, such as heart rate monitoring and basic activity tracking. Nike also developed the Nike+ platform to use technology to offer fresh, interesting workout experiences (Wearables, 2023).

On the other hand, Nike has also been observed to use AI for ensuring positive outcomes of its marketing activities. Specifically, for improving customer experience through marketing the organisation has been using AI (Choudhury et al. 2023). Through AI usage, the organisation has been improving its personalized offering and ensuring customer engagement (Kuznetsov, 2023). With the focus on addressing customer demand regarding fitness-tracking gadgets, understanding consumer behaviour, improve customer experience the organisation has been ensuring its financial stability and it has become the 61st most valuable organisation around the world according to its market capitalisation (Companies Market Cap, 2023). However, it is a notable fact that while using artificial intelligence in marketing as well as product development there is always a concern related to data protection. For example, in 2021, Fitbit user data was exposed in a breach that affected 61 million fitness tracker records (Landi, 2021). Thus, considering Nike and its fitness tracking gadget, the research will emphasize identifying challenges and relations encountered by the company in terms of using AI marketing tools.

Motivation to consider the topic

In recent years, the use of AI in marketing has been growing significantly and transforming the field of marketing in various sectors (Stone et al. 2020). Specifically, to sell fitness tracking gadgets companies like Nike have been integrating AI, which is benefiting them to a great extent. Thus, the main motivation to consider the current topic relies on analysing the impacts of integrating AI in marketing specification in terms of fitness tracking gadgets.

Aim and objectives

The research aims to critically evaluate the journey of Nike considering the Nike AI+ sensor as a fitness-tracking gadget, and also extract best practices from Nike’s innovations and experiences, providing valuable information that others in the fitness industry can use.

Research objectives

To find out best practices in AI Marketing by Nike for Product development
To investigate the challenges and lessons faced by Nike in Implementing AI Marketing tools
To draw parallels that can inform strategic decisions for other companies in the same sector
To Analyse customer reactions and responses to Nike’s use of AI Marketing tools

Research questions

What are the best practices in AI Marketing by Nike for Product development?
What are the challenges and lessons faced by Nike in Implementing AI Marketing tools?
What are the parallels that can inform strategic decisions for other companies in the same sector?
How do customers react and respond to Nike’s use of AI Marketing tools?

Annotated Bibliography

Critical analysis of the uses of AI at Nike

Owen, R., (2021). Artificial Intelligence at Nike – Two Current Use-Cases. Available at: https://emerj.com/ai-sector-overviews/artificial-intelligence-at-nike/ [Accessed on 15 December 2023]

In accordance with the current article by Owen (2021), Nike was founded in 1964 as Blue Ribbon Sports and as of 2021, the company operates with a market capital of more than $245 billion. The article examines that AI within Nike is used in 2 cases. The first is to “find the right fit” for the customers and secondly, it is being used to “customise the experience of customers based on the process of data mining”. As per the data of Nike, 60% of people in the global scenario seem to be wearing the wrong size of shoes and the company blames this issue on antiquated alongside two-dimensional sizing of shoes (Owen, 2021).

Figure 2: Right Fit application of Nike

(Source: Owen, 2021)

As a result of this, Nike created a fit tool with the help of AI that claims solutions through AI applications as stated above to find the right fit for all the customers. On the other hand, the current articles also state that Nike uses AI in order to customise the experiences of customers through the process of data mining (Owen, 2021). As a result of this, Nike has benefited in analysing the preferences and tastes of customers and predicting the demand of customers in the market. This provides useful benefits for enhancing sales and revenue margins in the market.

Critical evaluation of the usage of AI within Wearable Devices

Jin, C.Y., (2019, November). A review of AI Technologies for Wearable Devices. In IOP Conference Series: Materials Science and Engineering (Vol. 688, No. 4, p. 044072). IOP Publishing.

Jin (2019) in the current article stated that AI is highly being used within wearable devices in the current scenario. As AI is highly used for complex and rich data, therefore, technologies of AI are highly suitable for wearable devices produced by different companies such as Nike and others. The current study focuses on the fact that different types of wearable devices such as smartphone, smart watches, smart wristbands, smart glasses, smart shoes, smart earphones smart shocks and clothes and many others tends to use AI in order to enhance the level of innovation and assist people with high technological needs. In these devices, AI plays the role of implementing a built-in census to monitor daily activities phone calls, calorie consumption, heart rate, quality of sleep and many others. Contrary to this, Owen (2021) argued that AI also helps in tracking used data within these devices and fosters purchase rates. Henceforth, the use of AI within wearable devices is highly noted.

