Adoption And Impact Of AI In Marketing For The Fashion Industry

Research Aim and Objectives

Proliferation of technology and the emergence of different modernises technologies such as Artificial Intelligence or AI opens up opportunities for business entities to improvise their operational activities and performance efficiency. Marketing for businesses, specifically in the fashion industry is found to be one of the major aspects of promoting products and services in front of target audiences efficiently (Ma and Sun, 2020). In some cases, it is identified that due to a lack of marketer engagement, or persistence of inadequate customer data, business entities fail to establish strong brand recognition through a promotion that hinders business opportunities to drive success. In recent times, by perceiving the needs and efficiency of technologies in marketing, marketers in the fashion industry are trying to adopt or incorporate AI in their marketing or promotional activities. Anticipating customer data AI helps companies to improve the customer journey and Accelerate Business Efficiency (Gentsch, 2018).

Figure 1: AI-driven marketing landscape

(Source: Ma and Sun, 2020)

In this regard, this chapter is going to underline the key concept of the adoption of AI in marketing along with its impact in the present fashion business world. Challenges that influence businesses or marketers to adopt AI in marketing will also be underlined briefly. Research aim, question, and objectives, which will be considered for interpreting research-related data, will also be underlined in this chapter briefly.

The primary purpose and aim of this present research are to analyse and gather information related to the “usage and application of AI in marketing and promotional activities in the context of the fashion industry”.

The objectives that will be considered in the following section are:

• To investigate the concept and significance behind the incorporation of AI in marketing
• To determine the factors that maximise the adoption and usage of AI in marketing
• To identify the impact of AI in marketing in the fashion industry

The primary research question that will be considered is:

• What is the use of artificial intelligence or AI in marketing in relation to the fashion industry?

In order to accomplish the primary research question, the following sub-questions will be accomplished.

• What are the significance and factors behind the adoption of AI in marketing?
• How adoption of AI in marketing influences consumer purchasing decisions in the fashion industry?
• How different companies in the fashion industry are and will utilise the features of AI technologies in their digital marketing and promotional activities?

Insufficient customer information, inadequate product, brand, or service positioning, changing customer preferences, and others are found to be the present and growing challenges that marketers of every business entity operating in the fashion industry have witnessed. In some cases, it is identified that business entities are trying to determine strategic options or transform their business model digitally to overcome these issues (Orquin and Wedel, 2020). Thus, the problem statement of the present research is to address some challenges that global marketers in the fashion industry have witnessed along with the contribution of AI in marketing to resolve these challenges strategically.

Technology helps and supports businesses to prosper and grow by improving their operational activities and increasing their performance efficiency. Technology is considered as one of the strategic tools in relation to marketing that most of the business entities have already adopted to improve the customer journey and keep business competitive (Bala and Verma, 2018). With the emergence of different technologies, the adoption of AI in marketing is found to be growing rapidly presently due to its convenience, and attractive characteristics. As mentioned by Steinhoff and Palmatier (2021), with the rapidly changing customer preferences and purchasing behaviours, it becomes difficult for the marketers to collect relevant customer data through traditional marketing or only through digital marketing. Using AI in marketing enables marketers to collect data in real-time and maximise organisational chances to attract customers by promoting products, services, or brands in a more efficient manner.

Research Question

Figure 2: Features of AI in marketing

(Source: Columbus, 2019)

In the context of the above figure, a news report published in 2019 highlights, personalised experiences, effective customer segmentation. Automated interaction, predictive journey, and others are the key features that AI is associated with within marketing. Most of the business entities operating in the fashion industry have already incorporated AI in their marketing activities to improve the customer journey and foster their organisational growth. Marketers believed that application of AI in marketing helps to maximise sales by 52%, customer retention by 51%, and obtain success by launching new products by 49% respectively (Columbus, 2019).

Every business entity is found to incorporate a strategic approach in marketing to maximise its revenue, brand recognition, and profitability margin. It is identified that a global survey performed in 2020 reflects about 41% of the marketers mentioned that with the help of AI in marketing campaigns they have witnessed improved performance efficiency and revenue growth. Along with this, 38% of the marketers mentioned they are able to provide personalised consumer experiences through application of AI in promotional activities (Guttmann, 2021).

 

Figure 3: Outcome of business through AI-enabled marketing

(Source: Guttmann, 2021)

Considering this evidence, it can be articulated that after completion of the present research, it will help to obtain a clear insight into the way AI is being utilised for marketing practices in this digital age.

Figure 4: Structure of the dissertation

(Source: Created by learner) 

Artificial intelligence, (AI), Big Data, blockchain, the Internet of Things (IoT), and others are found to be disruptive technologies that have gradually changed the way businesses execute their operations. Among these disruptive technologies, AI is found to be one of the major technological disruptors that have been transforming the way businesses entities perform their marketing and promotional activities. Thus, in the following section brief illustrations of the selected research topic will be made. Consideration of suitable theoretical concepts critical interpretation of the sage of AI in promotional activities will be demonstrated.

In this fast-changing and competitive business entity, the primary focus of most of business entities is to implement strategic solutions to improve customers’ experience. Verma et al. (2021) in this regard underlines customers’ experiences that can be improved with the help of an AI-driven Chatbot based on Natural Language Processing (NLP). Application of AI helps marketers to analyse customers’ preferences, their demands, likes, interest, and others in real-time. This, in turn, positively influences businesses to maximise market competitiveness by meeting the demands of target audiences efficiently.

Problem Statement

Huang and Rust (2021) on the other hand, mentioned that AI in marketing has been gaining importance in the present business era, due to enhancing computing power, big data availability, emergence of machine learning models, and others. Considering the following figure, the author tries to highlight that application of AI in marketing provides opportunities to gain continuous improvements in the field of marketing research, marketing actions, and marketing strategy respectively.

Figure 5: AI for strategic marketing

(Source: Huang and Rust, 2021)

It is identified that application of AI technologies such as Big Data, Robotics, Machine Learning, Text Recognition, and others improve organisational responsiveness to customers’ demands and drive business success (Jarek and Mazurek, 2019). Other than this, it can also be mentioned that AI marketing helps to make automated decisions based on collected and analysed data along with economic and customer trends that directly influence upon marketing efforts.

Growing preferences and adoption of AI have been making a new path for businesses to maximise their service efficiency and market competitiveness. In the context of the following figure, the author AlSheibani et al. (2018) underlines AI readiness is found to be associated with aspects such as relative advantage, compatibility, organisational size, top management involvement, competitive pressure, and others that directly influence the adoption of AI. On the other hand, consumers these days are found to show their references towards obtaining real-time information about the products and services that they are willing to purchase. Application of AI in marketing helps companies to develop relationships between brands and customers that drive business prosperity (Surya, 2018).

Figure 6: Reason for AI adoption in business

(Source: AlSheibani et al. 2018)

Some certain factors that influence businesses to adopt AI in the practices of marketing are as follows:

Organisational profitability is found to be highly relied upon the customer’s engagement with specific brands. AI technology helps to involve personalised content in marketing that positively influences customer engagement, improves their loyalty and sales growth (Khrais, 2020). Demand for personalised content in advertising has increased rapidly, which can be considered as one of the key drivers or factors for the growing adoption of AI in marketing.

It is found to be complex to understand the changing customer’s demands and expectations from specific products, or brands to meet their requirements. In this regard, AI helps marketers to understand the perspectives and needs of the consumers and predict the buying behaviour of target customers in a more accurate and systematic manner (Jhala et al. 2018).

Research Significance

Businesses entities need to change their promotional activities in accordance with the change in customers’ demands and market trends. The incorporation of AI in marketing helps marketers to gain a clear insight into the emerging market trends and future business opportunities in accordance with which strategic decisions can be undertaken (Campbell et al. 2020).

Proliferation of technology has introduced a way to operate and execute business operations across the globe. It is identified that with the help of digital transformation and technological up-gradation business entities improvise their business processes and become responsive service providers that drive business success. As mentioned by Gursoy et al. (2019), with the help of technologies like AI, marketers are found to improve their ability to understand their target customers efficiently. Along with this, customers can build direct relationships with their proffered brands and obtain all the products and service-related information accurately before making any investment. On the other hand, by leveraging AI technologies, marketers are found to segregate their target customers and provide customer-centric services that positively influence business sustainability within the market (Prakash, 2021).