Usage of AI in enhancing personalisation and customer engagement

Kuznetsov, G., (2023). How Nike Customer Experience Uses Artificial Intelligence To Improve Engagement & Personalization. Available at: https://www.digitalsilk.com/digital-trends/nike-artificial-intelligence/ [Accessed on 15 December 2023]

Nike with the help of AI seems to be fueling the efforts of customer engagement further leading to high growth and development of its brand. The fitness industry as per the current report seems to be spending $35.8 billion in the area of AI and research (Kuznetsov, 2023). In respect to these, the current article also depicted that AI is used for personalized experiences and high customer engagement within Nike. Supported by Jin (2019), through the predictive tool used by Nike, the company has been beneficial in analysing previous purchase trends of customers along with their tastes and preferences. This helps the company to personalise user experiences within the market. Followed by personalization, the Triple Double Strategy of Nike helps in engaging customers towards the company through high innovation marketing speed and direct connection with all the customers.

AI foster innovative gaming experience within the fitness industry

Nike, (2023). Nike Launches Airphoria in Fortnite. Available at: https://about.nike.com/en/newsroom/releases/nike-launches-airphoria-in-fortnite [Accessed on 15 December 2023]

Currently fitness industry also seems to be implementing AI to evolve the experiences of gaming within the industry. For instance, the current article states that Nike aims at launching Airphoria in Fortnite which is considered to be an emerging experience of gaming through the aspects of innovation to serve the future needs of sports fandom (Nike, 2023). The technology is based on a combination of signature elements of designs such as Nike Air Max along with the landscape of Fortnite and allows players to engage with Air Max sneakers in a captivating and new way. As a result of this, it can be observed that AI within the fitness industry is elevating the concepts of gaming and sports effectively.

Critical assessment of the use of AI in generating powerful and engaging storytelling instances

AKQA US, (2023). Nike Uses AI to Pit Serena Williams Against Her Past Self. Available at: https://www.lbbonline.com/news/nike-uses-ai-to-pit-serena-williams-against-her-past-self [Accessed on 15 December 2023]

Another most interesting use of AI within the fitness industry reveals the area of generating powerful and engaging content and indulging in the area of storytelling activities in order to engage customers towards the organisation. From the current report, it can be observed that AI has been used effectively by Nike to showcase the evolution of Serena Williams over time (AKQA US, 2023). The article mainly focuses on the fact that AI has harnessed the power of advanced technology alongside machine learning to display the evolution of Serena Williams like never before. Supported by the previous article, AI is also effective in enhancing the experiences of gaming (Nike, 2023). However, Serena has been portrayed with the help of AI while engaging storytelling activities have been implemented in order to connect with customers effectively. This also predicted the future of the fitness industry through the game played by Serena Williams currently. Henceforth, AI is also used to predict the future through the current experience.

AI capitalises the area of web3, NFT and metaverse within the fitness industry

Marr, B., (2022). The Amazing Ways Nike Is Using The Metaverse, Web3 And NFTs. Available at: https://www.forbes.com/sites/bernardmarr/2022/06/01/the-amazing-ways-nike-is-using-the-metaverse-web3-and-nfts/?sh=68ac567356e9 [Accessed on 15 December 2023]

The current article states that AI has always been successful in enhancing in-store experience and e-commerce which shapes the strategy of a brand. It has been observed to be moving towards the capitalisation of NFTs, web3 and metaverse within the fitness industry. For instance, Nike developed a metaverse space that allows them in order to socialize and engage customers through their brand experiences (Marr, 2022). Moreover, Nike also uses NFT through the launch of NFT sneakers and many others to demonstrate innovation within the company and ensure personalization effectively. Most importantly, Nike also focuses on the use of digital data that reflects the use of web3 and NFT within the domain effectively. Henceforth, AI is implementing effective technologies within the fitness industry to shape its operations in a better way.