In the context of the fashion industry, it is identified that application of AI helps marketers to develop 3D digital fashion models and enhance the chance of introducing “virtual fitting rooms” that enhance customer-shopping journeys (Chen, 2021). Along with this, AI-based personalised and customised shopping experiences also provide new opportunities for marketers to maximise customers’ engagement with brands. This positively influences upon fashion businesses in terms of retaining customers and increasing profitability margin.

Diffusion innovation theory illustrates the way new technologies, products, or the target customers are adopting new services over a certain time. Qazi et al. (2018) mentioned that laggards, late majority, innovators, early adopters, and early majority are the key aspects that define the way people or consumers accept new technologies or products. For example, in the context of AI technologies, it can be interlinked with the early adopter’s aspects. The key reason behind this statement is that people or consumers these days are found to show their interest in usage of new technologies to purchase their required items. In the context of fashion industry, adoption of AI in marketing can enable the marketers to visualise the perspectives of customers accurately in accordance to which they could offer them efficient services (Dimitrieska et al. 2018).

Figure 7: Diffusion innovation theory

(Source: Qazi et al. 2018)

This theoretical concept illustrates that new technology or innovation can minimise the overall production cost and maximise the product demand with the market. Marketers who can incorporate AI technologies in their promotional or marketing practices minimise the operational cost that might be generated with traditional marketing approaches (Malerba and McKelvey, 2020). Along with this, AI technologies enable fashion marketers to promote products and services more efficiently and in real-time, which help to attract customers.

Structure of the Dissertation

Figure 8: Schumpeter’s innovation theory

(Source: Malerba and McKelvey, 2020)

It is identified that usage of AI in marketing generates challenges such as inadequate technological infrastructure, poor data quality, security issues, inadequate budgets, and others that minimise the chance for businesses to utilise AI in their operational activities. However, these challenges have not been highlighted and addressed in this section creating gaps in the entire literature review section.

In the context above discussion, marketing needs to be executed in an efficient and accurate manner as sales growth and profitability margin has highly relied upon the way products or services are being promoted in front of the trade customers. It is identified that Application of AI in marketing has been growing as AI helps marketers in the fashion industry to obtain real-time customer data in accordance with which they can improve their business operations and service facilities. AI in marketing has witnessed rapid momentum because of its practical significance in future and present businesses. On the other hand, it is identified that most of the marketers believe that after incorporation of AI they have witnessed sales growth and customer retention. Thus, in the next adjoining section brief evaluation of the methodological approach that will be considered to interpret the research-related data will be underlined.

Selection of appropriate methodological approaches enhances the chance of accomplishing research goals by obtaining desired research outcome. In the following section, methodological approaches such as philosophy, approach, design, and others that are being considered for data interpretation will be underlined. A brief justification behind selection of each of the selected methodologies will also be provided.

Research philosophy is considered as the beliefs of the researcher regarding the way they are intending to collect, use and analyse research-related data. Philosophical approach can be categorised in three ways such as interpretivism, realism, and positivism respectively. In order to execute and interpret the present research information, interpretivism philosophical approach is being considered (Ahlskog, 2020). The key reason behind this selection is that as the overall research is going to be based upon secondary sources, thus consideration of interpretivism approach enhances the chance of the researchers to obtain desired research outcome. Along with this, utilisation of the mentioned philosophy helps to perform in-depth illustrations regarding the usage of AI in marketing and enhance the chance to meet the research aim accurately.

Considering a suitable research approach, researchers can formulate and identify the path they can utilise to report and study the findings of specific research. As mentioned by Tjora (2018), research approaches are found to be systematic approaches that illustrate the steps of the broad assumptions regarding the methods for data analysis, interpretations, as well as collections. Deductive and inductive are found to be two specific research approaches among which, the present research has considered deductive approaches. Pearse (2019) mentioned that utilisation of incorporation of deductive approaches enables researchers to determine the causal relationship between the selected concept and identified variables. In the context of present research, the deductive approach will help to analyse the interrelationship between application of AI and marketing approach in a systematic and accurate manner.

Literature Review

Explanatory, exploratory, and descriptive are found to be the three types of research design that serves as beneficial to generate fruitful research outcome according to the research requirements (Doyle et al. 2020). Descriptive design is being utilised in this research as it helps to evaluate the information regarding the usage and application of AI in marketing, which can be interlinked, to non-quantified topics.

Methods for collecting data are considered as the most crucial aspects of research activities as it helps the researchers to find suitable and accurate solutions for the identified issues. Secondary and primary are found to be the two types of methods that can be utilised for collecting research-related relevant data (Johnston, 2017). This present research is based on secondary data methods in order to perform an in-depth interpretation of the research relevant data. In order to execute the entire research activities based on secondary data, this research has considered secondary information obtained from already published books, journals, newspapers, articles, and others (Rosinger and Ice, 2019). Consideration of the mentioned methods helps to analyse the way AI has been utilised in marketing activities in a cost-effective and logical manner.

Strategies that are being utilised in analysing data are found to be systematic application of logical techniques of statistical tools to interpret and evaluate each of the collected data. Quantitative and qualitative are the two strategic data analysis approaches among which qualitative analysis is being utilised in this research. Qualitative analysis is being made based on theme-based analysis that helps to evaluate the research topic in a more accurate and logical manner (Lowe et al. 2018). For example, the selected research topic is being categorised into sub-themes such as application AI, companies that have been utilising AI in marketing, future of AI in marketing, and others. This enhances the chance to determine the way AI has been utilising marketing-related activities in this dynamic business world.

Research ethics are important aspects as it helps the researchers to maintain integrity, honesty, and confidentiality while executing each of the research-related activities. While executing the present research, the Privacy Act 1988 is being followed to maintain the validity and reliability of the entire research (Legislation, 2022). Along with this, a suitable referencing style is being followed throughout the research to provide acknowledgment of the author whose perspective and research are being utilised.

Throughout analysis is mainly based upon secondary information without considering the perspective of marketers, managers, employees, and managers of real-world businesses. Omitting primary data might restrict the entire research evaluation to a certain extent creating limitations to the entire study.

In relation to the above discussion, it can be mentioned that methodological approach plays a significant role in research activities as it enhances the chance for researchers to generate desired research outcomes. The identified research methodological approach is found to be effective for the present research as it helps to collect, interpret and evaluate research-related information in a logical and systematic format. 

AI marketing is considered as the systematic approach to leverage concepts of AI like Machine Learning (ML) and customer data for anticipating customers’ purchasing intentions based on which customer’s journey can be improved. AI allows marketers to develop attractive marketing strategies and improvise the way businesses convert, nurture, and attract prospects. Thus, in the following sections, an in-depth illustration of the research topic will be made. Along with this, based on the methodological approach as identified earlier, different themes related to the selected research topic will be interpreted and evaluated to accomplish the predefined research aim.

Analysing consumer behaviour plays a significant role for fashion businesses entities, as marketers believe that it helps them to determine the factors or aspects that directly influence purchasing decisions of customers. As mentioned by Prentice and Nguyen (2020), determining the way consumers change their perceptions and decide to purchase a product, marketers can determine the specific clothing products that are required along with the obsolete fashion range in accordance to which strategic business decisions can be made. Along with this, knowing consumer behaviour also assists marketers to receive the way they require to present or promote their services or products to enhance customer engagement and convince them to make a purchase.

It is identified that with the usage of AI, 49% of customers are willing to purchase their required items frequently followed by 34% of consumers who are willing to invest more money (Brooks, 2020).

Figure 9: Buying pattern of customers with usage of AI

(Source: Mathis, 2021)

AI is found to play a dominant role in the field of B2B and B2C marketing providing opportunities for marketers to improve their marketing-related activities. The key reason behind this statement, the author (H Mussa, 2020) underlines as compared to social media platforms such as Facebook, Instagram, Twitter, YouTube, and others, AI helps marketers to establish efficient personalised interaction with attractive customer’s experiences through Chatbot. On the other hand, 79% of marketers believed that with the application of AI, they improvise and increase the efficiency of their marketing activities.