Data

Research approach

Research data can assist in offering researchers a detailed plan to adhere to while conducting their research. The process of designing a methodology simply supports researchers in choosing the best technique for their research outcome, it enables researchers to clearly state their research object use while addressing them with appropriate evidence and information (Gericke et al. 2020). Regarding this, the following research topic would be critically focused on evaluation based on qualitative data aspects. Regarding this, qualitative research allows the researcher to emphasise gathering information in the context of widening information sources. Social and behavioural research sciences are where qualitative research methodology effectively operates. Since today’s environment is complex it might be challenging to completely target individuals who have their perception towards significant things. The qualitative strategy would simply be comprehended because, with online research methods, the researcher would be able to be more descriptive and communicative with the understanding (Susanto et al. 2022). Regarding this, an evaluation of the fitness industry with the utilisation of AI along with a focus on product development in marketing practices.

Based on the understanding of the research onion, the researcher will proceed with the consideration of the philosophical approach where interpretivism would be considered. Interpretivism research philosophy supports the idea of focusing on understanding the physical occurrences while considering the complexities that are taken into consideration (Pervin and Mokhtar, 2022). Regarding this, with the support of interpretivism philosophy, the researcher would be able to produce high-validity information while focusing on the motivation of addressing research objectives.

Other than this, the consideration of the research approach has been noted to be very essential. Regarding this, the inductive research approach would be considered by scholars in terms of creating a hypothesis and generalising observations adequately. To create new theories and hypotheses, data are required to be gathered in a pattern that can modify the light of research findings (Guest and Martin, 2021). Thus, with inductive research, the researcher would be able to generate new ideas with a holistic viewpoint that can lead to discovering possibilities while improving understanding with flexibility.

With the support of qualitative understanding, the researcher will identify the research area effectively while observing a systematic approach to focus on the actual situation. Regarding this, a descriptive research design would be considered that will lead to observing and measuring the variables. Focusing on the design can lead to understanding the actual research context. Besides this, with the support of descriptive research design, the scholar would be able to perform cheap and high-quality research while considering diverse information that leads to thorough information while forming a better base for decisions (Budhwar et al. 2023).

Data collection

The process of acquiring and accessing data on reliable variables in terms of addressing research questions while testing the hypothesis is referred to as data collection. For the following study, the researcher would focus on utilising qualitative data that are being gathered by another party or to address a different research aspect (Busetto et al. 2020). Secondary qualitative data significantly provides an opportunity to maximise the data utility while having a cost-effective aspect that can lead to an advantageous option of storing data effectively. In this context, the secondary sources that would be considered for collecting information are Google Scholar, ProQuest, SAGE, ResearchGate, and numerous others, in terms of collecting information from journals. Besides this, in terms of websites, newspaper articles, organisational reports, and other authentic web pages would be considered.

Resources in terms of the journal and website research would be able to determine the objectives and research question effectively with better suitability and appropriateness of the information. This considered research would be specifically linked with the annotated bibliography that is specified to address the research objective and aims. In this context, it can be stated that with this consideration of qualitative understanding and research approaches the research objective and questions will be addressed and measured.

Analysis

The data analysis of this approach that would be considered to focus on the information would be secondary qualitative data analysis. In this context, a secondary qualitative data analysis would be presented based on already published information while addressing the research objective. This analysis is also presented as a thematic analysis that searches for patterns in terms of identifying themes from the research objective and questions (Braun and Clarke, 2022). Making sense of the information a relative subjective experience would begin from this research process. Besides this, in terms of identifying themes the research would critically focus on the process constructed by Barun and Clarke’s 6-step coding procedure that can impact on reflecting the research objective and questions efficiently (Braun and Clarke, 2021). Moreover, with thematic analysis, the researcher would be able to construct evidence-based information that can impact over-interpretation while simplifying the complexities of research objectives and answering research purposes.

Results

The current research has been focused on evaluating the use of AI in marketing and fitness tracking gadgets, considering Nike. It is expected that the research will include best practices of AI integration in marketing that have been helping Nike to maintain success as well as in terms of product development. On the other hand, the research findings will also include challenging aspects encountered by Nike to implement AI marketing tools and customers’ reactions to its AI usage in marketing. Marketing professionals in the fitness and fashion industry can be interested in the outcome of this research as they can get effective knowledge and understanding regarding AI usage in marketing product development and influence consumer behaviour to ensure sales rate. Most importantly, marketing professionals of businesses that manufacture fitness-tracking gadgets will be the main interested persons, as they will benefit from the outcomes of this research.