Figure 10: Efficacy of Chatbot

(Source: Statista, 2022)

In the context of the above figure, considering the perspective of baby boomers and millennial, it is identified that customers’ 24 hours service is found to be one of the major factors that Chatbot can offer to the customers. In addition to this, Chatbot also provides instant response, efficient communication, detailed information, and others about specific products, brands, or services that directly influence consumer purchase behaviour (Statista, 2022).

 

Figure 11: AI in marketing

(Source: Allen, 2017)

In the context of the above figure, it is identified that smart curation of content, voice search, application personalisation, predictive analytics, and others are the key features that influence marketers to adopt AI in their marketing activities (Allen, 2017). This in turn enhances their chance to gain proactive engagement of customers with the brand and enhances the chance for maintaining market competitiveness and business growth. There are different types of brands that have already incorporated AI in their marketing and those companies are going to be underlined in the next adjacent section.

The acceptance of Machine Learning (ML) and AI is projected to increase to $2.6 Trillion from $1.4 Trillion in terms of resolving challenges related to sales and marketing. The usage of AI in marketing is found to have soared to 84% during the financial year 2020 from 29% in 2018 respectively (Columbus, 2021). It is identified that traditional marketing tools are found to be associated with challenges such as lack of scalability, comprehensiveness, and flexibility to address and assist modernise business entities to resolve business-related challenges. On the other hand, it is identified that with the growing dependencies on digital technology and maximisation of online audiences, marketers are required to incorporate AI to maintain their competitiveness and enhance their customers (Sima et al. 2020). 

Figure 12: Growth of AI application in Marketing

(Source: Columbus, 2021)

In this regard, the case of renowned fashion brand H&M can be interlinked as the company has been utilising AI to understand the perceptions of customers and enhance customer engagement with the brands. It is identified that AI platforms that H&M has been utilising offer customised and personalised recommendations to its potential customers.

H&M has been utilising an AI-based Chatbot to support mobile customers in navigating their searches. This platform allows and guides customers to perceive their desired products based on which customer can make their purchase decision. Along with this, H&M’s Chatbot also offers outfit suggestions, emerging style, and attractive shopping experiences that help to gain customer loyalty (Faggella, 2019).  On the other hand, another fashion brand Dior utilises “A Beauty Assistant” through Dior Insider to offer personalised cosmetics and skincare shopping experiences to their respective customers. Nike also leverages their brands through utilisation of AI in its promotional activities. The company utilises AI-based solutions to enhance customer experiences and predict their purchasing habits in accordance with which they introduce their new services and products ranges (Kumar, 2020).

These AI-based solutions allow the company to align its business operations with the emerging or changing market trends and improve customers’ journeys. Application of AI enhances the chance for the companies to strengthen their promotional activities accurately and establish their strong brand recognition across the international market.

In this digital era and fast-changing consumer preferences, business entities are required to become responsive and must be aware of the emerging market environment in order to keep competitive. As mentioned by Brill et al. (2019), knowing customers’ perspectives and theoretical interests is found to be one of the major aspects and complex factors for marketers as it directly influences organisational revenue generation, growth, and profitability margin. A primary way through which AI can transform the existing digital marketing is by offering improved versions of users’ experiences. For example, AI has the potential to predict a wide range of purchasing motivators and customers’ behaviours in real-time. This positively enhances the chance for businesses to maximise their productivity by meeting those customers’ demands accurately (De Bruyn et al. 2020).

Figure 13: Growth of AI-based marketing

(Source: Businesswire, 2018)

In the context of the above figure, the AI-based personalised market is expected to increase at a CAGR rate of 13% within 2022 (Businesswire, 2018). For example, with the help of AI, marketers can provide real-time experiences to the target customers to try their products through company websites or applications. This allows the customers to determine where their selected product would meet the requirement in accordance to which they can make a purchase decision. At the same time, this in turn, also allows marketers to promote their products, or services in a more attractive manner creating strong customer engagement with brands (Libai et al. 2020). Thus, it can be mentioned that AI has been gradually improving the state of marketing practices and enhancing the chance for businesses to build strong relationships with the target customers by meeting their needs efficiently.