Critical Reflection

The following reflection will be presented based on the stages understood from Gibbs’s reflective cycle. In this context, the experience of presenting this research proposal has been very informative for me, as it has improved my understanding of Artificial Intelligence and the fitness industry as a whole. My thoughts about this experience are very positive, as it has given me a better understanding of constructing research along with reflecting on appropriate procedures that are required for evaluating and improving a research dissertation. For instance, I have understood the practices of AI marketing considering the product development for Nike along with focusing on future challenges that impact the implementation of marketing tools.

These are the areas, which has given me a better experience that has contributed to my all-over acknowledgement and understanding. Thus, from the following situation, it can be concluded that I have been able to handle the situation and information effectively with my critical thinking and analytical skills. However, it would be further developed with primary information, which has been disregarded for this research topic. Therefore, if I get a chance to do the task differently next time then my focus will be specifically on a primary survey to acquire information.

References

Owen, R., (2021). Artificial Intelligence at Nike – Two Current Use-Cases. Available at: https://emerj.com/ai-sector-overviews/artificial-intelligence-at-nike/ [Accessed on 15 December 2023]

Nike, (2023). Nike Launches Airphoria in Fortnite. Available at: https://about.nike.com/en/newsroom/releases/nike-launches-airphoria-in-fortnite [Accessed on 15 December 2023]

Grandview Research, (2023). Wearable AI Market Size, Share & Trends Analysis Report By Type (Smartwatches, Smart Eyewear, Smart Earwear), By Application, By Operations, By Component, By Region, And Segment Forecasts, 2023 – 2030. [Online]. Available at: https://www.grandviewresearch.com/industry-analysis/wearable-ai-market-report [Accessed on 14 December 2023]

Wearables, (2023). Nike. [Online]. Available at: https://wearables.com/collections/nike [Accessed on 14 December 2023]

Companies Market Cap, (2023). Market capitalization of Nike (NKE). [Online]. Available at: https://companiesmarketcap.com/nike/marketcap/ [Accessed on 14 December 2023]

Kuznetsov, G., (2023). How Nike Customer Experience Uses Artificial Intelligence To Improve Engagement & Personalization. [Online]. Available at: https://www.digitalsilk.com/digital-trends/nike-artificial-intelligence/ [Accessed on 14 December 2023]

Landi, H., (2021). Fitbit, Apple user data exposed in breach impacting 61M fitness tracker records. [Online]. Available at: https://www.fiercehealthcare.com/digital-health/fitbit-apple-user-data-exposed-breach-impacting-61m-fitness-tracker-records [Accessed on 14 December 2023]

Stone, M., Aravopoulou, E., Ekinci, Y., Evans, G., Hobbs, M., Labib, A., Laughlin, P., Machtynger, J. and Machtynger, L., (2020). Artificial intelligence (AI) in strategic marketing decision-making: a research agenda. The Bottom Line, 33(2), pp.183-200. https://research.stmarys.ac.uk/id/eprint/3892/1/AI%20in%20strategic%20marketing%20decision%20making%20final%20V2.pdf

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Choudhury, R.R., Phatak, M. and Joshi, I., (2023). Artificial Intelligence in Retail: Opportunities and Challenges for the Future. European Economic Letters (EEL), 13(4), pp.921-936. https://eelet.org.uk/index.php/journal/article/download/685/583

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Susanto, F., Ramos, P.P. and Ibrahim, M.A.A.S., (2022). Strategies of English Lecturers in Facilitating Interactional Communication of English Students During the New Normal Period of the Covid 19 Pandemic at UIN Fatmawati Sukarno Bengkulu for the 2021-2022 Academic Year. Al-Hijr, 1(2), pp.88-97. http://download.garuda.kemdikbud.go.id/article.php?article=2728468&val=24642&title=Strategies%20of%20English%20Lecturers%20in%20Facilitating%20Interactional%20Communication%20of%20English%20Students%20During%20the%20New%20Normal%20Period%20of%20the%20Covid%2019%20Pandemic%20at%20UIN%20Fatmawati%20Sukarno%20Bengkulu%20for%20the%202021-2022%20Academic%20Year

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Jin, C.Y., (2019, November). A review of AI Technologies for Wearable Devices. In IOP Conference Series: Materials Science and Engineering (Vol. 688, No. 4, p. 044072). IOP Publishing. https://iopscience.iop.org/article/10.1088/1757-899X/688/4/044072/pdf

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Integrated Management Research Project