In the context of the above discussion, it can be mentioned that emerging technologies like AI have been improvising marketing along with its associated business practices that strengthen business competitiveness and productivity. On the other hand, companies like Dior, H&M, and Nike have already incorporated AI by utilising Chatbot to understand and predict the customers’ purchasing behaviour in accordance to which they develop or change their business plans. It is also identified that gradually by perceiving the effectiveness and importance of AI in promotional activity; marketers also show their willingness to incorporate AI in the operational process to improve their performance efficiency accurately.

Conclusion

In the context of overall discussion and data interpretation, it can be articulated that the emergence of technology has changed the business operation in a modernised way. Most of the business entities are trying to adopt technology-based solutions to improve their performance efficiency. The present research has shown that by perceiving the needs and effectiveness of emerging technologies, marketers have shown their preferences for incorporating AI in its promotional or marketing practices. It is identified that AI provides a new way for marketers to promote their brands, services, and products in front of their target market and accelerate business efficiency by improving customers’ journeys.

On the other hand, it is seen that most of the renowned companies such as H&M, Nike, and Dior have already been utilising AI-based solution Chatbot to predict and identify customer’s purchasing intentions based on which they tried to provide customer-centric service facilities. On the other hand, factors such as personalised content, identification of market trends in real-time, rapid changes in customer behaviour, and others influence marketers to adopt AI-based solutions like Chatbot. From the overall discussion, it can be stated that application of AI for marketing creates a wide range of business opportunities for future growth and stability.

Objective 1 is found to be emphasised upon determining the concept and significance behind usage of AI for marketing, which has been met in the literature review section. The key reason behind this statement is that in section 2.2 of chapter 2, it has mentioned the importance of AI for marketing. Along with this, the way features of AI helped to improve the efficiency of marketing has also been highlighted.

The objective 2 is to investigate the factors that influence the adoption of AI in the marketing activities. In section, 2.3 of the literature review, different factors such as customer’s preferences, customised content, business efficiency, and others have been highlighted. Each of the factors provides an idea regarding the reason behind growing preferences for AI incorporation in marketing. In 4.2.1 of the data analysis section, an illustration of the way AI has been influencing consumer purchasing behaviours has been drawn. Thus, it can be mentioned that objective two of the present research has met in chapter 2 and chapter 4.

In order to show the impact of AI in the promotional activities, the research has provided a detailed illustration in chapters 2 and chapter 4. The key reason behind this statement is that in section 2.4 of the literature, the impact of AI has been highlighted and in 2.5 critical evaluations has been made by considering suitable theoretical concepts. On the other hand, in the data analysis chapter by considering company examples, the usage of AI marketing has been interpreted. Thus, the third objective was met in both chapter 2 and chapter 4.

While incorporating AI in marketing, companies can consider the following recommendation to enhance their chance to obtain marketing success after incorporating AI.

It is important for business entities that are highly related to customers’ data to perceive the business opportunities in relation to the customer’s needs and exceptions. This would maximise the chance for businesses to analyse the marketing field within which they need to incorporate AI to generate maximised value for the business and drive business growth. Along with business opportunities, it will help marketers to analyse the metrics that they should need to construct to analyse the impact of AI on their overall organisational performance.

Employees are found to be the key strength for any business entity as they incorporate their proactive engagement to drive business success. Thus, it would be important for companies to analyse their internal capabilities and expertise before incorporating AI. Companies will require to provide suitable training to their respective employees so that they can understand the way marketing approaches or marketing goals need to be accomplished with the help of AI.

It would be important for companies who are willing to incorporate AIR in their marketing to determine a candidate or expertise that has the potential to execute marketing activities with usage of AI technology-based solutions. Thus, before implementing AI, it would be important for companies to develop a strong team with highly skilled experts who can efficiently utilise modernised technology to enhance customer engagement with brands.

In the context of the overall discussion, the research is found to be based on secondary analysis by considering the way AI has been transforming marketing approaches to improve business activities. However, the adoption of AI in business operations or in marketing is found to be associated with a wide range of challenges such as deployment complexity, privacy, regulation, data theft, and others. These negative sides of AI marketing have not been addressed in this research creating gaps in the entire study.

Thus, in the future, information obtained from this research can be utilised to evaluate the way emerging AI technologies such as Big Data, Blockchain, Deep Learning, and others can address the identified issues. Along with these, how these technologies transform the future marketing approach can also be underlined.

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